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Top Data Analytics Certifications

What is data analytics?In the world of IT, every small bit of data count; even information that looks like pure nonsense has its significance. So, how do we retrieve the significance from this data? This is where Data Science and analytics comes into the picture.  Data Analytics is a process where data is inspected, transformed and interpreted to discover some useful bits of information from all the noise and make decisions accordingly. It forms the entire basis of the social media industry and finds a lot of use in IT, finance, hospitality and even social sciences. The scope in data analytics is nearly endless since all facets of life deal with the storage, processing and interpretation of data.Why data analytics? Data Analytics in this Information Age has nearly endless opportunities since literally everything in this era hinges on the importance of proper processing and data analysis. The insights from any data are crucial for any business. The field of data Analytics has grown more than 50 times from the early 2000s to 2021. Companies specialising in banking, healthcare, fraud detection, e-commerce, telecommunication, infrastructure and risk management hire data analysts and professionals every year in huge numbers.Need for certification:Skills are the first and foremost criteria for a job, but these skills need to be validated and recognised by reputed organisations for them to impress a potential employer. In the field of Data Analytics, it is pretty crucial to show your certifications. Hence, an employer knows you have hands-on experience in the field and can handle the workload of a real-world setting beyond just theoretical knowledge. Once you get a base certification, you can work your way up to higher and higher positions and enjoy lucrative pay packages. Top Data Analytics Certifications Certified Analytics Professional (CAP) Microsoft Certified Azure Data Scientist Associate Cloudera Certified Associate (CCA) Data Analyst Associate Certified Analytics Professional (aCAP) SAS Certified Data Analyst (Using SAS91. Certified Analytics Professional (CAP)A certification from an organisation called INFORMS, CAP is a notoriously rigorous certification and stands out like a star on an applicant's resume. Those who complete this program gain an invaluable credential and are able to distinguish themselves from the competition. It gives a candidate a comprehensive understanding of the analytical process's various fine aspects--from framing hypotheses and analytic problems to the proper methodology, along with acquisition, model building and deployment process with long-term life cycle management. It needs to be renewed after three years.The application process is in itself quite complex, and it also involves signing the CAP Code of Ethics before one is given the certification. The CAP panel reviews each application, and those who pass this review are the only ones who can give the exam.  Prerequisite: A bachelor’s degree with 5 years of professional experience or a master's degree with 3 years of professional experience.  Exam Fee & Format: The base price is $695. For individuals who are members of INFORMS the price is $495. (Source) The pass percentage is 70%. The format is a four option MCQ paper. Salary: $76808 per year (Source) 2. Cloudera Certified Associate (CCA) Data Analyst Cloudera has a well-earned reputation in the IT sector, and its Associate Data analyst certification can help bolster the resume of Business intelligence specialists, system architects, data analysts, database administrators as well as developers. It has a specific focus on SQL developers who aim to show their proficiency on the platform.This certificate validates an applicant's ability to operate in a CDH environment by Cloudera using Impala and Hive tools. One doesn't need to turn to expensive tuitions and academies as Cloudera offers an Analyst Training course with almost the same objectives as the exam, leaving one with a good grasp of the fundamentals.   Prerequisites: basic knowledge of SQL and Linux Command line Exam Fee & Format: The cost of the exam is $295 (Source), The test is a performance-based test containing 8-12 questions to be completed in a proctored environment under 129 minutes.  Expected Salary: You can earn the job title of Cloudera Data Analyst that pays up to $113,286 per year. (Source)3. Associate Certified Analytics Professional (aCAP)aCAP is an entry-level certification for Analytics professionals with lesser experience but effective knowledge, which helps in real-life situations. It is for those candidates who have a master’s degree in a field related to data analytics.  It is one of the few vendor-neutral certifications on the list and must be converted to CAP within 6 years, so it offers a good opportunity for those with a long term path in a Data Analytics career. It also needs to be renewed every three years, like the CAP certification. Like its professional counterpart, aCAP helps a candidate step out in a vendor-neutral manner and drastically increases their professional credibility.  Prerequisite: Master’s degree in any discipline related to data Analytics. Exam Fee: The base price is $300. For individuals who are members of INFORMS the price is $200. (Source). There is an extensive syllabus which covers: i. Business Problem Framing, ii. Analytics Problem Framing, iii. Data, iv. Methodology Selection, v. Model Building, vi. Deployment, vii. Lifecycle Management of the Analytics process, problem-solving, data science and visualisation and much more.4. SAS Certified Data Analyst (Using SAS9)From one of the pioneers in IT and Statistics - the SAS Institute of Data Management - a SAS Certified Data Scientist can gain insights and analyse various aspects of data from businesses using tools like the SAS software and other open-source methodology. It also validates competency in using complex machine learning models and inferring results to interpret future business strategy and release models using the SAS environment. SAS Academy for Data Science is a viable institute for those who want to receive proper training for the exam and use this as a basis for their career.  Prerequisites: To earn this credential, one needs to pass 5 exams, two from the SAS Certified Big Data Professional credential and three exams from the SAS Certified Advanced Analytics Professional Credential. Exam Fee: The cost for each exam is $180. (Source) An exception is Predictive Modelling using the SAS Enterprise Miner, costing $250, This exam can be taken in the English language. One can join the SAS Academy for Data Science and also take a practice exam beforehand. Salary: You can get a job as a SAS Data Analyst that pays up to $90,000 per year! (Source) 5. IBM Data Science Professional CertificateWhenever someone studies the history of a computer, IBM (International Business Machines) is the first brand that comes up. IBM is still alive and kicking, now having forayed into and becoming a major player in the Big Data segment. The IBM Data Science Professional certificate is one of the beginner-level certificates if you want to sink your hands into the world of data analysis. It shows a candidate's skills in various topics pertaining to data sciences, including various open-source tools, Python databases, SWL, data visualisation, and data methodologies.  One needs to complete nine courses to earn the certificate. It takes around three months if one works twelve hours per week. It also involves the completion of various hands-on assignments and building a portfolio. A candidate earns the Professional certificate from Coursera and a badge from IBM that recognises a candidate's proficiency in the area. Prerequisites: It is the optimal course for freshers since it requires no requisite programming knowledge or proficiency in Analytics. Exam Fee: It costs $39 per month (Source) to access the course materials and the certificate. The course is handled by the Coursera organisation. Expected Salary: This certification can earn you the title of IBM Data Scientist and help you earn a salary of $134,846 per annum. (Source) 6. Microsoft Certified Azure Data Scientist AssociateIt's one of the most well-known certifications for newcomers to step into the field of Big Data and Data analytics. This credential is offered by the leader in the industry, Microsoft Azure. This credential validates a candidate's ability to work with Microsoft Azure developing environment and proficiency in analysing big data, preparing data for the modelling process, and then progressing to designing models. One advantage of this credential is that it has no expiry date and does not need renewal; it also authorises the candidate’s extensive knowledge in predictive Analytics. Prerequisites: knowledge and experience in data science and using Azure Machine Learning and Azure Databricks. Exam Fee: It costs $165 to (Source) register for the exam. One advantage is that there is no need to attend proxy institutions to prepare for this exam, as Microsoft offers free training materials as well as an instructor-led course that is paid. There is a comprehensive collection of resources available to a candidate. Expected Salary: The job title typically offered is Microsoft Data Scientist and it typically fetches a yearly pay of $130,993.(Source) Why be a Data Analytics professional? For those already working in the field of data, being a Data Analyst is one of the most viable options. The salary of a data analyst ranges from $65,000 to $85,000 depending on number of years of experience. This lucrative salary makes it worth the investment to get a certification and advance your skills to the next level so that you can work for multinational companies by interpreting and organising data and using this analysis to accelerate businesses. These certificates demonstrate that you have the required knowledge needed to operate data models of the volumes needed by big organizations. 1. Demand is more than supply With the advent of the Information Age, there has been a huge boom in companies that either entirely or partially deal with IT. For many companies IT forms the core of their business. Every business has to deal with data, and it is crucial to get accurate insights from this data and use it to further business interests and expand profits. The interpretation of data also aims to guide them in the future to make the best business decisions.  Complex business intelligence algorithms are in place these days. They need trained professionals to operate them; since this field is relatively new, there is a shortage of experts. Thus, there are vacancies for data analyst positions with lucrative pay if one is qualified enough.2. Good pay with benefitsA data analyst is an extremely lucrative profession, with an average base pay of $71,909 (Source), employee benefits, a good work-home balance, and other perks. It has been consistently rated as being among the hottest careers of the decade and allows professionals to have a long and satisfying career.   Companies Hiring Certified Data Analytics Professionals Oracle A California based brand, Oracle is a software company that is most famous for its data solutions. With over 130000 employees and a revenue of 39 billion, it is surely one of the bigger players in Data Analytics.  MicroStrategy   Unlike its name, this company is anything but micro, with more than 400 million worth of revenue. It provides a suite of analytical products along with business mobility solutions. It is a key player in the mobile space, working natively with Android and iOS.   SAS   One of the companies in the list which provides certifications and is also without a doubt one of the largest names in the field of Big Data, machine learning and Data Analytics, is SAS. The name SAS is derived from Statistical Analysis System. This company is trusted and has a solid reputation. It is also behind the SAS Institute for Data Science. Hence, SAS is the organisation you would want to go to if you're aiming for a long-term career in data science.    Conclusion To conclude, big data and data Analytics are a field of endless opportunities. By investing in the right credential, one can pave the way to a viable and lucrative career path. Beware though, there are lots of companies that provide certifications, but only recognised and reputed credentials will give you the opportunities you are seeking. Hiring companies look for these certifications as a mark of authenticity of your hands-on experience and the amount of work you can handle effectively. Therefore, the credential you choose for yourself plays a vital role in the career you can have in the field of Data analytics.  Happy learning!    
Top Data Analytics Certifications
Abhresh
Abhresh

