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What Is a Data Pipeline? What Are the Properties and Types of Data Pipeline Solutions

A data pipeline is a set of actions that extracts data from numerous sources. It is a computerized process where the system takes columns from the database and merges them with other columns from this API. It also combines subset rows and corresponding values, alternates NAs with the median and loads them in this other database. This is known as a “job”, and pipelines are made of many jobs. Generally, the endpoint for a data pipeline is a data lake, such as Hadoop, S3, or a relational database. An ideal data pipeline should have the following properties:Low Occurrence Inactivity: Data scientists should have accessibility to the data. Users should be able to raise a query to recover the recent event data in the pipeline. Usually, this happens in minutes or seconds of the event being directed to the data collection endpoint. Scalability: A data pipeline should be able to gauge billions of data points, and product sales. Collaborative Querying: A highly operational data pipeline should support both long-running batch queries and minor interactive queries that allow data scientists to discover tables and comprehend the data scheme.Versioning: You should be able to edit and customize your data pipeline and event definitions without damaging the framework Monitoring: Data tracking and monitoring are important to check if the data is dispatched properly. In case of a failure, immediate alerts should be generated through tools such as PagerDuty.Testing: You should be able to test your data pipeline with test events that do not end up in your data lake or database, but that do test components in the pipeline.Do You want to Get AWS Certified? Learn about various AWS Certification in detailData Pipeline- UsageHere are a few things you can do with Data Pipeline.Convert received data to a common format.Prepare data for investigation and imagining.Travel between databases.Share data processing logic across web apps, batch jobs, and APIs.Power your data ingestion and integration tools.Input large XML, CSV, and fixed-width files.Substitute batch jobs with real-time dataNote that the Data Pipeline does not levy a specific structure on your data. All the data flowing through your pipelines can follow the same plan or an alternative NoSQL approach. The NoSQL feature offers a diverse structure to the data that can be altered at any point in your pipeline.What are the Types of DataData is typically defined with the following labels:Raw Data: This is on processed data stored in the message encoding format which is used to send tracking events, such as JSON. Processed Data: Processed data is raw data that has been deciphered into event-specific formats, with an applied plan.Cooked Data: Processed data that has been amassed or abridged is referred to as cooked data.The Evolution of Data PipelinesOver the past two decades the framework for accumulating and analyzing data been drastically changed. Earlier users would store data locally through log files, today we have modern systems that can trace data activity and use machine learning for real-time solutions. There are four different approaches to pipelines:Flat File Era: Data is saved locally on game serversDatabase Era: Data is staged in flat files and then loaded into a databaseData Lake Era: Data is stored in Hadoop/S3 and then loaded into a DBServerless Era: Managed services are used for storage and queryingEach of the steps supports the grouping of greater data sets. But it ultimately depends on the goal of the company to decide how the data is to be utilized and distributed.Application of Data PipelinesMetadata: Data Pipeline lets users connect metadata to each separate record or field.Data processing: Dataflows when processed and broken into smaller units, are easier to work with. It also quickens the process and saves on memory.Adapting to Apps: Data Pipeline adjusts to your applications and services. It occupies a small footprint of less than 20 MB on disk and in RAM. Flexible Data Components: Data Pipeline comes with readers and writers integrated to stream the inflow or outflow of data. There are also stream operators for controlling this data flow.Data Pipeline TechnologiesSome examples of products used in building data pipelines. These tools are used by engineers to find competent results and enhance the system’s performance and reach; Data warehousesETL toolsData Prep toolsLuigi: a workflow timetable that can be used to manage jobs and processes in Hadoop and similar systems.Python / Java / Ruby: programming languages used to transcribe processes in many of these systems.AWS Data Pipelines: another workflow management service that charts and implements data movement and processesKafka: a real-time streaming platform that allows you to move data between systems and applications, can also transform or react to these data streams.Types of data pipeline solutionsThe following list shows the most popular types of pipelines available:Batch: Batch processing is most valuable of all as it lets you move huge volumes of data at a steady interval.Real-time: These tools are improved to develop data in real time. Cloud native: These tools are optimized to work with cloud-based data, such as data from AWS buckets. These tools are hosted in the cloud, and are a cost effective and quick technique to enhance the infrastructure.Open source: These tools are a cheaper alternative to a vendor. Open source tools are often inexpensive but require technical know-how on the part of the user. The platform is open for all to optimise and edit any way they want. AWS Data PipelineAWS Data Pipeline is a web service that supports dependable process and transfer data between a diverse range of AWS services, as well as on-premises data sources. With the AWS Data Pipeline, you can frequently keep in contact with the data and back where it’s deposited. Developers can also customize the data, convert and modify it at scale, and resourcefully allocate the results to other AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR.AWS Data Pipeline aids you in creating an intricate data processing network. It takes care of all the data monitoring, tracking and optimization tasks. AWS Data Pipeline also allows you to change the data that was previously protected in the on-site data storage facility.Decoding Data Pipelines Let’s look into the process of assigning, transferring, altering and storing data via pipelines; Sources: First and foremost, we decide where we get the data from. Data can be accessed from different sources and in different formats. RDBMS, Application APIs, Hadoop, NoSQL, cloud sources, are a few primary sources. After the data is retrieved, it has to pass through the security controls and follow set protocols. next, the data schema and statistics are gathered about the source to simplify pipeline design.List of common terms related to data science Joins: It is common for data to be shared from different sources as part of a data pipeline.Extraction: Some separate data elements may be implanted in bigger fields. In some cases numerous values are clustered together. Or, distinct values may need to be removed- data pipelines allow all that. Standardization: Data needs to be consistent. It should follow a unit of measure, dates, attributes such as color or size, and codes related to industry standards.Correction: Data, especially raw data can contain a lot of errors. Some common errors are- invalid fields that are not present or abbreviations that need to be extended. There may also be corrupt records that need to be detached or studied in an isolated process.Loads: Once the data is ready, it needs to be loaded into a system for scrutiny. The endpoint is generally an RDBMS, a data warehouse, or Hadoop. Each destination has its own set of regulations and restrictions that need to be followed. Automation: Data pipelines are usually completed many times, and characteristically set on a schedule. This simplifies the error detection process and aids monitoring by sending regular reports to the system.Moving Data Pipelines Many corporations have hundreds or thousands of data pipelines. Companies shape each pipeline with one or more technologies, and each pipeline might follow a different approach. Datasets often start with an establishment’s customer base. But there are cases where they will also initiate with their assumed departments within the organization itself. Thinking of data as events simplifies the process. Events are logged in, integrated and then transmuted across the pipeline. The data is then changed and altered to suit the systems that they are moved to. Moving data from place to place means that different end users can use it more methodically and accurately. Users can now access the data from one place rather than refer to multiple sources. Good data pipeline architecture will be able to provide justification for all sources of events. It would also have an explanation or reason to support the setups and schemes caring for these datasets. Event frameworks help you get hold of events from your applications a lot faster. This is achieved by making an event log that can then be processed for use.ConclusionA career in data science is a very profitable decision considering the revolutionary discoveries made in the field each day. We hope that this information was useful in helping the reader understand all about data pipelines and why they are important.
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What Is a Data Pipeline? What Are the Properties and Types of Data Pipeline Solutions

