Big data is now a reality. IBM has declared that in a single day, we generate 2.5 quintillion bytes of data. Big data offers colossal benefits to businesses and individuals alike. Gartner reports that the 2022 trends in data and analytics include: adaptive AI systems, data-centric AI, metadata-driven data fabric, and always sharing data. The advantages of big data include tangible benefits that it brings to all kinds of organizations irrespective of type and size: right from improved efficiency in operations and increased visibility of the fast-changing environments to the optimization of products and services for customers. As a result, new architectures and techniques for mining, processing, managing and analyzing big data across a business continue to emerge. The organizations and aspiring big data professionals alike, therefore, seek Big Data and Hadoop Course for enhanced efficiency.
What Is Big Data?
Big data is a huge assemblage of information and data in the form of structured, semi-structured and unstructured form that organizations collect and mine for information that is used in machine learning projects, predictive modeling and various advanced analytics applications. Systems that store, process, and manage big data are big data tools and technologies and have become a common feature of data management architecture in organizations for big data analytics.
Big Data Examples
Big data can come from any source. Some examples include emails, medical records, internet search logs, mobile apps and social media. Machine-generated data like network and server log files, data from various sensors on industrial equipment, manufacturing machines and internet of things (IoTs) devices also comprise big data.
Apart from this, big data also includes external data on consumers, financial markets, weather, geographic information, traffic, and research among others in the form of texts, images, audio or video.
What Are the Benefits of Using Big Data?
Organizations big data advantages
As per the survey by NewVantage Partners, 73.2% of the surveyed executives mentioned that they observed measurable business results from big data.
Businesses derive multiple benefits from big data. Some pros of big data are:
Nearly 59.4% (6 out of 10) of the respondents mentioned that with the help of big data tools, they were able to reduce costs and increase operational efficiency.
About 66.7% (or two thirds of the respondents) mentioned that they started using big data to reduce expenses.
Though only 13% of the respondents selected cost reduction as their primary goal of big data analytics, suggesting that many businesses perceive the cost reduction benefit of big data as a very welcome side advantage.
2. Augmented Revenue
In Precisely Holdings, LLC survey, more than half of respondents or 54.7% mentioned that they were using big data tools to increase revenue and accelerate growth based on better insights (that resulted from their improved decision-making and customer service capabilities).
3. Enhanced Customer Service
NewVantage Partners survey revealed that 53.4% of the participant companies had mentioned that improving customer service was the second most important goal of their big data analytics projects, and they also achieved some degree of success in this. Data from CRM (customer relationship management), social media and others provide businesses with big insight into their customers, and quite naturally, enterprises would like to use big data to have a better understanding of their customers and improve customer service.
4. Agility Expanded
Precisely Holdings, LLC survey again reports that 41.7% of the business respondents mentioned their increased agility by using big data to align their IT and business efforts better. Furthermore, they used their analytics to support more frequent and accelerated changes to their business strategies and tactics.
5. Faster Time-to-Market
NewVantage Partners survey revealed that businesses were using big data to achieve faster time-to-market. 53.6% of the surveyed companies mentioned that they had kept this as the primary goal of big data analytics projects and 54.1% agreed that they had achieved some success. The other side of this is faster growth and higher revenue.
6. More Innovation
11.6 % of the respondent executives of the NewVantage survey mentioned that their companies were investing in big data analytics primarily as a means to bring innovation in their markets. This way, they could remain ahead of the rest of the market with their new products and services by getting insights from big data that their competitors did not have.
7. Detection of Fraud
Among the plentiful benefits of big data in business, this is another gratuity that big data brings, especially in the banking and financial services industry. Because big data analytics systems rely on machine learning, they are superb at detecting anomalies and abnormal patterns. As a result, banks and credit card companies can spot stolen credit cards fast or fraudulent purchases made often before the fraudsters get to know.
8. Improved and Increased Productivity
NewVantage Partners survey mentioned that by using tools like Hadoop and Spark, 59.9% of the businesses were able to increase their productivity. Because such modern tools analyze data accurately and fast, this increases even personal productivity apart from the organizational productivity improvement throughout the company.