Abhresh Sugandhi

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Abhresh is specialized as a corporate trainer, He has a decade of experience in technical training blended with virtual webinars and instructor-led session created courses, tutorials, and articles for organizations. He is also the founder of Nikasio.com, which offers multiple services in technical training, project consulting, content development, etc.

Posts by Abhresh Sugandhi

Top Data Analytics Certifications

What is data analytics?In the world of IT, every small bit of data count; even information that looks like pure nonsense has its significance. So, how do we retrieve the significance from this data? This is where Data Science and analytics comes into the picture.  Data Analytics is a process where data is inspected, transformed and interpreted to discover some useful bits of information from all the noise and make decisions accordingly. It forms the entire basis of the social media industry and finds a lot of use in IT, finance, hospitality and even social sciences. The scope in data analytics is nearly endless since all facets of life deal with the storage, processing and interpretation of data.Why data analytics? Data Analytics in this Information Age has nearly endless opportunities since literally everything in this era hinges on the importance of proper processing and data analysis. The insights from any data are crucial for any business. The field of data Analytics has grown more than 50 times from the early 2000s to 2021. Companies specialising in banking, healthcare, fraud detection, e-commerce, telecommunication, infrastructure and risk management hire data analysts and professionals every year in huge numbers.Need for certification:Skills are the first and foremost criteria for a job, but these skills need to be validated and recognised by reputed organisations for them to impress a potential employer. In the field of Data Analytics, it is pretty crucial to show your certifications. Hence, an employer knows you have hands-on experience in the field and can handle the workload of a real-world setting beyond just theoretical knowledge. Once you get a base certification, you can work your way up to higher and higher positions and enjoy lucrative pay packages. Top Data Analytics Certifications Certified Analytics Professional (CAP) Microsoft Certified Azure Data Scientist Associate Cloudera Certified Associate (CCA) Data Analyst Associate Certified Analytics Professional (aCAP) SAS Certified Data Analyst (Using SAS91. Certified Analytics Professional (CAP)A certification from an organisation called INFORMS, CAP is a notoriously rigorous certification and stands out like a star on an applicant's resume. Those who complete this program gain an invaluable credential and are able to distinguish themselves from the competition. It gives a candidate a comprehensive understanding of the analytical process's various fine aspects--from framing hypotheses and analytic problems to the proper methodology, along with acquisition, model building and deployment process with long-term life cycle management. It needs to be renewed after three years.The application process is in itself quite complex, and it also involves signing the CAP Code of Ethics before one is given the certification. The CAP panel reviews each application, and those who pass this review are the only ones who can give the exam.  Prerequisite: A bachelor’s degree with 5 years of professional experience or a master's degree with 3 years of professional experience.  Exam Fee & Format: The base price is $695. For individuals who are members of INFORMS the price is $495. (Source) The pass percentage is 70%. The format is a four option MCQ paper. Salary: $76808 per year (Source) 2. Cloudera Certified Associate (CCA) Data Analyst Cloudera has a well-earned reputation in the IT sector, and its Associate Data analyst certification can help bolster the resume of Business intelligence specialists, system architects, data analysts, database administrators as well as developers. It has a specific focus on SQL developers who aim to show their proficiency on the platform.This certificate validates an applicant's ability to operate in a CDH environment by Cloudera using Impala and Hive tools. One doesn't need to turn to expensive tuitions and academies as Cloudera offers an Analyst Training course with almost the same objectives as the exam, leaving one with a good grasp of the fundamentals.   Prerequisites: basic knowledge of SQL and Linux Command line Exam Fee & Format: The cost of the exam is $295 (Source), The test is a performance-based test containing 8-12 questions to be completed in a proctored environment under 129 minutes.  Expected Salary: You can earn the job title of Cloudera Data Analyst that pays up to $113,286 per year. (Source)3. Associate Certified Analytics Professional (aCAP)aCAP is an entry-level certification for Analytics professionals with lesser experience but effective knowledge, which helps in real-life situations. It is for those candidates who have a master’s degree in a field related to data analytics.  It is one of the few vendor-neutral certifications on the list and must be converted to CAP within 6 years, so it offers a good opportunity for those with a long term path in a Data Analytics career. It also needs to be renewed every three years, like the CAP certification. Like its professional counterpart, aCAP helps a candidate step out in a vendor-neutral manner and drastically increases their professional credibility.  Prerequisite: Master’s degree in any discipline related to data Analytics. Exam Fee: The base price is $300. For individuals who are members of INFORMS the price is $200. (Source). There is an extensive syllabus which covers: i. Business Problem Framing, ii. Analytics Problem Framing, iii. Data, iv. Methodology Selection, v. Model Building, vi. Deployment, vii. Lifecycle Management of the Analytics process, problem-solving, data science and visualisation and much more.4. SAS Certified Data Analyst (Using SAS9)From one of the pioneers in IT and Statistics - the SAS Institute of Data Management - a SAS Certified Data Scientist can gain insights and analyse various aspects of data from businesses using tools like the SAS software and other open-source methodology. It also validates competency in using complex machine learning models and inferring results to interpret future business strategy and release models using the SAS environment. SAS Academy for Data Science is a viable institute for those who want to receive proper training for the exam and use this as a basis for their career.  Prerequisites: To earn this credential, one needs to pass 5 exams, two from the SAS Certified Big Data Professional credential and three exams from the SAS Certified Advanced Analytics Professional Credential. Exam Fee: The cost for each exam is $180. (Source) An exception is Predictive Modelling using the SAS Enterprise Miner, costing $250, This exam can be taken in the English language. One can join the SAS Academy for Data Science and also take a practice exam beforehand. Salary: You can get a job as a SAS Data Analyst that pays up to $90,000 per year! (Source) 5. IBM Data Science Professional CertificateWhenever someone studies the history of a computer, IBM (International Business Machines) is the first brand that comes up. IBM is still alive and kicking, now having forayed into and becoming a major player in the Big Data segment. The IBM Data Science Professional certificate is one of the beginner-level certificates if you want to sink your hands into the world of data analysis. It shows a candidate's skills in various topics pertaining to data sciences, including various open-source tools, Python databases, SWL, data visualisation, and data methodologies.  One needs to complete nine courses to earn the certificate. It takes around three months if one works twelve hours per week. It also involves the completion of various hands-on assignments and building a portfolio. A candidate earns the Professional certificate from Coursera and a badge from IBM that recognises a candidate's proficiency in the area. Prerequisites: It is the optimal course for freshers since it requires no requisite programming knowledge or proficiency in Analytics. Exam Fee: It costs $39 per month (Source) to access the course materials and the certificate. The course is handled by the Coursera organisation. Expected Salary: This certification can earn you the title of IBM Data Scientist and help you earn a salary of $134,846 per annum. (Source) 6. Microsoft Certified Azure Data Scientist AssociateIt's one of the most well-known certifications for newcomers to step into the field of Big Data and Data analytics. This credential is offered by the leader in the industry, Microsoft Azure. This credential validates a candidate's ability to work with Microsoft Azure developing environment and proficiency in analysing big data, preparing data for the modelling process, and then progressing to designing models. One advantage of this credential is that it has no expiry date and does not need renewal; it also authorises the candidate’s extensive knowledge in predictive Analytics. Prerequisites: knowledge and experience in data science and using Azure Machine Learning and Azure Databricks. Exam Fee: It costs $165 to (Source) register for the exam. One advantage is that there is no need to attend proxy institutions to prepare for this exam, as Microsoft offers free training materials as well as an instructor-led course that is paid. There is a comprehensive collection of resources available to a candidate. Expected Salary: The job title typically offered is Microsoft Data Scientist and it typically fetches a yearly pay of $130,993.(Source) Why be a Data Analytics professional? For those already working in the field of data, being a Data Analyst is one of the most viable options. The salary of a data analyst ranges from $65,000 to $85,000 depending on number of years of experience. This lucrative salary makes it worth the investment to get a certification and advance your skills to the next level so that you can work for multinational companies by interpreting and organising data and using this analysis to accelerate businesses. These certificates demonstrate that you have the required knowledge needed to operate data models of the volumes needed by big organizations. 1. Demand is more than supply With the advent of the Information Age, there has been a huge boom in companies that either entirely or partially deal with IT. For many companies IT forms the core of their business. Every business has to deal with data, and it is crucial to get accurate insights from this data and use it to further business interests and expand profits. The interpretation of data also aims to guide them in the future to make the best business decisions.  Complex business intelligence algorithms are in place these days. They need trained professionals to operate them; since this field is relatively new, there is a shortage of experts. Thus, there are vacancies for data analyst positions with lucrative pay if one is qualified enough.2. Good pay with benefitsA data analyst is an extremely lucrative profession, with an average base pay of $71,909 (Source), employee benefits, a good work-home balance, and other perks. It has been consistently rated as being among the hottest careers of the decade and allows professionals to have a long and satisfying career.   Companies Hiring Certified Data Analytics Professionals Oracle A California based brand, Oracle is a software company that is most famous for its data solutions. With over 130000 employees and a revenue of 39 billion, it is surely one of the bigger players in Data Analytics.  MicroStrategy   Unlike its name, this company is anything but micro, with more than 400 million worth of revenue. It provides a suite of analytical products along with business mobility solutions. It is a key player in the mobile space, working natively with Android and iOS.   SAS   One of the companies in the list which provides certifications and is also without a doubt one of the largest names in the field of Big Data, machine learning and Data Analytics, is SAS. The name SAS is derived from Statistical Analysis System. This company is trusted and has a solid reputation. It is also behind the SAS Institute for Data Science. Hence, SAS is the organisation you would want to go to if you're aiming for a long-term career in data science.    Conclusion To conclude, big data and data Analytics are a field of endless opportunities. By investing in the right credential, one can pave the way to a viable and lucrative career path. Beware though, there are lots of companies that provide certifications, but only recognised and reputed credentials will give you the opportunities you are seeking. Hiring companies look for these certifications as a mark of authenticity of your hands-on experience and the amount of work you can handle effectively. Therefore, the credential you choose for yourself plays a vital role in the career you can have in the field of Data analytics.  Happy learning!    
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Top Data Analytics Certifications