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  • by Joydip Kumar
  • 06th Sep, 2019
  • Last updated on 02nd Jan, 2020
  • 11 mins read
What Is a Data Pipeline? What Are the Properties and Types of Data Pipeline Solutions

A data pipeline is a set of actions that extracts data from numerous sources. It is a computerized process where the system takes columns from the database and merges them with other columns from this API. It also combines subset rows and corresponding values, alternates NAs with the median and loads them in this other database. This is known as a “job”, and pipelines are made of many jobs. Generally, the endpoint for a data pipeline is a data lake, such as Hadoop, S3, or a relational database. An ideal data pipeline should have the following properties:

  • Low Occurrence Inactivity: Data scientists should have accessibility to the data. Users should be able to raise a query to recover the recent event data in the pipeline. Usually, this happens in minutes or seconds of the event being directed to the data collection endpoint. 
  • Scalability: A data pipeline should be able to gauge billions of data points, and product sales. 
  • Collaborative Querying: A highly operational data pipeline should support both long-running batch queries and minor interactive queries that allow data scientists to discover tables and comprehend the data scheme.
  • Versioning: You should be able to edit and customize your data pipeline and event definitions without damaging the framework 
  • Monitoring: Data tracking and monitoring are important to check if the data is dispatched properly. In case of a failure, immediate alerts should be generated through tools such as PagerDuty.
  • Testing: You should be able to test your data pipeline with test events that do not end up in your data lake or database, but that do test components in the pipeline.

Do You want to Get AWS Certified? Learn about various AWS Certification in detail

Data Pipeline- Usage

Here are a few things you can do with Data Pipeline.

  • Convert received data to a common format.
  • Prepare data for investigation and imagining.
  • Travel between databases.
  • Share data processing logic across web apps, batch jobs, and APIs.
  • Power your data ingestion and integration tools.
  • Input large XML, CSV, and fixed-width files.
  • Substitute batch jobs with real-time data

Note that the Data Pipeline does not levy a specific structure on your data. All the data flowing through your pipelines can follow the same plan or an alternative NoSQL approach. The NoSQL feature offers a diverse structure to the data that can be altered at any point in your pipeline.

What are the Types of Data

Types of Data in AWS Data Pipeline

Data is typically defined with the following labels:

  • Raw Data: This is on processed data stored in the message encoding format which is used to send tracking events, such as JSON. 
  • Processed Data: Processed data is raw data that has been deciphered into event-specific formats, with an applied plan.
  • Cooked Data: Processed data that has been amassed or abridged is referred to as cooked data.