9. Improved Decision-Making
36.2% of the respondents of NewVantage Partners survey said that better decision-making was the chief goal of their big data analytics venture. 84% already started working towards it and 59% already achieved some measurable success with, an overall success rate of 69%. The insights derived from big data analytics helped this business to make faster and better business decisions resulting in the growth and ability to remain ahead of its competitors.
10. Individuals' Big Data Advantages
Big data is even a big influencing factor in the day-to-day life of individuals by influencing the daily environments of people like:
The collection and application of big data from mass information have changed the entire healthcare sector.
The areas where big data concept advantages are creating a big impact are:
Prediction of epidemics and disease transmission.
Protocols of treatment.
Tracking and improving health, well-being and quality of life.
Maintaining and tracking of personal records of health.
12. Transportation and Travel
Thanks to big data, the way people move around their cities and find different locations to reach their desired destinations has changed dramatically in recent years. The example areas are:
The help of GPS and intelligent maps that help to locate location.
Better traffic control and understanding the congested/less congested for traveling.
Improvement in an air traffic system.
Increased efficiency in mass transit systems.
Various government departments like police and fire, to name a few, depend on big data to develop and implement new policies and procedures for public safety. The law enforcement department and police worldwide use big data to work proactively rather than reacting to crimes and incidents after they have occurred. This is even true for dealing with terrorists and terrorist attacks, the security of high-profile officials. The networks of cameras, mobile devices, and computers track incidents in real-time for the police to work efficiently.
14. News, Information, Social Media
Right from the news collection and delivery of the news to comments on the news, big data covers the entire news cycle. Reporters increasingly utilize social media to gather the information that shapes their news reports. Often it happens that any major news is often first reported on social media platforms like Twitter or FaceBook and reaches the public in seconds much before they make news headlines.
Big data trends in social media shape various media timelines and determine the stories of higher importance or particular interest to the public. The automated data processing systems determine the most talked about stories and news reporters and anchors push such stories to the front.
15. Music, Shows Movies
Perhaps the biggest impact of big data in personal life is felt through the entertainment industry which includes various OTP platforms, music and video streaming services, television and film platforms.
Platforms like Pandora and Spotify heavily rely on big data for tracking the music choice of an individual, making projections in real-time, offering a weekly, personalized playlist and even marking it with the individual user’s photo.
16. Shopping and Marketing
Major retailers use big data to shape their front-end business and also direct their marketing efforts.
The same is realized while shopping online on platforms like Amazon or others that depend on big data to push their products by showing ads and projections about what an individual might like to buy now or in the future. They do this as the individual’s shopping experience, preferences, interests, data and information that they keep collecting, storing and analyzing.
17. Employment and Job Applications
Employers make good use of big data to facilitate their hiring processes by taking services from enterprises/firms that aggregate massive volumes of candidates’ data, to choose the candidates who are most likely to fit and excel in the particular jobs.
Colleges and universities especially the private ones rely on big data to increase and speed up their enrolment process by identifying and attracting students with the help of specially designed programs of various types. Likewise, big data also influences admission decisions to predict the success of both students and the institutions.
Types of Big Data
Big data may be structured, unstructured or semi-structured.
Structured data- has a fixed format or structure. Like the one shown below:
Unstructured data- where the data form or structure is unknown from heterogeneous data sources containing various formats like images, videos, text files and more. A Google search is a good example.
Semi-structured data – shares the properties of structured and unstructured both. An example could be
Big data- the 4 main processing components
It is the process of gathering and preparing the data by identifying the data sources, determining how they will be collected (like gathering in batches or streaming) and taking the data through cleansing, massaging and organizing. The whole thing is done by a) extraction process or data collection/gathering and b) transformation process.
The ingested data needs to be stored which may be a data warehouse or a data lake depending on the requirements. For this, it is important to know the organizational goal first before performing any big data process.
