The Beginner’s Guide to Big Data

“In God we trust, all others must bring data” – William Edwards Deming.

In the world of business today, every facet comes down to data. Investors need hard facts before investing, customers need data on product safety before consuming, companies need data on consumption patterns before product launches. Data can be a dummy’s guide to business if analysed correctly.

Unlike traditional data collection resources, tools being used currently are constantly collecting huge amounts of data that comes in various types and complexities. The task is on how to simplify this data into a usable form to improve business, healthcare, and life in general. Big data comes into the picture, no traditional data analysis system is sophisticated enough to analyze all this complex data and provide relevant results instantly.

Here are 5 things you should know as a beginners guide to Big data

  1. What are the basic types of Big Data

Big Data is majorly categorized into 3 segments

  1. Structured Data – Anything that can be analyzed in a way that is simple, can be stored, can be processed using relevant tools and can be put into a certain format is basically structured data, example: customer records in USA online casinos. One can just look at various ways of analyzing data in order to meet maximum benefits out of it.
  2. Unstructured data

This type of data is more complex, it cannot all be converted into one single format. They will be available across various formats and processes that may not be tangible. For instance the results you get every time you Google search something.

  1. Semi-structured data :

This is when the data can be analyzed in some way, it has some organizational possibility despite not being in a singular format.  This semi-structured data is more flexible than the structured data but not as intangible as the unstructured data.

What are the Big V’s of the Big Data?

Every time you hear the word big data, you will most likely hear of the V’s of Big Data

  1. Volume

Big Data is voluminous. Any data that can be qualified as Big Data needs to have copious amounts of data on it waiting to be analyzed. The memory of such big data files usually ranges in Terabytes or petabytes.

  1. Velocity

This determines the momentum with which data is being constantly generating in the system. Usually, with Big Data, there is a staggeringly huge amount of data that is being constantly processed and even faster processing time.

  1. Variety

Variety is the basis of everything. The world is too colorful and variable now to be stuck to a single format for making any business work. If your data has a blend of various formats such as image file, pdf file, audio, numbers can all be classified as the variety of Big Data?

In terms of Big Data, Robotics, Medicine, Research and development, Meteorology are all promising application areas.

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