The Evolution of Data Pipelines

Over the past two decades the framework for accumulating and analyzing data been drastically changed. Earlier users would store data locally through log files, today we have modern systems that can trace data activity and use machine learning for real-time solutions. There are four different approaches to pipelines:

  • Flat File Era: Data is saved locally on game servers
  • Database Era: Data is staged in flat files and then loaded into a database
  • Data Lake Era: Data is stored in Hadoop/S3 and then loaded into a DB
  • Serverless Era: Managed services are used for storage and querying

Each of the steps supports the grouping of greater data sets. But it ultimately depends on the goal of the company to decide how the data is to be utilized and distributed.

Application of Data PipelinesApplication of Data Pipelines in AWS

  • Metadata: Data Pipeline lets users connect metadata to each separate record or field.
  • Data processing: Dataflows when processed and broken into smaller units, are easier to work with. It also quickens the process and saves on memory.
  • Adapting to Apps: Data Pipeline adjusts to your applications and services. It occupies a small footprint of less than 20 MB on disk and in RAM. 
  • Flexible Data Components: Data Pipeline comes with readers and writers integrated to stream the inflow or outflow of data. There are also stream operators for controlling this data flow.

Data Pipeline Technologies

Some examples of products used in building data pipelines. These tools are used by engineers to find competent results and enhance the system’s performance and reach; 

  • Data warehouses
  • ETL tools
  • Data Prep tools
  • Luigi: a workflow timetable that can be used to manage jobs and processes in Hadoop and similar systems.
  • Python / Java / Ruby: programming languages used to transcribe processes in many of these systems.
  • AWS Data Pipelines: another workflow management service that charts and implements data movement and processes
  • Kafka: a real-time streaming platform that allows you to move data between systems and applications, can also transform or react to these data streams.

Types of data pipeline solutions

The following list shows the most popular types of pipelines available:

  • Batch: Batch processing is most valuable of all as it lets you move huge volumes of data at a steady interval.
  • Real-time: These tools are improved to develop data in real time. 
  • Cloud native: These tools are optimized to work with cloud-based data, such as data from AWS buckets. These tools are hosted in the cloud, and are a cost effective and quick technique to enhance the infrastructure.
  • Open source: These tools are a cheaper alternative to a vendor. Open source tools are often inexpensive but require technical know-how on the part of the user. The platform is open for all to optimise and edit any way they want. 

AWS Data Pipeline

AWS Data Pipeline is a web service that supports dependable process and transfer data between a diverse range of AWS services, as well as on-premises data sources. With the AWS Data Pipeline, you can frequently keep in contact with the data and back where it’s deposited. Developers can also customize the data, convert and modify it at scale, and resourcefully allocate the results to other AWS services such as Amazon S3, Amazon RDS, Amazon DynamoDB, and Amazon EMR.

AWS Data Pipeline aids you in creating an intricate data processing network. It takes care of all the data monitoring, tracking and optimization tasks. AWS Data Pipeline also allows you to change the data that was previously protected in the on-site data storage facility.

Decoding Data Pipelines 

Let’s look into the process of assigning, transferring, altering and storing data via pipelines; 

Sources: First and foremost, we decide where we get the data from. Data can be accessed from different sources and in different formats. RDBMS, Application APIs, Hadoop, NoSQL, cloud sources, are a few primary sources. After the data is retrieved, it has to pass through the security controls and follow set protocols. next, the data schema and statistics are gathered about the source to simplify pipeline design.

List of common terms related to data science 

  • Joins: It is common for data to be shared from different sources as part of a data pipeline.
  • Extraction: Some separate data elements may be implanted in bigger fields. In some cases numerous values are clustered together. Or, distinct values may need to be removed- data pipelines allow all that. 
  • Standardization: Data needs to be consistent. It should follow a unit of measure, dates, attributes such as color or size, and codes related to industry standards.
  • Correction: Data, especially raw data can contain a lot of errors. Some common errors are- invalid fields that are not present or abbreviations that need to be extended. There may also be corrupt records that need to be detached or studied in an isolated process.
  • Loads: Once the data is ready, it needs to be loaded into a system for scrutiny. The endpoint is generally an RDBMS, a data warehouse, or Hadoop. Each destination has its own set of regulations and restrictions that need to be followed. 
  • Automation: Data pipelines are usually completed many times, and characteristically set on a schedule. This simplifies the error detection process and aids monitoring by sending regular reports to the system.

Moving Data Pipelines 

Many corporations have hundreds or thousands of data pipelines. Companies shape each pipeline with one or more technologies, and each pipeline might follow a different approach. Datasets often start with an establishment’s customer base. But there are cases where they will also initiate with their assumed departments within the organization itself. Thinking of data as events simplifies the process. Events are logged in, integrated and then transmuted across the pipeline. The data is then changed and altered to suit the systems that they are moved to. 

