What You need to Know about Big Data?

Big Data is a phrase that gets bandied about quite a bit in the media, the board room – and everywhere in between. It’s been used, overused and used incorrectly so many times that it’s become difficult to know what it really means. Is it a tool? Is it a technology? Is it just a buzzword used by data scientists to scare us? Is it really going to change the world? Or ruin it?

Here are some interesting things to know about Big Data –

What is Big Data?

First of all, what is Big Data? In it’s purest form, Big Data is used to describe the massive volume of both structured and unstructured data that is so large it is difficult to process using traditional techniques. So Big Data is just what it sounds like – a whole lot of data.

The concept of Big Data is a relatively new one and it represents both the increasing amount and the varied types of data that is now being collected. Proponents of Big Data often refer to this as the “Datification” of the world. As more and more of the world’s information moves online and becomes digitized, it means that analysts can start to use it as data. Things like social media, online books, music, videos and the increased amount of sensors have all added to the astounding increase in the amount of data that has become available for analysis.

Everything you do online is now stored and tracked as data. Reading a book on your Kindle generates data about what you’re reading when you read it, how fast you read it and so on. Similarly, listening to music generates data about what you’re listening to, when how often and in what order. Your smartphone is constantly uploading data about where you are, how fast you’re moving and what apps you’re using.

What’s also important to keep in mind is that Big Data isn’t just about the amount of data we’re generating, it’s also about all the different types of data (text, video, search logs, sensor logs, customer transactions, etc.). In fact, Big Data has some important characteristics that are known in the industry as the 8 V’s:

Based on the incredible amount, speed, variety and unstructuredness of the data we are now generating and storing, it’s no surprise that it quickly became unmanageable using traditional storing and analysis methods. This is where the term Big Data becomes confusing, because it is often used to refer to the new technologies, tools and processes that have sprung up to accommodate this vast amount of data.

Why has it become so Popular?

Big Data’s recent popularity has been due in large part to new advances in technology and infrastructure that allow for the processing, storing and analysis of so much data. Computing power has increased considerably in the past five years while at the same time dropping in price – making it more accessible to small and midsize companies. In the same vein, the infrastructure and tools for large-scale data analysis has gotten more powerful, less expensive and easier to use.

As the technology has gotten more powerful and less expensive, numerous companies have emerged to take advantage of it by creating products and services that help businesses to take advantage of all Big Data has to offer.  According to Inc, in 2012 the Big Data industry was worth $3.2 billion and growing quickly. They went on to say that “Total [Big Data] industry revenue is expected to reach nearly $17 billion by 2015, growing about seven times faster than the overall IT market.

Businesses have also started taking notice of the Big Data trend. In a recent survey, “Eighty-seven percent of enterprises believe big data analytics will redefine the competitive landscape of their industries within the next three years.”

Why Should Businesses Care?

Data has always been used by businesses to gain insights through analysis. The emergence of Big Data means that they can now do this on an even greater scale, taking into account more and more factors. By analyzing greater volumes from a more varied set of data, businesses can derive new insights with a greater degree of accuracy. This directly contributes to improved performance and decision making within an organization.

Big Data is fast becoming a crucial way for companies to outperform their peers. Good data analysis can highlight new growth opportunities, identify and even predict market trends, be used for competitor analysis, generate new leads and much more. Learning to use this data effectively will give businesses greater transparency into their operations, better predictions, faster sales and bigger profits.

How can I access Big Data?

Big Data is available in an endless number of places and it’s only increasing as time goes on. A simple Google search will enable you to find a data repository for just about everything. A lot of people aren’t aware of just how much data is already available for access and analysis.

How you can access and utilize this data can be split into six parts:-

Data Extraction

Before anything happens, some data is needed. This can be gained in a number of ways, normally via an API call to a company’s web service.

Data Storage

The main difficulty with Big Data is managing how it will be stored. It all depends on the budget and expertise of the individual responsible for setting up the data storage as most providers will require some programming knowledge to implement. A good provider should allow you a safe, straightforward place to store and query your data.

Data Cleaning

Like it or not, datasets come in all shapes and sizes. Before you can even think about how the data will be stored, you need to make sure it is in a clean and acceptable format.

Data Mining

Data mining is the process of discovering insights within a database. The aim of this is to provide predictions and make decisions based on the data currently held.

Data Analysis

Once all the data has been collected it needs to be analyzed to look for interesting patterns and trends. A good data analyst will spot something out of the ordinary or something that hasn’t been reported by anyone else.

Data Visualisation

Perhaps the most important is the visualization of the data. This is the part that takes all the work done prior and outputs a visualization that ideally anyone can understand. This can be done using programming languages such as Plot.ly and d3.js or software such as Tableau.

Are there careers related to Big Data?

With the growing access to Big Data, it should come as no surprise that the volume of careers related is on the rise as well. According to the Data Motion, a Big Data Engineer would earn an average salary of $150,000 a year.

Is it a growing industry?

The general interest and access to Big Data is on the rise. This Google Trends chart shows the increase in popularity of the search term ‘Big Data’ between 2004 and the present day.

According to IDC, “Worldwide revenues for big data and business analytics (BDA) will reach $150.8 billion in 2017, an increase of 12.4 percent over 2016”. The company goes onto estimate that by 2020, big data revenues could top $210 billion.

How do I learn more?

Big Data is a broad subject, so learning it all requires knowledge of several areas. Someone looking to work in the field would need an array of certain skills, including one or more of the following:

You can learn all courses related to Big Data and that too in vernacular language online also. Some sites like Unanth is providing skilled based video courses like –

Learn By Example: Hadoop, MapReduce for Big Data problems , Taming Big Data with Apache Spark and Python – Hands On!!