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Top Cloud Certifications

What is Cloud Computing?Cloud is the new buzzword these days, and the term Cloud Computing is everywhere. Everyone, everywhere, is moving their storage to the cloud, and reaping its immense benefits. With the advent of Cloud storage, there's also been a rise in job opportunities in the field. Cloud Computing jobs relate to professionals in Cloud Data Management systems, who have the expertise to deal with cloud servers and the problems that may arise both on the user level and the server levels.Why Cloud Computing?Due to the rise of Cloud services, like iCloud and Dropbox, to name a few, there's also a rise in the number of professionals needed for the job. Cloud Professionals and engineers are paid handsome amounts for their work - as much as $117892 (Source) per year or even more, depending on the level of experience or expertise. It is a growing field, so jobs are unlikely to diminish over the next few years, in fact quite the opposite. So, it is not too late to gain experience and get started in the world as a Cloud Computing professional.The Need for Certification and Prospective OpportunitiesAs we have mentioned before, the value and salary of a Cloud Professional depends on their experience. One of the ways to show expertise is through certifications. They provide you with appropriate knowledge to deal with the job and provide valuable proof of expertise in the market if they're obtained from reputed sources. A certification is sure to kickstart fruitful career in Cloud Computing. Keeping that in mind, we have compiled a set of the most reputed certifications in the field of Cloud.  Top Cloud Certificationsndustry-recognised certifications give you an edge over your non-certified peers, increasing your employability and helping you get ahead in your cloud career. Fresh, certifiable skills are guaranteed to open new career opportunities and increase your salary as well! Listed below are the top cloud certifications that you can consider: Google Certified Professional Data Architect  Amazon Web Services (AWS) Certified Solutions Architect- Associate  MCSE: Cloud Platform and Infrastructure (Microsoft)  Certified Cloud Security Professional (CCSP)  CompTIA Cloud +  VMware VCP7-CMA  CCNP Cloud (Cisco) 1. Google Certified Professional Cloud Architect Google Certified Professional Data Architect has the honour of topping the lists of the hugest paying IT certifications in the United States of America. Google is a borderline ubiquitous brand. Most people used a few Google products to reach this article in the first place, so here is the same reputed company offering a certification that validates proficiency on the Google Cloud Platform. It includes the fields of Cloud architecture design, development, and management on different scales and an incredibly high degree of security and standards.  Prerequisites: There are no official pre-requisites, but Google recommends more than three years of experience in the industry, including more than a year's worth of designing and management experience using the Google Cloud Platform.  Exam Cost & Duration: The exam costs $200 each, (Source), and a test Center can be found on the Google Cloud website. The exam duration is 2 hours long and can be taken in either English or Japanese.  Exam Guide: Google Cloud offers an exam guide with a dedicated list of topics and many case studies that can help with studying for the exam. They also offer a training path comprising of texts and videos, which are easy to engage with as well.  Salary: The average Pay for a Google Cloud Architect can be around $103K (Source)  2. Amazon Web Services (AWS) Certified Solutions Architect- Associate Amazon Web Services is one of the top cloud computing companies in recent times. They have achieved an impressive 43% growth over the last year. They are followed by Microsoft Azure and Google Cloud with a close lead. Amazon Web Services offer certifications at the foundation, associate, and professional levels. This prepares a candidate for developing and architecture roles and offers operational knowledge. The associate certification can be a steppingstone to a potential professional level certification which comes with veteran level jobs and authorizes years' worth of experience in the field of Cloud Computing architecture, and design.  Prerequisites: Amazon prefers hands-on experience in the fields of networking, database, computational, and storage AWS services with the ability to perfectly define requirements for an AWS application. They require critical thinking skills taking into view the AWS service format along with knowledge on building security services.  Exam Cost: It costs $150. A practice exam can be purchased for $20 USD. (Source).  The exam can be taken in English, Japanese, Korean, and Simplified Chinese languages. Exam Guide: Amazon offers a collection of hands-on training courses, videos, and much more to prepare for the exam. Self-evaluation methods include an exam guide and sample questions. 65 MCQ format questions.  Salary: The average Pay an AWS solution Architect can expect is around $121K (Source)  3. MCSE: Cloud Platform and Infrastructure (Microsoft)Microsoft is, again, one of the brands which have made a mark on the technology industry today. The MCSE: Cloud Platform and Infrastructure Course certifies a person's ability to effectively manage cloud data, shows their skill in managing virtual networks, storage management systems, and many more cloud technologies,  Prerequisites: One does not just take the MCSA (Microsoft Certified Solution Associate): Azure certification. They must also score a passing grade on an exam called the MSCE, which covers development, and Azure-based and related architecture solutions along with hybrid cloud operations and bits of big data analytics. An MCSE along with two or three pre-requisite exams need to be taken.   Exam Cost: The MCSE exam costs $165, (Source) while the pre-requisite exams cost $165 and $300 (MCSA and LFCS, respectively) Exam Guide/Courses: Microsoft Virtual Academy (MVA) offers free courses and reference matter relevant to Cloud professionals and cloud development. A program called Exam Reply is available that allows candidates to buy a slightly discounted exam, a practice attempt (which needs a slight upcharge), and a retake attempt as well.    Salary: The job title that can be earned after this certification is Microsoft Cloud Solution Architect, and this role can earn around $154133 per year. (Source)  4. Certified Cloud Security Professional (CCSP)Offered by the (ISC)^2 (International Information System Security Certification Consortium, the CCSP is a globally recognized certification. It validates a candidate's ability to work within a cloud architecture along with good abilities in the field of design, secure applications, along data and infrastructure. These are carried out under the protocols offered by (ISC)^2, which are a hallmark of security. It's ideal for those who want an enterprise architect role, and other roles include systems engineers, security administrator or a consultant in the field of security.  Prerequisites: The (ISC)^2 recommends around five years of experience in the field of IT, including three in Information security and one in any of the domains prescribed by CSSP Common Body of Knowledge.  Exam Cost: The exam is provided by Pearson VUE. The standard registration for the exam costs $600 (Source)  Exam Guide/Courses: The CCSP examination involves preparation in 6 different domains, as highlighted in the CCSP exam outline.  Salary: The job title earned is Cloud Security Professional, a job that can pay up to $138k per annum. (Source)  5. CompTIA Cloud+ An acronym for Computing Technology Industry Association, CompTIA is a non-profit. It serves the IT industry and is one of the global leaders in certifications like the ones you're looking for on the list. These are vendor-neutral, meaning you can apply to a broad range of jobs, and it means you're not restrained to any particular company. They cover certifications from novice to professional levels.  CompTIA Cloud+ acts as a foundation-level certification. Like its selling point, Cloud+ offers a piece of foundational knowledge in a broad domain in the Cloud market. It authorizes skills in the maintenance and optimization of cloud software. It shows that a candidate can demonstrate the ability to migrate data to cloud platforms, manage cloud resources and make appropriate modifications, perform automation tasks to improve performance, all the while focusing on security.  Prerequisites: It needs 2-3 years' worth of experience in system administration.  Exam Cost & Format: The exam includes 90 questions. Available in English and Japanese Costs $338 (Source), The certification expires in 3 years after launch Salary: As a cloud specialist an average pay that can be expected in the US market is around $80317 (Source). 6. VMware VCP7-CMA VMware is a company that is well known within the IT-sphere for its strong grasp of virtualization technologies. The VCP7- Cloud Management and Automation is the latest in a series of certifications the company has rolled out. The vRealise and the vSphere-based program are instrumental in certifying new as well as veteran IT professionals in the field of virtualization in the Cloud.  Prerequisites:  A prerequisite is to have a minimum of 6-month experience with the vSphere 6 and realized software.  One also needs to complete one of the training courses offered by VMware, which keeps updating on the current course list portion of the website.  Candidates can choose one out of 3 exams: vSphere 6 Foundations, vSphere 6.5 Foundations, or VMware Certified Professional Management and Automation exam.  Exam Cost: vSphere 6 and 6.5 cost $125, whereas the third exam costs $250 (Source). A VMWare candidate ID is needed to register.  Exam Guide: Exam Self-study material is available on the certification page.  