Moving data from place to place means that different end users can use it more methodically and accurately. Users can now access the data from one place rather than refer to multiple sources. Good data pipeline architecture will be able to provide justification for all sources of events. It would also have an explanation or reason to support the setups and schemes caring for these datasets. 

Event frameworks help you get hold of events from your applications a lot faster. This is achieved by making an event log that can then be processed for use.

Conclusion

A career in data science is a very profitable decision considering the revolutionary discoveries made in the field each day. We hope that this information was useful in helping the reader understand all about data pipelines and why they are important.

Joydip

Joydip Kumar

Solution Architect

Joydip is passionate about building cloud-based applications and has been providing solutions to various multinational clients. Being a java programmer and an AWS certified cloud architect, he loves to design, develop, and integrate solutions. Amidst his busy work schedule, Joydip loves to spend time on writing blogs and contributing to the opensource community.


Website : https://geeks18.com/

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This way, you can deal with analytics as well as move between different business layers.Management skills:Even though they won’t be directly involved in the management of the project, they will have to account for given resources and deadlines. They must be able to make decisions about what works for the project and what does not. They are focused on giving satisfying business results in the given resources and timeframe.To achieve this, you must have a Bachelor’s degree or higher in IT, Computer Science, Software Engineering or any other related field. Additional certifications from AWS, Microsoft, IBM, etc. are optional but impactful. You must have in-depth knowledge of computer systems, web platforms, database management, operating systems, and security measures. You must also be able to communicate information to technical as well as non-technical members of the team. To fulfill these requirements, you can follow these steps:DegreeYou will need a bachelor’s or higher degree in the field of computer science, information technology, or software engineering. During your undergraduate program, topics like hardware compatibility training, operating systems, etc. will be covered. If you are going for a Master’s degree, you will be needing specialization in systems architecture. Some others go for MBA in Information Systems. In the Master’s degree coursework, concepts like systems design, software engineering, project management, and advanced computer architecture are included. In some colleges, along with the undergraduate training, a graduate-level certification is offered in systems architecture. During college, you must work on your communications skills as you will be working as a liaison between the engineers and the business managers. You must also be able to communicate your needs to the non-technical employees. CertificationIt is not mandatory. However, it will display your expertise as a solutions architect. Some organizations even ask the solutions architects working for them to get periodic training or get certified. Many organizations that provide these certification programs in enterprise and systems architecture offer programs for teams and individuals. ExperienceRelevant working experience will help advance your career. It must be in the field of business intelligence tools or complex database management system. During this time, you will be learning about different software programs and technology platforms. Also, you can try taking independent contractor jobs.AWS Solutions Architect Certification validityThe AWS Solutions Architect Certification is created for professionals who have experience in creating distributed applications. With this certification, you will be able to validate your skills of designing, implementing, and managing applications using the services and tools provided on the AWS platform. To get this certification, you will be required to take a 130 minutes long multiple-choice, multiple-answer exam that costs 150 USD. In the exam, the following areas will be covered:Using network technologies on the AWS platformConnecting the AWS platform to the client’s interfaceBuilding reliable and secure applicationsDeveloping hybrid systems with AWS components and on-premises data centerDesigning scalable and highly available systems on AWSImplementing and deploying applications on AWSData security practices, troubleshooting, and disaster recovery methods used on AWSAWS certification uses its thoroughness and rigor for evaluating the skills of a candidate. They focus on best practices and hands-on experience. If your organization uses AWS, a certification will clear your concepts and strengthening your knowledge. If you have no experience working on AWS, the certification will build a foundation of skills and knowledge used for working with AWS solutions. With the AWS certifications, you will have validated your expertise in some of the most profitable and in-demand skills from the most reputed and recognizable service provider in cloud computing. AWS is still the number one provider of public cloud computing, where 68% of SMBs and 64% of enterprises are running applications on the AWS platform.Once you get the AWS certification, it will be valid for 3 years from the date you passed your certification exam. For maintaining the status of your AWS certification, you have to demonstrate your expertise periodically through recertification. It will not only strengthen the value of your certificate but also display to your employers that you have the latest knowledge, best practices, and skills related to AWS.For recertifying the AWS Certified Solutions Architect- Associate, you can just retake the current exam. You will get a 50% discount voucher in the benefits section of the AWS certification exam. Also, you can just earn a professional-level certificate that will satisfy your associate-level recertification requirement.There is an AWS Certification Program Agreement containing terms for governing your participation in the certification program, entering the AWS, Inc., which is a part of the customer agreement. To get an AWS certification, you must have:Taken the certification exam and passedComplied with the requirements of the AWS certificationAdhered to the rules and regulations applied on the programWhen you have the AWS certificate and are working on the AWS platform, you must be:Conducting