What is Big Data? – A Beginner’s Guide to the World of Big Data

There is no place where Big Data does not exist! The curiosity about what is Big Data has been soaring in the past few years. Let me tell you some mind-boggling facts! Forbes reports that every minute, users watch 4.15 million YouTube videos, send 456,000 tweets on Twitter, post 46,740 photos on Instagram and there are 510,000 comments posted and 293,000 statuses updated on Facebook!

Just imagine the huge chunk of data that is produced with such activities. This constant creation of data using social media, business applications, telecom and various other domains is leading to the formation of Big Data. You can get a better understanding of Big Data and its various concepts from the Hadoop Course.

In order to explain what is Big Data, I will be covering the following topics:

• Evolution of Big Data
• Big Data Defined
• Characteristics of Big Data
• Big Data Analytics
• Industrial Applications of Big Data
• Scope of Big Data

Evolution of Big Data

Before exploring any further, let me begin by giving some insight into why the this technology has gained so much importance.

When was the last time you guys remember using a floppy or a CD to store your data? Let me guess, had to go way back in the early 21st century right? The use of manual paper records, files, floppy and discs have now become obsolete. The reason for this is the exponential growth of data. People began storing their data in relational database systems but with the hunger for new inventions, technologies, applications with quick response time and with the introduction of the internet, even that is insufficient now. This generation of continuous and massive data can be referred to as Big Data. There are a few other factors that characterize Big Data which I will be explaining later in this blog.

Forbes reports that there are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating. Internet of Things(IoT) is one such technology which plays a major role in this acceleration. 90% of all data today was generated in the last two years.

Big Data Definition

What is Big Data?

So before I explain what is Big Data, let me also tell you what it is not! The most common myth associated with it is that it is just about the size or volume of data. But actually, it’s not just about the “big” amounts of data being collected. Big Data refers to the large amounts of data that is pouring in from various data sources and has different formats. Even previously there was huge data which were being stored in databases, but because of the varied nature of this Data, the traditional relational database systems are incapable of handling this Data. Big Data is much more than a collection of datasets with different formats, it is an important asset that can be used to obtain enumerable benefits.

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The three different formats of big data are:

1. Structured: Organised data format with a fixed schema. Ex: RDBMS
2. Semi-Structured: Partially organised data which does not have a fixed format. Ex: XML, JSON
3. Unstructured: Unorganised data with an unknown schema. Ex: Audio, video files etc.

Characteristics of Big Data

Following are the characteristics:

The above image depicts the five V’s of Big Data but as and when the data keeps evolving so will the V’s. I am listing five more V’s which have developed gradually over time:

• Validity: correctness of data
• Variability: dynamic behaviour
• Volatility: tendency to change in time
• Vulnerability: vulnerable to breach or attacks
• Visualization: visualizing meaningful usage of data

Big Data Analytics

Now that I have told you what is Big Data and how it’s being generated exponentially, let me present to you a very interesting example of how Starbucks, one of the leading coffeehouse chain is making use of this Big Data.

I came across this article by Forbes which reported how Starbucks made use of this technology to analyse the preferences of their customers to enhance and personalize their experience. They analysed their member’s coffee buying habits along with their preferred drinks to what time of day they are usually ordering. So, even when people visit a “new” Starbucks location, that store’s point-of-sale system is able to identify the customer through their smartphone and give the barista their preferred order. In addition, based on ordering preferences, their app will suggest new products that the customers might be interested in trying. This my friends is what we call Big Data Analytics.  You can even check out the details of Big Data with the Data Engineering Course.

Basically, it is largely used by companies to facilitate their growth and development. This majorly involves applying various data mining algorithms on the given set of data, which will then aid them in better decision making.

There are multiple tools for processing Big Data such as Hadoop, Pig, Hive, Cassandra, Spark, Kafka, etc. depending upon the requirement of the organisation.

Big Data Applications

These are some of the following domains where Big Data Applications has been revolutionized:

• Entertainment: Netflix and Amazon use it to make shows and movie recommendations to their users.
• Insurance: Uses this technology to predict illness, accidents and price their products accordingly.
• Driver-less Cars: Google’s driver-less cars collect about one gigabyte of data per second. These experiments require more and more data for their successful execution.
• Education: Opting for big data powered technology as a learning tool instead of traditional lecture methods, which enhanced the learning of students as well aided the teacher to track their performance better.
• Automobile: Rolls Royce has embraced this technology by fitting hundreds of sensors into its engines and propulsion systems, which record every tiny detail about their operation. The changes in data in real-time are reported to engineers who will decide the best course of action such as scheduling maintenance or dispatching engineering teams should the problem require it.
• Government: A very interesting use case is in the field of politics to analyse patterns and influence election results. Cambridge Analytica Ltd. is one such organisation which completely drives on data to change audience behaviour and plays a major role in the electoral process.

Scope of Big Data

• Numerous Job opportunities: The career opportunities pertaining to the field of Big data include, Big Data Analyst, Big Data Engineer, Big Data solution architect etc. According to IBM, 59% of all Data Science and Analytics (DSA) job demand is in Finance and Insurance, Professional Services, and IT.
• Rising demand for Analytics Professional: An article by Forbes reveals that “IBM predicts demand for Data Scientists will soar by 28%”. By 2020, the number of jobs for all US data professionals will increase by 364,000 openings to 2,720,000 according to IBM.
• Salary Aspects: Forbes reported that employers are willing to pay a premium of $8,736 above median bachelor’s and graduate-level salaries, with successful applicants earning a starting salary of $80,265
  • Adoption of Big Data analytics: Immense growth in the usage of big data analysis across the world.

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The above image depicts the growing market revenue of Big Data in billion U.S. dollars from the year 2011 to 2027. So that was all in the blog and I hope this was helpful. For further understanding, refer to the Hadoop training in  Houston.

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