Salary: As a VMWare Staff Engineer, the salary expected could be up to $188446 every year. (Source)  7. CCNP Cloud (Cisco)CCNP stands for Cisco Certified Network Professional. This is one of the more reputed certifications that allows a professional to validate their skills in the fields of data management, cloud architecture, and design and authorize their path as a cloud professional. Along with the Cloud, the CCNP is also available as a Collaboration, Service Provider, Data Centre, and many other fields in the collection of solutions. Be warned, though. Cisco focuses on the practical requirements as well, so their certification process is equally rigorous, with design, practical, architecture-based assessments to keep one on their toes. But in the end, this multidisciplinary approach proves itself. An understanding of Application Centric Infrastructure (ACI) is also vital. They provide a lot of resources to prepare as well, with assignments, discussion forums, self-assessments, and much more!  Training in the fields of CLDING, CLDDES, CLDAUT, CLACI, CLDINF is highly recommended. These cover information on Cisco cloud infrastructure, automation, infrastructure, and troubleshooting.  Prerequisites: There are four exams that need to be taken in each of the above fields. They are administered by Pearson VUE.  Exam Cost: Each exam costs $300, $1200 total. (Source)  Exam Guide: For the study material, Cisco has curated many resources like Learning Network games, self-assessment modules, seminars, videos, and much more. Textbooks and other materials are also available on the Cisco Marketplace Bookstore.  Salary: The typical job that can be obtained is Cisco Systems Cloud Engineer that pays around $158010 per annum.(Source)  Certification LevelsThese cloud certifications can be segregated into Professional and Associate levels, where various criteria are required to be fulfilled to be eligible to apply for the respective certification. As per the market trends and the demand, here is a detailed description of some of the most coveted certifications: Amazon Web Services - AWS 1. AWS Certified Solutions Architect - Professional This certification is for professionals who have experienced hands-on solutions architect roles. A candidate must have 2 or more years of experience in operating and managing the AWS operations. The exam costs 300 USD and is 180 minutes long. This course validates the following abilities:  Implementation of cost control strategies  Designing fault proof applications on AWS  Choosing appropriate AWS services for design and application   Migrating the complex applications on AWS  Exam criteria 2 or more years of experience in handling cloud architecture on AWS  One should have diverse knowledge of AWS CLI, AWS APIs, AWS CloudFormation templates, the AWS Billing Console, and the AWS Management Console  Detailed knowledge of the scripting language  Must have worked on Windows and Linux  Must be able to explain the five pillars of the AWS architecture Framework  Practical knowledge of the architectural design across multiple projects of the company.  2. AWS Certified Solutions Architect - Associate  This course is for professionals who have one year of experience in handling and designing fault free and scalable distributed systems on AWS.  This certificate validates the following abilities:  In depth knowledge of deploying the secure and powerful applications on AWS  Knowledge and application of customized architectural principles  Exam criteria The course requires a complete understanding of the AWS global infrastructure, network technologies, security features and tools related to AWS  Knowledge of how to build secure and reliable AWS applications  Experience of deployment and management of management services.  The exam duration is 130-minutes and the fee is $150. The above were some of the main certified courses of AWS. The other two Associate level courses are AWS SysOps Administrator Associate and the AWS Developer Associate. 3. The AWS Certified DevOps Engineer – ProfessionalThis exam is for professionals who have experience as a DevOps engineer and have experience in provisioning, operating, and managing AWS environments.  This course validates the following abilities: Management and implementation of delivery systems and methodology on AWS  Deploying and managing the logging, metrics, and monitoring system on AWS  Implementation and management of highly scalable, and self-healing systems on AWS.  Automation of security controls, government processes and compliance validation  Exam criteria  Knowledge and experience in administering operating systems and building highly automated infrastructure.  Knowledge of developing code in at least one high level programming language.  The cost of the exam is 300 USD and the duration is 180 minutes. There will be 75 questions.  Microsoft Web Service – Azure:  1. Azure Developer Associate AZ-204This course will provide you with the skill set to design, build, test and maintain cloud solutions from the start to the end.  You will master the basics of developing an app and all the other services Azure provides. This certification course will help you learn the actual syntax and programming languages that are used to integrate the application on Azure.  Exam criteria You are required to take an Exam AZ-204: Developing Solutions for Microsoft Azure ($165 USD) and must have at least 1-2 years’ of experience with development and azure development.  Having a good command in any of these languages like C#, PHP, Java, Python, or JavaScript would be a plus.  Getting certified with this course will set you ahead of your peers in the development sector.  2. Azure Data Scientist Associate DP-100Turning data and facts related to a business into useful and actionable insights is an art, and getting the Azure data scientist certification will prove that you have the required expertise in data and machine learning.  This course is for professionals who are currently working as a data scientist or are planning to become one soon. Exam: DP-100: Designing and Implementing a Data Science Solution on Azure ($165 USD)  Exam criteria You should have knowledge and experience in data science and in using Azure Machine Learning and Azure Databricks. This certification course can future-proof your career, as there is spectacular growth in internet use and the demand for job roles in this sector will continue to increase year on year.   Wondering where to start? Here are some pointers:Are you a Newbie?If you are a lost soul in the world of technology but want to learn, then the perfect way to start is the Azure Fundamentals Course. Any beginner can grasp the fundamentals and get started.Are you in the middle of the road?If you are someone who has average experience and has worked with hands-on AWS, GCP, or Azure then too we would recommend you start with the Fundamental course. Refresh your knowledge and make your basics stronger before you move on to the Administrator Associate certification, which can be very intimidating otherwise. Are you an Expert?  If you have had enough experience with cloud computing or have got serious geek vibes in you, then you can take up any speciality or professional certifications to add the missing edge to your expertise.  If you still need more clarity, you can explore our cloud certification category page for more details. Need more handholding? Contact our experts by using the Contact Learning Advisor button and fill up a small form. Let’s connect! Why be a Cloud Computing Professional? 1. A Growing Field As more and more of our lives are uploaded on the Cloud, the demand for professionals with the capabilities to handle cloud architecture is increasing by the day. Professionals with the right expertise are paid handsome salaries, and the investments made in certification repay themselves many times over. The demands for Cloud professionals outstrip the supply by a huge margin, making this an easy job for entry-level applicants.   2. A Good PayThe salary for a Cloud Engineer ranges from $117,892 to $229,000 (Source). This is a rewarding field, indeed! You can get onto the entry point of the ladder and work your way up, which is an easy journey if you earn a certification. It is one of the highest paying jobs that can be found in the IT sector.   Companies Hiring Certified Cloud Computing Professionals Some of the companies whose certifications we addressed above are also among the key employers in the Cloud Computing market. The key employers for these jobs are listed below.    Amazon They are the undoubted leaders in the fields of Cloud Computing and management. They are branching out in the fields of AI, the Internet of things, machine learning, and database management as well, and you can explore exciting new opportunities in any of these fields. As documented above, AWS has faced over 43% growth year after year for a sustained period. They are undoubtedly one of the largest hirers in the field as they need competent workforce for their expanding ventures.  Microsoft After the enormous success of the Office 365 platform, Cloud Computing was the next step forward for Microsoft, with the Azure platform. They are neck to neck with Amazon for the number 1 spot in the field of Cloud architecture and database management.   IBM The waning brand of IBM has now made a sudden resurgence to capitalize on the demand in the fields of AI, the Information Age, and the new Cloud phenomenon. They have recently acquired Red Hat and have entered the field of hybrid cloud development. They will surely be looking for professionals in the field to boost their chances. Dell Technologies (VMware) VMware, mentioned on the above lists, has partnered with Dell Technologies to form a robust cloud platform. A veteran player in the industry already, VMware has constantly evolved to adapt to advancements in the industry. They have partnerships with all the huge players like AWS, Microsoft Azure and Google Cloud as well.  ConclusionIt is quite evident that Cloud computing is one of the most exciting and lucrative fields one can be in, considering the investment to return ratio. These certifications offer incredibly excellent value for money and will lead to placements in leading companies, which is not easy via other paths.  There is a lot to learn in the field of Cloud Computing, and it is a highly adaptive job as well; that is why one needs to keep an eye on the newest software and architecture in the market. These certifications make sure that you can validate your experience and increase your employability. While there are many certifications available, only the ones from reputed institutions help to get a job. They show that you have the knowledge and expertise to make your mark in the industry.  It is never too late to start your learning journey, so grab that certification exam guide and start learning. Happy computing!  
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Top Cloud Certifications

