Big Data Real Picture

Today I will present a real-world picture and scenario of big data and all the related supportive contents along with it.

Hello geeks!

Today I will present a real-world picture and scenario of big data and all the related supportive contents along with it, like:

  • What it is
  • How it is created
  • How it's going to change the world
  • What the effects are
  • What the necessity is
  • Many more things

What BIG-DATA is

In simple words, we can define big data as a huge/massive amount or collection of data that can be nearly any-type, any-size and variety.

Big Data | Estimated Size

According to IBM:
“Around 2.5 quintillion bytes of data is created every day.”

Big Data | Types

There are generally 2 types of data that currently exist:



Structured Data

(Data that resides in a fixed field within a record or file is called structured data.)

Unstructured Data

(It is a type of data that includes text, audio, videos, photos, web pages, documents, email messages, word processing and so on.)

According to TCS:
“In the current world almost 51% of data is structured data. 27% data is unstructured data while the rest, 21%, is called semi-structured data.”

Big Data | Generated Jobs

According to GARTNER:
“There are as much as 4.4 million IT jobs that will be created globally to support big data by 2015. The technology will generate 1.9 million IT jobs in the USA alone and all the rest will be divided in the whole world.”

Big Data | Talent Required

According to McKinsey:
“The USA alone could face a talent shortage of around 140K – 190K people by 2018. Further this shortage can get exceeded. According to their estimation the shortage can reach up to 1.5 million; that will include managers, analysts and so on to make effective decisions on big data. ”

Big Data | Re-Planning

According to TEK Systems:
“Around 81% of IT leaders and 77% of IT professionals believe there is a considerable shortage of talent that could make best use of their organization's data assets.”

Big Data | Utilization/Requirement

According to TEK Systems:
“Around 66% of IT leaders and 53% of IT professionals believe their organizations need to build new platforms and structures to make use of their vast mammoth data management needs, thereby getting rid of the current systems.”

Big Data | Business Values

Tata Consultancy Services has highlighted 3 major challenges for companies:

  • Making business share information across organizational lines
  • Dealing with 3 V's of big data



  • Determining which data could be best used under different conditions.

Big Data | Quality

According to TEK Systems:
“Around 57% of IT leaders and 52% of IT professionals claim that they don't know always who is the owner of data, meaning quality more or less lies on the back burner. Ensuring the accuracy and quality of data will be critical in the times to come in an ever expanding universe of big data. ”

Big Data | Data Management

According to COMPTIA:
“Nearly eight in 10 data executives believe that harnessing all of their enterprise data would result in a stronger business.”

Big Data | Business Driver

According to EMA and 9Sight Consulting: the 3 big data business drivers include:

Speeding time for operational or analytical workloads
(around 39%)
Increasing competitive advantage with flexibility of data used in business solutions
(around 34%)
Business requirements for higher levels of advanced analytics
(around 31%)

Big Data | Implementation

According to EMA and 9Sight Consulting:
“Big data implementations in production rose from 27% in 2012 to 34.3% in 2013.”



Big Data | Tools

According to Giga Space:
“Nearly 80% people in IT are either using or planning to use dedicated big data tools to manage massive amounts of data in their organizations.”

Big Data | Expenditures

According to TCS:

“Around 15% of the companies surveyed had spent at least $100 million each on big data in 2012, while 7% had invested at least $500 millions.”

Big Data | Expenditures based on Sectors

According to TCS:

“Travel related, high tech, share and banking industries have been the biggest spenders while industries related to life science, retails and energy have spent the least.”