Posted in Big Data Data Science

Breaking Down Big Data

Big Data is big news these days. There is continuous streaming of Data, flooding each business on a given day. This Data consists of information that is collected from a huge number of sources, such as, Production, Market Prices, Finance, Material Flow, Supply Chain, Security Data and so on. These huge masses of Data may be Structured and Unstructured. But it is not the quantity of Data that directly interests the Data Scientists or the organizations that generate and collect them. It is what this Data can yield which may lead to better insights and strategic decisions for the whole organization. What follows next is therefore a brief Introduction To Big Data, its workings and its capabilities.

A Little History

Big Data as a fore-runner of a new branch of knowledge called Data Science, first gained currency in the early 2000s. In 2001, Industry Analyst Doug Laney first coined the term ‘Big Data’ and the ‘3Vs’ of Volume, Velocity and Variety. These 3Vs now form the core definition of Big Data.

How Does it Work?

Big Data is said to consist of the 3Vs standing for Volume, Velocity and Variety. Let us discuss each V first, as follows:

  • Volume: Data is streamed from various sources and storage of this mass of information had become a major problem. Data is collected, by the organizations, from Industrial Equipment, Videos, Social Media, Business Transactions, Smart IoT (Internet of Things) Devices and many more. But modern storage that is at once cheap and capable of absorbing vast quantities of Data, like, Data Lakes and Hadoop, have made such storage a possibility at last.
  • Velocity: The Velocity of Data streaming has suddenly entered a phase of rapid upsurge, riding on the back of the IoT. These speeds were truly un-thought of previously. With Censors, Smart Meters and RFID Tags pushing the boundaries of collecting masses of Data in real time, the need for rapid collection of Data is foremost.
  • Variety: Data these days stream in with a vast Variety of formats. Traditional Data Bases providing Structured Data are more easily absorbed, but Unstructured Data, such as, Ticker Tape Data, Stock Figures, Audios, Videos, Emails and Financial Transactions create a mixed bag that needs special storage.

Two other Vs are also selected as important for Big Data. These are:

  • Variability: The Data itself is often changeable and sometimes seasonal. In order to predict Trending, on a daily basis, Social Media and other such sources of Data generation need to be considered on Variable platform.
  • Veracity: This is an important feature which evaluates the quality of the Data. In order to confirm the Veracity or Truth about the quality of Data received and it usefulness, businesses must be able to figure out relationships and linkages of Data on a mass scale. Otherwise overall control of Big Data may soon be lost.

Impact and Importance

In Big Data, the quantity of Data collected is less important than how the Big Data is handled and what it is used for. Analysis of Data can enable the Data Analyst to guide organizations to produce, firstly, Cost Reductions and Time Reductions. New products can be developed and optimized. Decision making thus becomes smart. Powerful Analytical Tools used by Data Scientists can yield insights on the following:

  • Root causes of failures and defects can be determined in close to real time.
  • The entire Risk Portfolio can be re-calculated in a matter of minutes.
  • Fraudulent functioning can be detected before the organization is affected, or at its early stages.

The Future of Big Data

The future belongs to Big Data and DI (Data Integration). With so many different types and sources of Data, with operational time varying from Real Time to Streaming Time, Data Integration uses Data Science to extract meaningful insights by mining Big Data. This Introduction To Big Data is only a brief glimpse of how our future is being built by Big Data and Analytical Strategy. A future can be conceived where Cloud, Containers and On-demand Computation Power can create a situation, where organizations can depend fully on the reliability of the Big Data-driven decisions across lines of business. Big Data is our Business’s staircase to a Big Future.