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How to Install Node.JS on Ubuntu

Node.js is a general-purpose programming JavaScript platform that allows users to quickly build network applications. Node.js makes development more consistent and integrated by using JavaScript on both the front and backend, and allows you to write JavaScript on the server-side.JavaScript, as you know, is a browser-based language. The browser's engine will take and compile JavaScript code into commands. The creator of Node.js took the engine of Chrome and set it to work on a server. The language can be interpreted in an environment.In this article, we will read about Node.js installation using three methods:Installing the Stable VersionInstall Using a PPAInstall Using NVMPrerequisitesHardware Requirements:RAM: 4 GBStorage: 256 GB of Hard Disk SpaceSoftware Requirements:Web Browser: Any browser such as Google Chrome, Mozilla Firefox, Microsoft Edge.Operating System: An Ubuntu 18.04 server installed with a non-root sudo user and firewall.Installation Procedure1. Installing the Stable Version for UbuntuIn its default repositories, Ubuntu 18.04 contains a version of Node.js that provides a consistent experience on a number of systems. The version of the repositories is 8.10.0 when it is written. This is not the latest version but should be stable and sufficient for quick language experiments.Step 1: You can use the apt package manager to obtain this version. Refresh your index for your local package with:$ sudo apt updateStep 2: Now, install Node.js from the repository:$ sudo apt install nodejsStep 3: This is all you need to do to get set up with Node.js if the package in the repositories fits your needs. In most cases, the package manager Node.js will also install npm. This can be done by:$ sudo apt install npmThis allows the installation of Node.js modules and packages.The executable from Ubuntu repositories is known as nodejs instead of node because of conflict with another package. Take this into account when you run the software.Step 4: To check which Node.js version you installed, try this:$ nodejs -vYou can decide if you want to work with different versions, package archives, and version managers, after you have established which version of Node.js you have installed from Ubuntu repositories. The following elements will be discussed with more flexible and robust installation methods.2. Install Using a PPAStep 1: First install curl on Ubuntu:$ sudo apt install curlStep 2: To access its contents, install the PPA first. Use curl to retrieve the installation script in your favourite version from your home directory so that your favourite version (if different) replaces 10.x:$ cd ~ $ curl -sL https://deb.nodesource.com/setup_10.x -o nodesource_setup.shStep 3: nano (or your preferred text editor) can be used to inspect the contents of this script:$ nano nodesource_setup.shStep 4: Now, run the script under sudo:$ sudo bash nodesource_setup.shStep 5: You add the PPA to the settings and automatically update your local package cache. You can install the Node.js package in the same way that you did above after running the Nodesource setup script:$ sudo apt install nodejsStep 6: To check the version of Node.js, use:$ nodejs -vThe nodejs package includes the nodejs binary and npm so that you don't have to install npm individually.Step 7: Npm uses a setup file to keep track of updates in your home directory. The first time you run npm, it will be created. To check that npm has been installed and to create a settings file, execute this command:$ npm -vStep 8: You need to install the build-essential package to allow certain npm packages (for instance those that require compilation code from source) to work.$ sudo apt install build-essentialYou now have the tools to work with npm packages, which require source code compilation.3. Install Using NVMAn alternative is to use a tool called nvm which stands for "Node.js Version Manager" when installing Node.js with apt.  You can access the latest versions of Node.js and manage previous releases by controlling your environment with nvm. However, the Node.js versions that you handle are different from the apt versions.Step 1: You can use curl to download the nvm installer from the GitHub project page. Note that the version number may differ from the above:$ curl -sL https://raw.githubusercontent.com/creationix/nvm/v0.35.3/install.sh -o install_nvm.shStep 2: Use nano to inspect the installation script:$ nano install_nvm.shStep 3: Now, run the script with bash:$ bash install_nvm.shIt installs the software in your home ~/.nvm subdirectory. The lines needed to use the file will also be added into your ~/.profile.Step 4: You will either need to log out and log in back in to get access to NVM functionality or to source the ~/.profile file so you know the changes in the current session:$ source ~/.profileStep 5: You can install isolated versions of Node.js with nvm installed. For information on the available Node.js versions, type:$ nvm ls-remoteStep 6: As you can see, at the time of writing this blog, the current version of LTS was v12.18.3. You can install this with:$ nvm install 12.18.3Step 7: Normally, nvm will use the most recently installed version. You can instruct nvm to use the newly downloaded version by typing:$ nvm use 12.18.3Step 8: The executable is called node when you install Node.js with nvm. The current version of the shell can be seen by:$ node -vStep 9: You can see what is installed in your system if you have multiple Node.js versions:$ nvm lsStep 10: If you wish to default to any of the versions, use:$ nvm alias default 12.18.3Step 11: When a new session spawns, this version is automatically selected. You can also mention it through the alias as follows:$ nvm use defaultEach Node.js version will track and have npm available to manage its own packages.Step 12: In the directory of Node.js project's /node modules you can also have npm install packages. Install the express module using the following syntax:$ npm install expressStep 13: If you want the module to be installed globally by other projects with the same node.js version, you can add the flag -g:$ npm install -g expressThe package will install in:~/.nvm/versions/node/12.18.3/lib/node_modules/expressStep 14: If you install the module globally, you can execute commands from the command line, but the package must be linked to your local area in order to access this from a program:$ npm link expressStep 15: You can learn more about the nvm by using:$ nvm helpCreate Demo Web ServerStep 1: If your node is to be tested. Set up js. Let's build a "Hello World!" web server. You can use the following command to create a file app.js and open it in a text editor.Step 2: Set up a JavaScript (js) file to test the node. Let's build a "Hello World!" web server. You can use the following command to create a file app.js and open it in a text editor.$ gedit app.jsStep 3: Now, add the following content in the text editor and save it:var express = require('express'); var app = express();app.get('/', function (req, res) {   res.send('Hello World!'); });app.listen(3000, function () {   console.log('Example app listening on port 3000!'); });Step 4: Start the node application using the following command:$ node app.jsYou will see the output as an example app running in port 3000!Step 5: On port 3000 the webserver was launched. Here is a web browser access http://127.0.0.1:3000/ URL. Now you need to set up your app's front-end server.You're done, that's it. You have created your first Node application successfully. Don't stop here, continue to explore the beautiful Node.js world, as it has more to offer.How to Uninstall Node.js?Depending on the version you want to target, you can uninstall Node.js with apt or nvm. You have to work with the apt utility at system level in order to remove the distro-stable version.1. Using apt:$ sudo apt remove nodejsThis command will remove the package and keep the setup files. This can be useful for you if the package is to be reinstalled later.2. If the configuration files for future use are not to be saved, then run the following:$ sudo apt purge nodejsThis deactivates the package and deletes its associated configuration files.3. You can then delete any unused packages, which have been installed automatically with the deleted package:$ sudo apt autoremoveUninstall using NVM1. To uninstall a Node.js version that you have enabled with nvm, first determine whether the version you want to remove is the current active version:$ nvm current2. If the current active version is the version you want to remove, you must first deactivate NVM in order to allow your changes:$ nvm deactivateYou can uninstall the current version by using the command above to uninstall all the associated Node.js files with the exception of cached files which can be reinstalled.Learn more about the core concepts of Node with REPL, Cluster, Routing, Express with Node.js Certification Course.Conclusion:On your Ubuntu 18.04 server, there are a few ways to run Node.js. You can decide which of the above-mentioned methods are best suited to your needs. The easiest way to use the packaged version in Ubuntu's repository is by adding flexibility using nvm.
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How to Install Node.JS on Ubuntu

