Big Data Introduction

1.Big Data Objective:

This tutorial aims to answer every aspirant to give a clear idea about the queries like what is Big Data? why to learn Big Data? We will also discuss why many of the Industries are investing more and more in this technology, why the professionals who are having skills in Big data are being paid hugely? why the industry is being shifted from legacy systems to Big Data?, why Big Data is the paradigm shift the IT industry had never seen, why and why ???

2. Why learn Big Data?

To get the answer to the above question why to learn Big Data? Let us have a look at what industry leaders say about Big Data:

Gartner – It is the new oil.
IBM – It is a Business Strategy for capitalization on information resources, but it’s not just a technology.
McKinsey – There will be a huge shortage of Big Data professionals at the end of 2018.
IBM – As technology makes it possible to analyze all the available data, Big Data is becoming the biggest BUZZ word.
IDC – Big Data’s market will be raised 7 times more than the overall IT market.

Many industries today are searching for new and better ways to maintain their position and also to be prepared for the future. According to many experts, Big Data Analytics provides leaders a path to capture insights and ideas to stay ahead in the tough competition.

3. What is Big Data Analytics?

What is Big Data? Many publishers have given their way of definition of Big Data.

Revolution, the Author explains it as – Big Data is a way to solve all the unsolved problems related to data management and handling, In earlier times the industry used to live with such big problems. With big data analytics, you can unlock hidden patterns and know the view of customers and better understand their needs.
Gartner explains big data as – Big Data is a huge-volume, fast-velocity, and different variety of information assets that demand an innovative platform for enhanced insights and decision making.
i.Definition of Big Data:
Big Data gets generated in multi terabytes in other words. Big Data changes fast and comes in a variety of forms that are difficult to manage and process using relational database management systems (RDBMS) or other technologies. It has solutions that provide different tools, methodologies, and technologies that are used to capture, store, search and analyze the data in seconds to find relationships and insights for innovation and competitive gain that were previously unavailable.
Almost 80% of the data generated today is unstructured and cannot be handled by traditional technologies. Earlier the amount of data was not that much high. We used to archive the data as there was a need for historical analysis of data. But nowadays the data is being generated in petabytes which is not possible to archive the data again and again and retrieve it when needed as data scientists need for playing with data now and then for predictive analysis unlike historical as used to be done with traditional.

4. Use-cases of Big Data:

After we learn about what is analytics. Now we can discuss various use cases of Big Data. Below are some of the use cases of Big Data from different domains :

Entertainment: Big Data is used by Amazon and Netflix to make shows and movie recommendations to their users.
Insurance: Big Data is used to predict illness, accidents, and price their products accordingly.
Self-Driving Cars: Google’s self-driving cars collect about one gigabyte of data per second. These types of experiments require more and more data for their successful execution.
Educational sector: Choosing a big data-powered technology as a learning tool instead of traditional lecturing methods. This enhances the learning of students as well as aid the teacher to track their performance better.
Automobile Industry: Rolls Royce has adopted Big Data by fitting hundreds of sensors into its engines and propulsion systems, which record each and every detail about their operation. If there are any changes in data in real-time, they will be reported to engineers who will decide the best course of action such as scheduling maintenance and dispatching engineering teams to solve the problems.
Government Sector: Big Data is being used in the field of politics to analyze patterns and influence election results. Cambridge Analytica LTD is an organization that completely drives on data to change audience behavior and plays a major role in the electoral process.

5. Big Data Technologies:

There are many technologies to solve the problem of Big Data storage and processing. Such technologies are Apache Spark, Apache Hadoop, Apache Kafka, etc. Let’s have a look at these technologies one by one –

i. Apache Hadoop :

Big Data is creating a huge impact on industries today. Therefore almost 50% of the data is moved to Hadoop. It is predicted that by 2017, more than 75% of the world’s data will be moved to Hadoop and this technology will be the most demanded ones in the market as it is now.

ii. Apache Spark :

Further enhancement of Big Data has led to the evolution of Apache Spark, which is lighting fast and general-purpose computation engine for large scale processing. Apache Spark can process the data up to 100 times faster than MapReduce.

iii. Apache Kafka :

Apache Kafka is a high throughput distributed messaging system frequently used with Hadoop. It is another addition to the Big Data ecosystem.

IT organizations have adopted Big Data initiative for managing their data in a better manner, visualizing this data, gaining insights into this data as and when required, and finding new business opportunities to boost their business growth. Every Chief Information Officer (CIO) wants his company, enhances their business models, and identifies potential revenue resources whether he being from the telecom domain, banking domain, retail or health care domain, etc. Such types of business transformations require the right tools and right people to ensure the right insights extract at the right time from the available data.

6. Conclusion:

So, Big Data is a big deal and a new competitive advantage to give a boost to your career and land in your dream job in the industry !!!

I hope this blog helped you guys to understand what is Big Data and the need to learn its technologies.