This phase includes analyzing the data to get valuable insights for an organization. Analytics uses four kinds of methods: prescriptive, predictive, descriptive, and diagnostic. Machine learning algorithms and artificial intelligence are used in the analysis phase.
Now that big data analytics have produced meaningful and actionable insights appropriate for a business, this is the stage where data visualization and data storytelling methods are used to share the insights effectively across the organization for technical and/or non-technical audiences like project managers and stakeholders.
Features of Big Data
Often big data is defined in terms of three Vs which denote:
Volume- signifying the massive volume.
Variety- the various data types stored in the big data systems.
Velocity- the speed at which the huge data volume and variety get generated, collected and processed.
Doug Laney, an analyst at consulting firm Meta Group Inc. first identified these features of big data in 2001.However, Gartner further propagated this after acquiring Meta Group Inc., and now other V’s have been added to the characteristics of big data like veracity, value and variability.
Veracity- denotes the degree of accuracy of data sets and how reliable they are. Since the raw data gets collected from varied sources, there could be quality issues that need to be rectified through a data cleansing process that eliminates bad data. Data management and analytics must have good quality, should be error-free and accurate for correct analytics results.
Value- Not all the data that gets collected has real business value or is useful. Therefore, businesses need to confirm that the data used in big data analytics projects must be relevant to the business.
Variability- refers to the variety of data that may have multiple meanings or may need to be formatted differently in separate data sources.
Who Uses Big Data?
Big data is used by almost all business and industrial sectors and also government, defense, space and semi government departments and agencies. Here is a list of only a few domains that use big data heavily.
Big data helps to reduce the cost of treatment by avoiding the chances of performing unnecessary diagnoses.
Helps to predict and prevent disease spread/epidemic.
Data on the past medical records of patients can help in prescribing evidence-based medicines ensuring faster and better treatment.
Proper use of big data helps any government of any country. Some examples are:
1. Designing welfare schemes
Making faster and well-informed decisions on various political programs.
Keeping track of the agricultural sector.
Overcoming national challenges like unemployment, energy resources, terrorism and plenty of other areas.
All aspects of cyber security and illegal monetary transactions/hoarding information depend on big data.
The reliance on big data for this sector is shooting up every second. Some of the uses are:
Preventing misuse of credit/debit cards.
Avoid money laundering.
Increased efficiency, customer satisfaction.
Big data in space
Space agencies gather and analyze petabytes of data to simulate the flight path before launching the actual payload in space, considering various factors like weather, payload, orbit location, trajectory, etc.
They collect data daily by observing outer space and information received from the orbiting satellites, probes studying outer space, and rovers on other planets.
Big data is used to make transportation management efficient.
Some of the uses are:
Congestion management and traffic control in real-time.
Route planning and modes of transportation planning for better, faster travel and reduced wait time.
Why Choose Big Data as a Career?
As per the World Economic Forum, nearly 97 million roles will be in increased demand by the year 2025 and out of the top most demanded roles, data-related roles will be topping the list, including data analysts, data scientists, artificial intelligence/machine learning, cloud computing, digital transformation, and more. There will be a decreased demand of 85 million jobs that will either be dominated or replaced by automation, technology, and the need for organizations to capture and utilize data. No doubt, fresh graduates are opting for Big Data training to make themselves future ready.
As per HP, big data and artificial intelligence will rule the future with healthcare as the main area from creating new strategies, reducing the risk factors to creating wearables to make healthcare more accessible.
Future Prospects of Big Data Employment: Categorized
1. Machine learning, data mining, big data analytics
Position titles : data scientist, data analyst, data mining engineer, business intelligence, machine learning engineer and business analyst.
Position titles : data engineer, big data engineer, software developer.
3. Big data operations and cloud computing
Includes: skill development in DevOps, storage, networking, virtualization, Linux and serverless architecture.
Reasons behind Choosing Big Data as a Career
1. In-demand profession
Fully utilizing the advantages of the big data concept, 75% of the IoT (Internet of Things) providers use big data analytics and 68% of them are facing issues in finding expertise with relevant experience and skill. The scope is anticipated to grow even more in the future. Predictive analytics, perspective analytics and descriptive statistics are the major in-demand data analytics job opportunities.