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How to Install React Native on Windows

React Native is a renowned JavaScript mobile application framework that allows building mobile applications on Android and iOS platforms. It offers superb mobile development capabilities and concentrates on creating applications for multiple stages using a similar codebase.  Originally developed by Facebook for its internal app development, React Native was open sourced in March 2015 for iOS Mobile apps, and by September of the same year a version for Android dev was also released. Today, Native React has been vastly improved and powers popular worldwide mobile applications like Instagram, Facebook, Skype, and more.  Are you ready to get started with React Native? Let's understand how to download, install and set up React Native in Windows 10. 1. PrerequisitesBefore we get started, here are a few system requirements to download, install, and set up React-Native on your Windows 10.Hardware requirementsTo download and successfully install React-Native in your computer, you need to consider the minimum hardware specifications required to support the app and run it smoothly. RAM 8 GB CPU: Intel ® Core ™ i7‐4870 HQ CPU @ 2.50 GHz 256 GB ROM Software requirementsTo efficiently install and set up React-Native on your Windows device, you will need to install the following:  Android Studio  Android SDK  Install JDK Node Js  NPM 3.5.2 React native cli 2. Installation procedureTo successfully install and set up React-Native to your device, you need to follow the steps discussed below: Step-1: Install ChocolateyThe first process that you need to do is to install Chocolatey, a well‐known package manager for Windows. Installation of Chocolatey requires administrator access to the computer’s command prompt to run.  Go to and choose the option – get started. In the Chocolatey install section, choose Individual as shown:Now go to Windows CMD Shell, and enter the following command in the cmd.exe shell.The installation will look like as shown below:    To check whether you have installed it correctly, open the command prompt and type; choco -version If you managed a correct installation, this command returns the Chocolatey version you have installed; like shown in the screen below:Step-2: Install Node Js Using Chocolatey we will now install Node.js, and JDK8 as follows. i. Installing Node Js Installing Node.js is crucial as it is a JavaScript runtime environment and React Native uses it build the JavaScript code. To install Node.js, you need to open the command prompt as the administrator and put in the Chocolatey command prompt below: Choco install -y nodejs.install Installation may take some time. Once done, you will see a message stating that Chocolatey is installed as shown below:  To confirm that installation has been successful, we will execute the below command at the command prompt, as administrator: node --version If the installation was successful, the version number is displayed. After installing Node.js, the Node Package Manager NPM automatically installs. Now check the installation of NPM in your system by entering the following command.   npm --versionThe displayed message below verifies that the installation of NPM is successful.Step:4 Installing JDK8 (Java Development Kit)JDK8 is crucial in the improvement of android applications by React-Native. To install the JDK8, go to the Windows PowerShell and use the following command: choco install -y nodejs.install openjdk8 To know whether it installed successfully, open the command prompt again and enter the command: java -version The message below is displayed if the JDK8 is successfully installed hence showing the Java version as: openjdk version “1.8.0_222” The installed JDK8 also has an installed Java compiler. To confirm whether the Java compiler has been installed, open the command prompt and enter the below command: javac -version Step-5: Install Android StudioTo improve mobile applications with React Native, you need to install Android Studio. To download the installation file, go to. By default, android studio automatically installs the latest Android SDK. However, building a React Native app with native code demands Android 11.0 (R) SDK in particular. The installation display message looks like below: After downloading the file, perform the Android Studio installation process. To continue, click on the Next button to see the Choose Components screen.  Tick the box containing Android Virtual Device and click on the Next button.  You then need to choose the location in your computer where you would like the Android Studio to get installed.  You can even leave it to install at the default location to save time, and  then click the Next button to go to the next screen:  You will come to the Choose Start Menu Folder. Click the Install button to install the program.When the bar reaches the end, click on the Next button to complete the process.On the next screen, check Start Android Studio and click on the Finish button.  Customize Android Studio: Click the Next button to go to the Install Type screen: Choose the Custom type of setup and then click the Next button.On this screen, you can select the theme of your choice and then click on the Next button to go to the SDK Component Setup window.On the SDK Component Setup display, check on the Performance Intel HAXM option plus Android Virtual Device option and then click on the Next button.On the Emulator Settings window, do not make changes to anything. Leave it the way it is and click on the Next button.   Verify settings.  The dialogue box below completes the whole process by clicking on the Install button.Customize Android SDK When you select Configure, the SDK Manager as shown on the screen above is displayed. This allows you to choose the Android SDK settings. Click on the Show Package Details located at the bottom right of the screen. From the list, tick the following: Android SDK Platform 28 Intel x86 Atom System Image Google APIs Intel x86 Atom System Image Google APIs Intel x86 Atom_64 System Image Click the OK button to install them, and you are done setting up the Android SDK. React Native needs environment variables to be customized to create applications using the native codes. Next, we will customize the Android Studio Environment variable. 3. Setting the path to Environmental VariableRight‐click on This PC and click Properties, a screen displays as below. Click on the advanced system settings.Once you are on the System Properties window, select the Advanced tab, and then the Environment Variables button at the bottom. Then press Enter.  After selecting the environment variable, go to the Variable name, type ANDROID_HOME and your variable value Android Studio SDK path. After that, customize the Android Studio platform‐tools path by selecting the Path variable on User variables for your name list to move to the edit dialog.  Input platform tools folder path in the SDK path, like C:\Users\[user name]\AppData\Local\Android\Sdk\to the end of the list and press Enter key. Open the command prompt and input the command below: adb When the environmental variable customization is successful, you get the below message: Android Debug Bridge version 1.0.41  Version 29.0.1-5644136  Installed as /Users/Username/Library/Android/sdk/platform-tools/adb Install React Native CLI To install React-Native CLI, open the command prompt as an administrator and enter the following command: npm install -g react-native-cli 4. Creating a New ApplicationLet us create a new React Native project using react native CLI. reactapp is the first project we are creating on React Native. react-native init reactapp Running the Application Once you have created your first React application, it's time to run the application. Open the application in any IDE of your choice. Here we are using Visual Studio Code as shown: If you want to run your project on an Android device, open Android Studio and create a virtual device. When your virtual device opens, use the following command in your Windows Command Prompt:  Once done, you will see the application opened on your Android device as shown:  5. Uninstalling React-NativeReact native application is a global package and not the same as other frameworks. Let us understand how to uninstall React Native from your system using Control Panel. Here is a step-by-step guide on how to uninstall React Native: To uninstall React Native from your system, use the command: npm uninstall -g react-native-cliConclusion In this article, we have seen the systematic procedure of downloading and setting up React-Native on Windows 10 devices. Besides, we have also discussed about React-Native, its origin, the installation process, and the follow up setup procedures. In a nutshell, you have learned how to install and set up the following software packages:   Installing Chocolatey Installing Node and JDK8 Installing Android Studio Customizing the Android SDK Installing React Native CLI Creating a new App Running the application You have also learnt how to create the React Native app and use it on an Android device. Lastly, we saw the uninstallation process too. Hurray! You have come to the end of the tutorial. It’s time to get started with React Native and build your projects. Keep Coding!  
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How to Install React Native on Windows

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What Is Statistical Analysis and Its Business Applications?