activities in a competent and professional mannerPromoting the AWS services maintaining its name and reputationNot making any guarantees, warranties, and representations related to AWS or its features, specifications, and capabilitiesNot engaging in any false, illegal or deceptive practicesComplying with the terms of the customer agreementAs a holder of the AWS certification, you have the right to use the name of your AWS certification. This right is revoked when your AWS certification is terminated or no longer valid. Also, AWS can revoke your license at any time by giving you a written notice.AWS Solutions Architect Associate Required SkillsSolutions architect is an in-demand tech job. Organizations are hiring Solutions Architects to help them design and develop advanced cloud-based solutions as well as migrate their infrastructure and workload to the existing AWS cloud. There are limitless virtual resources on the AWS platform that can be provisioned and disposed of. With these many resources available at their disposal, a Solutions Architect must have the skills to handle the data and infrastructure. Here are a few skills a solutions architect must have:1. Programming languageIt is the most basic and important skills for a Solutions Architect. Since they have a background in software development, this won’t be new to them. As a solutions architect, you must be skilled in Python, Java, C# or any programming language with an official AWS SDK. Having programming skills will help you to create logical and viable solutions. Also, it can be used for creating a demo or proof of concept for showing a point or learning how to use the latest technology.2. NetworkingKnowledge of networks like DNS, VP, HTTP, TCP/IP, and CDN will help you in creating a scalable and secure cloud-based solutions. You must also have working experience in services like CloudFront (CDN), Route 53 (DNS), and Virtual Private Cloud (VPC). This will help you in using the public as well as private subnets, VPC peering, and internet access for designing your cloud network.3. Data StorageAs a Solutions Architect, you must have knowledge of databases. There are several data storage options available on the AWS platform. This includes powerful and simple bucket storage like S3, relational database service, and Hadoop clusters. To select the one for your company’s data, you will have to compare different databases’ performance, capabilities, and price.4. SecurityThere are services and guidelines laid down by the AWS like securing access to your data and AWS account to ensure that only authorized people and code are allowed for performing specific tasks. You must also have a thorough understanding of the Identity and Access Management (IAM) that is used for defining which user and services can access the resources. You need to learn about securing your network through Access Control Lists and Security Groups.5. AWS Service SelectionWhen it comes to cloud architecture, AWS provides several front-end as well as back-end technologies. As a solutions architect, you must have the skills required for knowing which services are relevant to your organization. You must know what your end goal is. For this, you must have knowledge of SNS (notifications), SQS (Simple Queuing), RDS (Relational Database Service), and IoT related services.6. Cloud-specific technologiesThere are different rules while using cloud. As long as you correctly design and harness AWS infrastructure, availability, scalability, and recovery are comparatively easy. To create cost-effective and scalable applications, you need to use storing state and messages, and handle failures correctly. If you want to create applications which can be scaled through creating instances of the same service, you need to use patterns like eventual consistency, queuing, and pub/sub.7. CommunicationYou need to be able to explain your vision to managers, software developers, and fellow architects through documents, emails and presentations. You need to learn how to write in a concise, clear way, presenting your idea and displaying complex environments through diagramming tools. Apart from the above-mentioned skills, you must have the following relevant working experience:Software developmentData securityNetworkingAWSAlso, you must have hands-on experience working with Linux, the architect’s toolbox (Chef, Puppet, Docker, Capistrano, Jenkins, and Ansible), Infrastructure as code (CloudFormation), advanced project management tools, etc.Why Architecting in AWS?With Architecting in AWS, you will be able to perform the following:Application of the frameworkManaging multiple accounts for the organizationConnecting the AWS cloud to the on-premises dataDiscussing the billing to connect VPCs of multi-regionTransferring large data to AWS from the on-premises data centerDesigning large data centersUnderstanding architectural designs used to scale a large websiteProtecting the infrastructureUsing encryption to secure the dataEnhancing the solutions’ performanceOnce you get the AWS Solutions Architect certification, you will have a high-opportunity market and greater earning potential. This certification is one of the best paying certifications in the IT sector. It is perfect for people working on improving their AWS cloud skills pursuing a worthy certification path. Also, Solutions Architect working on the AWS with the certification can get an average annual salary of $114,000.AWS Certified Solutions Architect Exam ScheduleTo prepare for the AWS Certified Solutions Architect exam, you will need at least three months during which, you will cover the AWS ecosystem and general concepts of cloud computing. The first step is to create a document where you will mention everything that you will learn. This will be your study guide.The first monthThe task for the first month is to lay the groundwork. In this, you will get an introduction to the Ecosystem of AWS and how core AWS services interact with each other. It is the hardest month. So, you need to stay focused and vigilant.The second monthThis month you build the foundation. You need to keep up with your pace. During this month, you will be covering concepts like auto-scaling, load balancing, etc.The third monthUp until now, you have covered all the important topics. Now, you have to do some reading, go through FAQs and white papers. Also, study the best AWS practicesOnce you think you are ready, you can schedule your exam. To schedule your AWS Certified Solutions Architect exam, you need to follow the below-mentioned steps:Sign in to aws.training. Next, click Certification in the top navigation.Click AWS Certification Account, followed by Schedule New Exam.AWS Certified Solutions