1. https://www.esds.co.in
ESDS Software Solution
Pvt. Ltd.
Y o u r C l o u d P a r t n e r

3. “Big data is at the foundation of all of the
megatrends that are happening today,
from social to mobile to the cloud to
gaming”

4. Introducing Big Data
• Big Data not only refers to the data itself, but also the set of
technologies that capture, store, manage and analyse large and
variable collections of data in order to solve the complex problems
• Big Data solutions have enabled the organizations to effectively
manage the large data volumes thereby reducing costs
• The definition of Big Data depends on whether the data can be
processed and examined in a time that has met a particular
business’ requirements

5. 8%
4%
3%
3%
3%
2%
2%
2%
2%
2%
1%68%
IBM Splunk Dell Oracle AWS Accenture Palantir SAP HPE Microsoft Cloudera Others
Vendor-wise Market Share (as per 2017)

6. 4 V’s of Big Data
• The 4 V’s of Big Data are a set of specific attributes that define
Big Data
• The 4 V’s of Big Data includes the following-
i. Volume
ii. Variety
iii. Veracity
iv. Velocity

7. Explaining the 4 V’s
1. Volume:
Big Data implies large volumes of data. This data is now
generated by machines, networks and human interactions
on social media and the volume of data that has to be
analysed is large
2. Variety:
It refers to the sources and types of data- both structured
and unstructured. Generally, the variety of an unstructured
data creates problems for storage, mining and analysing
data

8. Explaining the 4 V’s
(contd…)
3. Veracity:
Big Data veracity refers to the biases, noise and abnormality
that is present in the data. It could also be the data being
stored and mined meaningful to the problem that needs to
be analysed
4. Velocity
The Big Data velocity refers to the pace at which the data
flows in from the various sources such as business processes,
machines, networks and human interactions with social
media, mobile devices etc. The flow of data is massive and
continuous

9. Interesting Stats on Big Data
1. It is predicted that by 2020, the amount of data will rise to 40
zettabytes
2. 90% of all the data has been created in the last two years
3. In the year 2012, only 0.5% of data was analysed
4. Today, Internet is responsible for generating about 2.5 quintillion bytes
of data every day
5. About 97.2% of the organizations are heavily investing towards Big
Data and AI

10. Global Big Data Market
• The global Big Data Market has accounted for an increase from $42
billion in the year 2018
• It is expected to reach $103 billion in the year 2027 at a CAGR of 10.48%
• The Big Data market is growing at a CAGR of 10.48%
• The combined market of Big Data and Hadoop is projected to grow from
$17.1 Bn to $99.31 Bn by 2022 with a CAGR of 28.5%
• The Big Data applications and analytics is expected to grow from $5.3 Bn
in 2018 to $19.4 Bn in 2026 with a CAGR of 15.49%

13. Integration With Other Technologies
• Today, there are devices that “talk” to each other over a connected
network and share and generate the data fed by the user
• There are algorithms learning patterns to process the information
from the generated data
• The simplest example of Internet of Things or IoT can be the smart
TV present in a home, connected to the user’s home network and
generating data based on the user viewing patterns, interests and
more
• The social media applications installed, are also considering the
personal tastes and preferences and cumulatively working on the
user persona for better delivery of the online content and
streaming options

14. Year
Professional
Services
Apps and
Analytics
Storag
e
Comput
e
SQL
Data
Management
Networkin
g
NoSQL Hadoop
2011 3.19 0.57 1.2 1.67 0.69 0.11 0.16 0.02 0.01
2012 5.06 1.07 1.92 2.52 0.97 0.29 0.25 0.1 0.06
2013 7.12 1.83 3.48 4.15 1.67 0.47 0.56 0.19 0.13
2014 10.46 2.25 4.81 5.62 2.15 0.97 0.68 0.23 0.19
2015 12.56 2.84 5.9 6.46 2.7 1.23 0.94 0.4 0.27
2016 13.92 3.41 6.82 7.18 3.16 1.45 1.16 0.55 0.33
2017 15.27 4.22 7.91 8.02 3.71 1.72 1.42 0.72 0.41
2018 16.5 5.31 9.11 8.94 4.3 2.01 1.71 0.91 0.5
2019* 17.45 6.69 10.29 9.85 4.9 2.3 1.99 1.09 0.59
2020* 18.38 8.33 11.36 10.68 5.43 2.56 2.24 1.26 0.66
2021* 19.08 10.2 12.25 11.38 5.88 2.77 2.45 1.4 0.72
2022* 19.6 12.19 12.96 11.95 6.23 2.94 2.61 1.51 0.77
2023* 20.08 14.2 13.5 12.39 6.5 3.07 2.74 1.58 0.81
2024* 20.52 16.13 13.93 12.76 6.7 3.17 2.83 1.64 0.84
2025* 20.94 17.88 14.29 13.07 6.88 3.26 2.91 1.69 0.86
2026* 21.37 19.41 14.61 13.36 7.04 3.33 2.97 1.73 0.88

15. 0
10
20
30
40
50
60
70
80
90
2011 2012 2013 2014 2015* 2016* 2017* 2018* 2019* 2020* 2021* 2022* 2023* 2024* 2025* 2026*
Growth by Product
Professional Services Apps and Analytics Storage Compute SQL Data Management Networking NoSQL Hadoop

16. Future Trends
1. Dark Data:
Dark data simply refers to the data that is generated from the non-digital sources and digital data
has always been undermined by the value that it holds. The data sets are usually untapped,
unstructured and untagged and may also be referred as dusty data. In future, such kind of data sets
are about come into limelight and will revolutionize this industry
2. Privacy:
Privacy continues to be one of the major shortcomings in today’s time. We, users of data barely
have any idea regarding how the data generated by us, is going to be used and shared amongst
the firms. New policies have and will be introduced in context of data consumption and analytics, by
paving a way for a safer ecosystem where consumers generate data
3. Data on the Rise:
The Big Data Hadoop future is always on the rise and the amount of data generated per day will
also continue to grow. In today’s time, the amount of data generated per day is 2.3 trillion gigabytes
of data and will continue to rise ever. The presence of smartwatches, smart TVs and smart wearables
present in the market are continuously collecting user data

17. Thank You
https://www.esds.co.in