Statistics is a science concerned with collection, analysis, interpretation, and presentation of data. In Statistics, we generally want to study a population. You may consider a population as a collection of things, persons, or objects under experiment or study. It is usually not possible to gain access to all of the information from the entire population due to logistical reasons. So, when we want to study a population, we generally select a sample. In sampling, we select a portion (or subset) of the larger population and then study the portion (or the sample) to learn about the population. Data is the result of sampling from a population.Major ClassificationThere are two basic branches of Statistics – Descriptive and Inferential statistics. Let us understand the two branches in brief. Descriptive statistics Descriptive statistics involves organizing and summarizing the data for better and easier understanding. Unlike Inferential statistics, Descriptive statistics seeks to describe the data, however, it does not attempt to draw inferences from the sample to the whole population. We simply describe the data in a sample. It is not developed on the basis of probability unlike Inferential statistics. Descriptive statistics is further broken into two categories – Measure of Central Tendency and Measures of Variability. Inferential statisticsInferential statistics is the method of estimating the population parameter based on the sample information. It applies dimensions from sample groups in an experiment to contrast the conduct group and make overviews on the large population sample. Please note that the inferential statistics are effective and valuable only when examining each member of the group is difficult. Let us understand Descriptive and Inferential statistics with the help of an example. Task – Suppose, you need to calculate the score of the players who scored a century in a cricket tournament.  Solution: Using Descriptive statistics you can get the desired results.   Task – Now, you need the overall score of the players who scored a century in the cricket tournament.  Solution: Applying the knowledge of Inferential statistics will help you in getting your desired results.  Top Five Considerations for Statistical Data AnalysisData can be messy. Even a small blunder may cost you a fortune. Therefore, special care when working with statistical data is of utmost importance. Here are a few key takeaways you must consider to minimize errors and improve accuracy. Define the purpose and determine the location where the publication will take place.  Understand the assets to undertake the investigation. Understand the individual capability of appropriately managing and understanding the analysis.  Determine whether there is a need to repeat the process.  Know the expectation of the individuals evaluating reviewing, committee, and supervision. Statistics and ParametersDetermining the sample size requires understanding statistics and parameters. The two being very closely related are often confused and sometimes hard to distinguish.  StatisticsA statistic is merely a portion of a target sample. It refers to the measure of the values calculated from the population.  A parameter is a fixed and unknown numerical value used for describing the entire population. The most commonly used parameters are: Mean Median Mode Mean :  The mean is the average or the most common value in a data sample or a population. It is also referred to as the expected value. Formula: Sum of the total number of observations/the number of observations. Experimental data set: 2, 4, 6, 8, 10, 12, 14, 16, 18, 20  Calculating mean:   (2 + 4 + 6 + 8 + 10 + 12 + 14 + 16 + 18 + 20)/10  = 110/10   = 11 Median:  In statistics, the median is the value separating the higher half from the lower half of a data sample, a population, or a probability distribution. It’s the mid-value obtained by arranging the data in increasing order or descending order. Formula:  Let n be the data set (increasing order) When data set is odd: Median = n+1/2th term Case-I: (n is odd)  Experimental data set = 1, 2, 3, 4, 5  Median (n = 5) = [(5 +1)/2]th term  = 6/2 term   = 3rd term   Therefore, the median is 3 When data set is even: Median = [n/2th + (n/2 + 1)th] /2 Case-II: (n is even)  Experimental data set = 1, 2, 3, 4, 5, 6   Median (n = 6) = [n/2th + (n/2 + 1)th]/2  = ( 6/2th + (6/2 +1)th]/2  = (3rd + 4th)/2  = (3 + 4)/2      = 7/2      = 3.5  Therefore, the median is 3.5 Mode: The mode is the value that appears most often in a set of data or a population. Experimental data set= 1, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4,4,5, 6  Mode = 3 (Since 3 is the most repeated element in the sequence.) Terms Used to Describe DataWhen working with data, you will need to search, inspect, and characterize them. To understand the data in a tech-savvy and straightforward way, we use a few statistical terms to denote them individually or in groups.  The most frequently used terms used to describe data include data point, quantitative variables, indicator, statistic, time-series data, variable, data aggregation, time series, dataset, and database. Let us define each one of them in brief: Data points: These are the numerical files formed and organized for interpretations. Quantitative variables: These variables present the information in digit form.  Indicator: An indicator explains the action of a community's social-economic surroundings.  Time-series data: The time-series defines the sequential data.  Data aggregation: A group of data points and data set. Database: A group of arranged information for examination and recovery.  Time-series: A set of measures of a variable documented over a specified time. Step-by-Step Statistical Analysis ProcessThe statistical analysis process involves five steps followed one after another. Step 1: Design the study and find the population of the study. Step 2: Collect data as samples. Step 3: Describe the data in the sample. Step 4: Make inferences with the help of samples and calculations Step 5: Take action Data distributionData distribution is an entry that displays entire imaginable readings of data. It shows how frequently a value occurs. Distributed data is always in ascending order, charts, and graphs enabling visibility of measurements and frequencies. The distribution function displaying the density of values of reading is known as the probability density function. Percentiles in data distributionA percentile is the reading in a distribution with a specified percentage of clarifications under it.  Let us understand percentiles with the help of an example.  Suppose you have scored 90th percentile on a math test. A basic interpretation is that merely 4-5% of the scores were higher than your scores. Right? The median is 50th percentile because the assumed 50% of the values are higher than the median. Dispersion Dispersion explains the magnitude of distribution readings anticipated for a specific variable and multiple unique statistics like range, variance, and standard deviation. For instance, high values of a data set are widely scattered while small values of data are firmly clustered. Histogram The histogram is a pictorial display that arranges a group of data facts into user detailed ranges. A histogram summarizes a data series into a simple interpreted graphic by obtaining many data facts and combining them into reasonable ranges. It contains a variety of results into columns on the x-axis. The y axis displays percentages of data for each column and is applied to picture data distributions. Bell Curve distribution Bell curve distribution is a pictorial representation of a probability distribution whose fundamental standard deviation obtained from the mean makes the bell, shaped curving. The peak point on the curve symbolizes the maximum likely occasion in a pattern of data. The other possible outcomes are symmetrically dispersed around the mean, making a descending sloping curve on both sides of the peak. The curve breadth is therefore known as the standard deviation. Hypothesis testingHypothesis testing is a process where experts experiment with a theory of a population parameter. It aims to evaluate the credibility of a hypothesis using sample data. The five steps involved in hypothesis testing are:  Identify the no outcome hypothesis.  (A worthless or a no-output hypothesis has no outcome, connection, or dissimilarities amongst many factors.) Identify the alternative hypothesis.  Establish the importance level of the hypothesis.  Estimate the experiment statistic and equivalent P-value. P-value explains the possibility of getting a sample statistic.  Sketch a conclusion to interpret into a report about the alternate hypothesis. Types of variablesA variable is any digit, amount, or feature that is countable or measurable. Simply put, it is a variable characteristic that varies. The six types of variables include the following: Dependent variableA dependent variable has values that vary according to the value of another variable known as the independent variable.  Independent variableAn independent variable on the other side is controllable by experts. Its reports are recorded and equated.  Intervening variableAn intervening variable explicates fundamental relations between variables. Moderator variableA moderator variable upsets the power of the connection between dependent and independent variables.  Control variableA control variable is anything restricted to a research study. The values are constant throughout the experiment. Extraneous variableExtraneous variable refers to the entire variables that are dependent but can upset experimental outcomes. Chi-square testChi-square test records the contrast of a model to actual experimental data. Data is unsystematic, underdone, equally limited, obtained from independent variables, and a sufficient sample. It relates the size of any inconsistencies among the expected outcomes and the actual outcomes, provided with the sample size and the number of variables in the connection. Types of FrequenciesFrequency refers to the number of repetitions of reading in an experiment in a given time. Three types of frequency distribution include the following: Grouped, ungrouped Cumulative, relative Relative cumulative frequency distribution. Features of FrequenciesThe calculation of central tendency and position (median, mean, and mode). The measure of dispersion (range, variance, and standard deviation). Degree of symmetry (skewness). Peakedness (kurtosis). Correlation MatrixThe correlation matrix is a table that shows the correlation coefficients of unique variables. It is a powerful tool that summarises datasets points and picture sequences in the provided data. A correlation matrix includes rows and columns that display variables. Additionally, the correlation matrix exploits in aggregation with other varieties of statistical analysis. Inferential StatisticsInferential statistics use random data samples for demonstration and to create inferences. They are measured when analysis of each individual of a whole group is not likely to happen. Applications of Inferential StatisticsInferential statistics in educational research is not likely to sample the entire population that has summaries. For instance, the aim of an investigation study may be to obtain whether a new method of learning mathematics develops mathematical accomplishment for all students in a class. Marketing organizations: Marketing organizations use inferential statistics to dispute a survey and request inquiries. It is because carrying out surveys for all the individuals about merchandise is not likely. Finance departments: Financial departments apply inferential statistics for expected financial plan and resources expenses, especially when there are several indefinite aspects. However, economists cannot estimate all that use possibility. Economic planning: In economic planning, there are potent methods like index figures, time series investigation, and estimation. Inferential statistics measures national income and its components. It gathers info about revenue, investment, saving, and spending to establish links among them. Key TakeawaysStatistical analysis is the gathering and explanation of data to expose sequences and tendencies.   Two divisions of statistical analysis are statistical and non-statistical analyses.  Descriptive and Inferential statistics are the two main categories of statistical analysis. Descriptive statistics describe data, whereas Inferential statistics equate dissimilarities between the sample groups.  Statistics aims to teach individuals how to use restricted samples to generate intellectual and precise results for a large group.   Mean, median, and mode are the statistical analysis parameters used to measure central tendency.   Conclusion Statistical analysis is the procedure of gathering and examining data to recognize sequences and trends. It uses random samples of data obtained from a population to demonstrate and create inferences on a group. Inferential statistics applies economic planning with potent methods like index figures, time series investigation, and estimation.  Statistical analysis finds its applications in all the major sectors – marketing, finance, economic, operations, and data mining. Statistical analysis aids marketing organizations in disputing a survey and requesting inquiries concerning their merchandise. 
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What Is Statistical Analysis and Its Business Appl...