Architect salary in IndiaAWS certification exams are in great demand and are now offered in multiple languages across the globe. As more and more companies are making the move to AWS, it has led to an increase in salaries of professionals who are AWS certified. Designed for solutions architects, system operations administrators, and developers, AWS certifications are role based. So they can be used by candidates working at associate as well as professional level. For solutions architect, AWS offers certifications for the associate and professional level. To be eligible for the professional level certification, you must have the associate level certification.In India, the average pay for an AWS Certified Solutions Architect is Rs 10,00,000. Your salary will also depend on your experience in terms of prior knowledge of database, operating system, network, and best practices used in AWS. Also, your expertise level varies with the certification you have. An AWS certification will help you get priority over other professionals.With so many job profiles, it is clear the cloud computing jobs are increasing every year. According to the report by Gartner Forecasts Worldwide, the market of Cloud computing is expected to reach $411B by the year 2020. Also, from the year 2015 to 2018, the AWS adoption rate has increased to 68%.AWS Certified Solutions Architect Exam If you want to get started in cloud computing and start developing applications on the AWS platform, you need to have an in-depth knowledge of the services offered by the AWS. For this, you need AWS certification. For solutions architect, there is an associate-level and a professional-level certification. Once you have prepared for the exam, you need to get ready for it. For this, you need to understand the following:1. Types of QuestionsIf you have been taking practice tests, you will have a firm grasp on the subject. Every certification exam covers certain material and you must have a thorough understanding of every concept to be confident. AWS certification exams have multiple choice and/or multiple answer questions. All the questions are real-world scenario based with charts and graphs for more detail. To test your knowledge, ambiguous questions are written.2. Format of the examAll the certification exams offered by AWS have the same format where at a time, only one question is displayed. There is an option to mark the question for later. After you have gone through all the questions, a list of every answered question will be displayed. The selected options will be displayed as letters. There will an asterisk next to the questions that were marked for later. 3. Cost and duration of the Certification examThe cost of the associate-level certification is $150 while the professional-level certification costs $300. The duration also varies for both the exam. For the associate-level, the duration is 130 minutes while that for the professional-level is 170 minutes.4. Environment for the testYou can use Pearson VUE or the PSI network for taking the AWS exam. For admission, you will have to show two personal identifications at the exam center. The primary identification includes a valid driver’s license issued by the government and passport. For secondary identification, you can either use a second primary ID form or your debit card.  There are no personal items, food, and drinks allowed in the test area. Also, people wearing watches, eyewear, or GPS tracking device will be inspected. You can request paper, pencil, marker, or whiteboard.AWS Certified Solutions Architect Exam Retake PolicyGetting AWS certified will help bring tremendous job growth and multiple job opportunities. One of the most common questions people ask is what to do if you fail the certification exam. There can be many reasons behind this like inadequate preparation or it might not have been just your day. One thing to remember is that you shouldn’t be afraid of failure. Worrying about whether you can pass the certification exam or not will only hinder your preparation. There are a lot of people who have failed the AWS certification exam. After all, they are difficult exams which can separate masters in AWS from the others. You need to remember that plenty of people pass the certification exam too. Having stress of the exam is common. The important thing is to remember how to manage that stress. Every now and then, you need to take a break and maintain the work-life balance. When there are just a few days left for the exam, you will start to doubt yourself and feel underprepared. Take a deep breath and remember that you have worked hard and prepared well for the exam.After you have taken the exam, you will be immediately shown your results on the screen. However, there is no single passing score. Instead, AWS has a statistical method to determine if you passed or failed. The passing scores change every exam. If you win the exam, you will receive an AWS Certified logo, digital badge, and an e-certificate within 72 hours. However, if even after all the preparation you still fail, don’t feel disappointed. It is a tough exam and not everyone clears in first attempt. You will be eligible to retake the exam after 14 days. There is no exam limit. You can retake the exam as many times as you want. However, for every attempt, you will have to pay the complete registration price. For beta exam test takers, only one attempt is available.After AWS Solutions Architect CertificationAfter you have passed the exam, within 72 hours, you will get an AWS Certified logo, a digital badge and an e-certificate in your AWS account. You can use the digital badges to display your status on Facebook, LinkedIn or any other social media website. Within 5 days of finishing the exam, you will receive a transcript of your results.The IT landscape is shifting more and more towards cloud computing. This has led to an increase in prominence of the AWS. And with this certification, you will be ready for the change as the following skills will be validated by a renowned brand:Architecting and deploying robust and secure applications using the AWSUsing the principles of architectural design for defining a solution that fulfills all the requirements of the customer.Using the best practices for implementation.After you get your certificate, you should start working on projects. If you have old projects hosted on a web server, you can migrate them on to the AWS platform.All the figures mentioned above are accurate as of August 2019 and are sourced from online job portals such as Indeed.com, Salary.com, Glassdoor.com, etc.
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What is the Learning Path to Become an AWS Certifi...

