Big data- it’s big, trending and the future of how world interprets and analyze. It is changing the way of how world uses raw data to transform into meaningful business information. Learn what big data has to offer along with standards and paradigms.

1. Big Data
What? Why? & How?
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2. What is Big Data?
Big Data can be described as huge chunks of structured
and unstructured data that is hard to interpret. It’s
simply a mechanism to gain insights and meaningful
data values from large data sets, which ultimately leads
to better understanding of business progress and aids
in taking better decisions.

3. History of Big Data
The process of transforming raw data into meaningful
information has been followed since ages. In early
2000s, a proficient analyst Doug Laney explained the
growing nature of data as the three Vs, Volume, Velocity
and Variety.

4.  Volume. The quantity of the data produced and
stored.
 Velocity. In this context, the rate at which the data is
being produced and processed to meet different
business challenges.
 Variety. The type of the data produced.
History of Big Data

5. The data has grown exponentially in the last few years
making it difficult to manage and analyze, which gave
birth to the term
‘Big Data’.
History of Big Data

6. The Four Additional V’s
While devising a Big Data strategy there are some
additional parameters (some additional V’s), which require
your critical eye. Here, we list the same.
Veracity Variability Visualization Value

7. The Four Additional V’s
 Veracity. You need to be accountable for the data
being produced, stored and analyzed by the analysis
team for organization’s growth, prosperity or hardship.
Poor Accuracy
Good Accuracy

8. The Four Additional V’s
 Variability. It is the core in performing analyzes.
Algorithms should be good enough to comprehend
the entered data and produce meaningful insights.
0
1
2
3
4
0 0.5 1 1.5 2 2.5 3
More Variability
Less Variability

9. The Four Additional V’s
 Visualization. Huge chunks of
complex data rendered into the
simplest form with plenty of
variables to work with. Not the
regular graphs or pies but a
graphical representation of
compound data.
A
B
C
0
2
4
6
S1 S2 S3 S4
A B C

10. The Four Additional V’s
 Value. Big data churns the existing raw data sets
into useful information that adds value to the
business in the process of decision making and
future strategy moves.

11. Importance of Big Data
No matter how much data is stored inside the data
banks unless it’s managed, sorted and analyzed to
meaningful information. This is where Big Data comes
into picture helping organizations to achieve the
following,

12. Importance of Big Data
The benefits come in a flurry especially when Big Data
combines with analytics. Here are some of the benefits
you can reap after sowing the seeds of Big Data
analytics.
Real-Time Bug Identification Improved Customer Analysis
Effective Risk Management Reduction in Frauds

13. How It Works
 Streaming Data
 Social Media Channels
 Publicly Available Sources
The benefits come in a flurry especially when Big Data
combines with analytics. Here are some of the benefits
you can reap after sowing the seeds of Big Data
analytics.

14. How It Works
 How to store and manage it?
 How much of it to analyze?
 How to use any insights you uncover?
Once the data sources are identified, data gets
processed to yield consequential results that actually
makes sense. This includes:

15. What should be your last move?
Consider technologies or tools for Big Data Analytics
keeping the following factors in mind:
 Affordable yet effective
 Massive storage capacity
 Fast processors
 Parallel processing,
clustering, MPP, virtualization
 High connectivity and high
throughputs
 Cloud computing
 Flexible resource allocation
arrangements
 Popular tools like Hadoop

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