2. Simple to start
Agreed that data analytics needs programming skills that include Java, C, Python, or Scala. But those with a natural interest and inclination in finding solutions to problems will find it easy and interesting to learn these languages regardless of the present profession.
Big Data Analytics Courses can be suitable for both fresh and knowledgeable aspirants who either want to learn or wish to broaden their skills in big data which includes knowledge of Java /OOPS programming or working with Unix /Linux platforms and tools like Hadoop, R etc.
3. Multi-domain or multi-industry opportunities with brands
To reap the full potential and benefits of using big data, brands like Microsoft, SAP, EMC, HP, Software AG, Oracle Corporation, IBM and Dell have invested more than $15 billion in software enterprises that specialize in data management or data analytics; thereby increasing the demand for specialists across industries and domain types. Examples of sectors that super utilize the benefits of big data are healthcare, manufacturing, education, media and others. One has the option to select from an array of industries that match one’s interests and skills.
4. Good future
Working with big data analytics fortifies a person with insights about what worked and did not. This increases the importance of such an employee within the company as the company takes action based on the analysis and solutions of the employee who then turns into key-performer influencing the top executives who start depending on such an employee.
5. Opportunities to work with big brands
One can start a career in big data with start-ups and small companies and make them realize the advantages of using big data. After having enough experience, chances of getting employment with brands like IBM, SAP, Microsoft, HP, Oracle and others (investing billions into Big Data research and in constant need of data specialists with experience) increase with plenty of growth opportunities. Besides, working with such a company reduces or even eliminates the cost of learning any programming language as the company invests in in-house employee training/ brings the opportunity to work with a team of experts.
6. Domain expertise
Since big data analytics in multiple technical languages, mastering a particular language gives the accountability and authority for the complete delivery of domains that one specializes in. Thus, as an expert, such a professional will be able to offer a reliable solution to companies which will not require to purchase an expensive database from elsewhere.
7. Freelance consultancy
After gaining enough experience a big data analyst can switch over to consultancy services to clients offering insights about key areas, including marketing and sales, strategizing, analysis, visualization of data arriving from multiple sources and more. Those with a good grasp of smart algorithms and the latest big data technologies, can offer consultancy services to multiple companies and gain greater exposure instead of pursuing a fixed-hour regular job.
Our Final Thoughts on Big Data
Our world is now rich with big data of all forms. Companies and governments are trying to make the best use of big data competitive advantage to derive better business strategies and decisions. But the reality is companies (including the blue-chips or the big brands) are struggling to maximize the business potential of their big data environments and analytics. A Gartner survey report of January 2022 mentions only 39.7% of the companies were able to manage big data as a business asset, and just 26.5% could create data-driven organizations. The optimum use and importance of big data lie not in how much data they collect but in how a business utilizes the data to handle the big data benefits and challenges.
Mounika Narang is a project manager having a specialisation in IT project management and Instructional Design. She has an experience of 10 years
working with Fortune 500 companies to solve their most important development challenges. She lives in Bangalore with her family.
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Frequently Asked Questions (FAQs)
1. What is the importance of big data?
Helps organizations understand the market/opportunities.
Helps in research and development and healthcare efficiency.
Better customer service, and personalization.
Reduces cost, increases profit.
2. What are the challenges of big data?
Scarcity of adequately skilled professionals to make good use of big data and get meaningful insight.
Lack of understanding of the massive data and how to make the best use of it.
Confusion while selecting the right big data tool as per the application.
3. What is the impact of big data?
Improved cyber security and threat management.
News and media channels need big data information for delivering the appropriate information.
Ecommerce majorly depends on big data for their sales and marketing.
Space, healthcare, and defense depend on big data information.
4. How is big data changing the world?
The biggest challenge big data throws is how best to analyze and apply big data for the betterment and how to prevent its misuse as well.
5. What problems does big data solve?
Better traffic management and improvement in transport management.
Better healthcare management, research, predicting diseases and epidemics and their management.