The AWS Solutions Architect – Associate certific... Read More

What is AWS Certification Syllabus?

Cloud computing has become a lucrative space for IT graduates and tech-savvy students to develop a career in. With data at the forefront of the modern-world, Cloud tech plays an important role in the development of businesses. AWS is among the biggest platforms offering a selection of 11 top-notch cloud certifications to professionals, setting a new yardstick of quality and efficiency in the industry. Getting certified by AWS is a sure-shot way for professionals to make them stand out among peers.Need for AWS CertificatesHaving an  AWS certification adds a degree of authenticity to your cloud computing skills, widening your web visibility, and generating better earning opportunities. Most companies are looking for reliable and professional cloud support to speed up their projects. AWS certification increases your credibility in the IT sector, it also enhances your chances of getting hired by the top companies and corporate houses around the world.Choosing the Right AWS CertificateMost enterprises have switched over to cloud-based platforms, tweaking their marketing strategies to suit the needs of their customers. Cloud storage, sharing, and services have been in vogue for a few years now, gaining more popularity and business with each passing year. AWS has over a million customers at present, changing the prejudice that people have against multi-cloud strategies. The top cloud provider in 2018 is AWS, according to the 2018 RightScale State of the Cloud Report. The future of cloud-based platforms and services looks very promising with the likes of AWS gaining increasing popularity among clients. Also, with investments pouring in and a gradual yet consistent expansion to international markets, AWS is slowly but surely growing and will soon become a leading cloud-based service provider in the industry.Candidate CertificateAWS certifications help validate the applicant’s technical skills and overall practical knowledge. It is, therefore, a very sought-after platform for both newbies and established professionals in the tech sector. AWS is equipped with the latest tech developments, upgrading the coursework regularly to keep up with the changing trends of the industry. AWS also provides candidates with the necessary practical skills and hands-on experience in cloud architecture, data management, and web security.Employee CertificateAWS cloud platform is not only useful to independent candidates and tech-savvy engineers but also employees looking for new ways to improve their skills and get better promotional opportunities within the organization. Some companies are also developing their own cloud certificate programs to customize the skills and coding knowledge of the employees to suit their needs.Getting Started- how long does it take to get certified?Candidates who are planning to opt for AWS certification need not devote their entire time to studying. You can easily manage the coursework along with the various professional and personal commitments. Usually, it takes about two months for professionals to complete the AWS curriculum. And this is when you are devoting approx. 80 hours of study. Candidates who are new to the AWS framework might need more time to get used to the system. We would recommend 120 hours of study or a minimum of three months of preparation before you opt for the exam. Start with the basics, and then move on to the more complex topics to get a thorough understanding of the subjects.Which is the Best AWS Certificate?AWS at present offers eleven certifications: an introductory certification, three associate-level certifications, two professional-level certifications, and three specialty certifications.AWS Certified Cloud PractitionerAWS Certified Developer – AssociateAWS Certified SysOps Administrator – AssociateAWS Certified Solutions Architect – AssociateAWS Certified DevOps Engineer – ProfessionalAWS Certified Solutions Architect – ProfessionalAWS Certified Big Data – SpecialtyAWS Certified Advanced Networking – SpecialtyAWS Certified Security – SpecialtyAWS Certified Alexa Skill Builder – SpecialtyAWS Certified Machine Learning – SpecialtyThe Process- Steps to Prepare For AWS ExamsGetting an AWS certificate is not an easy task. For starters, you have to put in a lot of time and effort into mastering the fundamental and core concepts of AWS and cloud computing. Next, you have to clear the certification exam and then undergo rigorous training to get some on-site job experience. Here are some of the steps that aspiring candidates can follow to study for the AWS certificate test:Pick an AWS training institute and get yourself enrolled to get an understanding of the syllabus and overall curriculum of AWS certification exam.Go through all the study guides and other reference materials that you can get your hands on.Read numerous AWS whitepapers, as these contain crucial information about the kind of questions asked in the evaluation test and how to answer themNow that you have an idea about the theory, it is time to put it to practice. Take practice tests and work on sets to learn to execute technical skills.Once you are certain of your preparation, schedule the exam. Most candidates take about 80-120 hours of practice/studying to prepare for the exam.Foundational CertificationAWS Certified Cloud Practitioner is the latest certification offered by AWS and is an entry-level course which is designed to evaluate the candidate’s understanding of the core concepts of cloud computing. People opting for this course need at least six months experience in AWS cloud services from either the technical, managerial or marketing sector.The foundational AWS course includes the basic AWS features and the common uses of the cloud services. It also teaches students about the core cloud architectural principles, security functions, and operations offered here as well.Associate Certification:Getting an AWS certification can work wonders for your IT career. It helps learners build credibility in the market, and also boost their confidence about their own programming skills. Most IT-based organizations and companies from other sectors prefer candidates who have cleared their AWS exams and received a high-level certification for the same. Listed below are some of the top AWS certifications