Statistics is a science concerned with collection,... Read More

Measures of Dispersion: All You Need to Know

What is Dispersion in StatisticsDispersion in statistics is a way of describing how spread out a set of data is. Dispersion is the state of data getting dispersed, stretched, or spread out in different categories. It involves finding the size of distribution values that are expected from the set of data for the specific variable. The statistical meaning of dispersion is “numeric data that is likely to vary at any instance of average value assumption”.Dispersion of data in Statistics helps one to easily understand the dataset by classifying them into their own specific dispersion criteria like variance, standard deviation, and ranging.Dispersion is a set of measures that helps one to determine the quality of data in an objectively quantifiable manner.The measure of dispersion contains almost the same unit as the quantity being measured. There are many Measures of Dispersion found which help us to get more insights into the data: Range Variance Standard Deviation Skewness IQR  Image SourceTypes of Measure of DispersionThe Measure of Dispersion is divided into two main categories and offer ways of measuring the diverse nature of data. It is mainly used in biological statistics. We can easily classify them by checking whether they contain units or not. So as per the above, we can divide the data into two categories which are: Absolute Measure of Dispersion Relative Measure of DispersionAbsolute Measure of DispersionAbsolute Measure of Dispersion is one with units; it has the same unit as the initial dataset. Absolute Measure of Dispersion is expressed in terms of the average of the dispersion quantities like Standard or Mean deviation. The Absolute Measure of Dispersion can be expressed  in units such as Rupees, Centimetre, Marks, kilograms, and other quantities that are measured depending on the situation. Types of Absolute Measure of Dispersion: Range: Range is the measure of the difference between the largest and smallest value of the data variability. The range is the simplest form of Measure of Dispersion. Example: 1,2,3,4,5,6,7 Range = Highest value – Lowest value  = ( 7 – 1 ) = 6 Mean (μ): Mean is calculated as the average of the numbers. To calculate the Mean, add all the outcomes and then divide it with the total number of terms. Example: 1,2,3,4,5,6,7,8 Mean = (sum of all the terms / total number of terms)  = (1 + 2 + 3 + 4 + 5 + 6 + 7 + 8) / 8  = 36 / 8  = 4.5 Variance (σ2): In simple terms, the variance can be calculated by obtaining the sum of the squared distance of each term in the distribution from the Mean, and then dividing this by the total number of the terms in the distribution.  It basically shows how far a number, for example, a student’s mark in an exam, is from the Mean of the entire class. Formula: (σ2) = ∑ ( X − μ)2 / N Standard Deviation: Standard Deviation can be represented as the square root of Variance. To find the standard deviation of any data, you need to find the variance first. Formula: Standard Deviation = √σ Quartile: Quartiles divide the list of numbers or data into quarters. Quartile Deviation: Quartile Deviation is the measure of the difference between the upper and lower quartile. This measure of deviation is also known as interquartile range. Formula: Interquartile Range: Q3 – Q1. Mean deviation: Mean Deviation is also known as an average deviation; it can be computed using the Mean or Median of the data. Mean deviation is represented as the arithmetic deviation of a different item that follows the central tendency. Formula: As mentioned, the Mean Deviation can be calculated using Mean and Median. Mean Deviation using Mean: ∑ | X – M | / N Mean Deviation using Median: ∑ | X – X1 | / N Relative Measure of DispersionRelative Measures of dispersion are the values without units. A relative measure of dispersion is used to compare the distribution of two or more datasets.  The definition of the Relative Measure of Dispersion is the same as the Absolute Measure of Dispersion; the only difference is the measuring quantity.  Types of Relative Measure of Dispersion: Relative Measure of Dispersion is the calculation of the co-efficient of Dispersion, where 2 series are compared, which differ widely in their average.  The main use of the co-efficient of Dispersion is when 2 series with different measurement units are compared.  1. Co-efficient of Range: it is calculated as the ratio of the difference between the largest and smallest terms of the distribution, to the sum of the largest and smallest terms of the distribution.  Formula: L – S / L + S  where L = largest value S= smallest value 2. Co-efficient of Variation: The coefficient of variation is used to compare the 2 data with respect to homogeneity or consistency.  Formula: C.V = (σ / X) 100 X = standard deviation  σ = mean 3. Co-efficient of Standard Deviation: The co-efficient of Standard Deviation is the ratio of standard deviation with the mean of the distribution of terms.  Formula: σ = ( √( X – X1)) / (N - 1) Deviation = ( X – X1)  σ = standard deviation  N= total number  4. Co-efficient of Quartile Deviation: The co-efficient of Quartile Deviation is the ratio of the difference between the upper quartile and the lower quartile to the sum of the upper quartile and lower quartile.  Formula: ( Q3 – Q3) / ( Q3 + Q1) Q3 = Upper Quartile  Q1 = Lower Quartile 5. Co-efficient of Mean Deviation: The co-efficient of Mean Deviation can be computed using the mean or median of the data. Mean Deviation using Mean: ∑ | X – M | / N Mean Deviation using Mean: ∑ | X – X1 | / N Why dispersion is important in a statisticThe knowledge of dispersion is vital in the understanding of statistics. It helps to understand concepts like the diversification of the data, how the data is spread, how it is maintained, and maintaining the data over the central value or central tendency. Moreover, dispersion in statistics provides us with a way to get better insights into data distribution. For example,  3 distinct samples can have the same Mean, Median, or Range but completely different levels of variability. How to Calculate DispersionDispersion can be easily calculated using various dispersion measures, which are already mentioned in the types of Measure of Dispersion described above. Before measuring the data, it is important to understand the diversion of the terms and variation. One can use the following method to calculate the dispersion: Mean Standard deviation Variance Quartile deviation For example, let us consider two datasets: Data A:97,98,99,100,101,102,103  Data B: 70,80,90,100,110,120,130 On calculating the mean and median of the two datasets, both have the same value, which is 100. However, the rest of the dispersion measures are totally different as measured by the above methods.  The range of B is 10 times higher, for instance. How to represent Dispersion in Statistics Dispersion in Statistics can be represented in the form of graphs and pie-charts. Some of the different ways used include: Dot Plots Box Plots Stems Leaf Plots Example: What is the variance of the values 3,8,6,10,12,9,11,10,12,7?  Variation of the values can be calculated using the following formula: (σ2) = ∑ ( X − μ)2 / N (σ2) = 7.36 What is an example of dispersion? One of the examples of dispersion outside the world of statistics is the rainbow- where white light is split into 7 different colours separated via wavelengths.  Some statistical ways of measuring it are- Standard deviation Range Mean absolute difference Median absolute deviation Interquartile change Average deviation Conclusion: Dispersion in statistics refers to the measure of variability of data or terms. Such variability may give random measurement errors where some of the instrumental measurements are found to be imprecise. It is a statistical way of describing how the terms are spread out in different data sets. The more sets of values, the more scattered data is found, and it is always directly proportional. This range of values can vary from 5 - 10 values to 1000 - 10,000 values. This spread of data is described by the range of descriptive range of statistics. The dispersion in statistics can be represented using a Dot Plot, Box Plot, and other different ways. 
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Measures of Dispersion: All You Need to Know

What is Dispersion in StatisticsDispersion in stat... Read More