available.AWS Solutions Architect AssociateAWS Solutions Architect Associate certification is for the experienced candidates who have already mastered the basic features and concepts of AWS. It covers the technical aspects of cloud-based applications- particularly the designing and advertising part of it. Candidates have to answer a set of multiple-choice questions in 130 minutes. The questions will be based on networking technologies of AWS, AWS applications, hybrid systems, AWS data protection measures, etc.AWS Developer AssociateThe  AWS developer associate exam lasts for a duration of 80 minutes in which candidates have to answer a set of multiple choice questions. The main topics would be from AWS services and databases. There might also be questions from AWS architecture and other practical topics.AWS SysOps Administrator AssociateThis  AWS Certified SysOps Administrator Associate exam is suited for system administrators. It is taken only by industry professionals who have substantial experience in AWS concepts as well as the practical experience to back it up. Knowledge in Linux or Windows administrator will be an added perk. The exam format is the same.Professional Certification:Solution Architect ProfessionalAn AWS Architect Professional is an advanced position, involving a wider set of responsibilities and greater flexibility. Candidates should have a deeper understanding of AWS framework, come up with better actionable solutions and offer effective architectural recommendations. Only applicants who have 2 years of work experience are eligible for this exam.AWS DevOps Engineer professional The DevOps Engineer certification involves detecting, delegating, operational, and supervising applications on the AWS platform. This exam concentrates on the two fundamental concepts of the DevOps movement- continuous delivery (CD) and the automation of processes.Specialty CertificationsAWS offers Specialty certifications, including Big Data Speciality, Networking Speciality, Security Speciality, Alexa Skill Builder Speciality, and Machine Learning Speciality.AWS Big Data Speciality This courseware is perfect for data analysts and engineers looking for better opportunities in the cloud computing sector. It allows the applicant to explore the numerous big data concepts and its execution on the AWS platform. It even tests the person’s coding skills, automation data analysis using AWS. Minimum five years hands-on experience in a data analytics field is recommended.AWS Networking SpecialityThe networking specialty certification is intended to check a candidate’s networking skills and ability to implement them on the AWS framework. It even validates your cross IT architectural skills at figuring out innovative solutions for real-time issues. Advanced knowledge of AWS networking concepts and technologies is recommended.AWS Security SpecialityThis certification covers topics necessary for assuring the safety and security of the AWS platform. Hence, it is a field that requires a sense of responsibility, sincerity and deep knowledge of programming. The exam tests the applicant’s knowledge on a variety of topics including infrastructure development, data security, encryption, incident response, and access management. At least two years of hands-on experience securing AWS workloads is recommended.AWS Alexa Skill Builder SpecialityThis certification is necessary to authenticate your practical know-how in generating, testing, and organizing Amazon Alexa. Candidates basically have to be good at coding, building applications and have six-months experience in creating Alexa skills by means of the Alexa Skills Kit.AWS Machine Learning SpecialityThis certification exam tests the candidates coding skills, technical knowledge and also ML skills. The applicant should be able to identify, create and implement ML concepts in basic AWS platforms and cloud-based programs. Also, note, only people with a minimum of 2 years’ experience in Ml or big data can apply.AWS Exam TopicsAWS Exams are not limited to a few select topics or set coursework. In fact, candidates have to be well versed in almost all the areas concerning the IT sector from basic coding to complicated concepts like big data and machine learning. Also, we would suggest the aspiring candidates have some practical experience with AWS before applying for the exam. Cloud-based architectures, cloud developing services, Networking skills, and data security are some of the core areas one can focus on.Preparing for AWS Certificate Exams AWS certifications, as discussed earlier, are a series of exams which aim at preparing and validating aspiring candidates by honing their programming skills and other technical skills and optimize it for the AWS platform. AWS is a cloud computing interface, which is intuitive and reliable enough to allow clients to save, manage, monitor and share their information in a quick, protected and hassle-free way. Aspiring candidates who are planning to prepare for the AWS certificate exams must already be aware of the intense competition. There are various candidates trying for these exams every year. AWS offers a set of 11 certifications: a foundational certification, three associate-level certifications, two professional-level certifications, and three specialty certifications.There are several online courses and tutorials available online where one can log in to know all about the various areas one can explore and learn about via the AWS platform. The AWS exam includes multiple-choice questions and lasts for a duration of 130 minutes. These questions check the candidate’s comprehension skills as well, as you have to carefully read and understand the question to comprehend what is asked and which AWS concept should be applied to solve the issue.What’s New In AWS CertificationAWS has recently expanded its test centers and is now accessible in 5000 locations spread across 180 countries. Other than that, AWS now also offers candidates better courseware and updates syllabus for the latest exams. This curriculum is detailed, comprehensive, easy and freely accessible. Now, all there is left to do is sign up and take a class that piques your interest and best suits your caliber. Best of luck!
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What is AWS Certification Syllabus?

Cloud computing has become a lucrative space for I... Read More