4 V's of BIG Data

2. Faculty Name:Namrata
Sharma/Arjun S. Parihar
Year/Branch:3rd/CSE
Subject Code:CS-503(A)
Subject Name:Data Analytics

3.  Four V’s of Big Data
 Drivers of Big Data
 Introduction to Big Data Analytics
 Big Data Analytics Application
Learning Objectives
• In this session you will learn about:

4. Four V’s of Big Data

5. Volume
-Size of data plays a very crucial role
- In determining value out of data
- Business data is enormous
- Volume is one characteristic which needs to be
considered
- While dealing with Big Data.
Four V’s of Big Data

6. Variety
-Heterogeneous sources and the nature of data.
-Both structured and unstructured.
-During earlier days, spreadsheets and databases were
the only sources of data .
-Nowadays, data in the form of emails, photos, videos,
monitoring devices, PDFs, audio, etc.
-Data poses certain issues for storage, mining and
analyzing data.
Four V’s of Big Data

7. Velocity
-The term 'velocity' refers to the speed of generation of
data.
-How fast the data is generated and processed to meet the
demands, determines real potential in the data.
-Big Data Velocity deals with the speed at which data flows
in from sources
-Like business processes, application logs, networks, and
social media sites, sensors, Mobile devices, etc.
-The flow of data is massive and continuous.
Four V’s of Big Data

8. Veracity
-Veracity refers to an uncertainty of data available
-Harder for the companies to react quickly and make
appropriate solutions.
-Accuracy is the major issue.
-Need strategy to organise data in porper format.
-Avoid mixing to related and unrelated data .
-To make right decisions, the data must be clean, consistent
and consolidated.
Four V’s of Big Data

9. -Big Data is no longer just a buzzword.
-A recent IDC report predicts that the digital universe will be
44 times bigger in 2020 than it was in 2009
-Famous example Apple,Amazon,Facebook,netflix
Drivers of Big Data

10. Drivers of Big Data
Six main business drivers can be identified:
-The digitization of society;
-The plummeting of technology costs;
-Connectivity through cloud computing;
-Increased knowledge about data science;
-Social media applications;
-Internet-of-Things (IoT).

11. Introduction to Big Data Analytics

12. What is analytics ?
-Analytics is an encompassing and multidimensional field.
-It uses mathematics, statistics, predictive modeling
- Machine-learning techniques
-To find meaningful patterns and knowledge in recorded
data.
Introduction to Big Data Analytics

13. What is big data analytics?
- Process of collecting, organizing and analyzing a large
amount of data
-To uncover hidden pattern, correlation and other
meaningful insights.
- Helps an organization to understand the information
contained in their data
- Use it to provide new opportunities to improve their business
-In turn leads to more efficient operations, higher profits and
happier customers.
Introduction to Big Data Analytics

14. - What actually happened?
- How or why did it happen?
- What’s happening now?
- What is likely to happen next?
Answer the following types of questions:
Introduction to Big Data Analytics

15. Key Technologies behind Big data Analytics
-Hadoop-Open source framework
-Data Mining-discover patterns
-Text Mining-NLP,ML
-Predictive Analytics-Predict future outcome
Introduction to Big Data Analytics

16. -It improves customer services.
-It contains better operational efficiency.
-It has better decision making.
- It quickly identifies the risks of the products and services
Benefits of Big Data Processing

17. Benefits of Big Data
Example of e-commerce industry:
-Collect information about the items searched by the
customer.
-Information regarding their preferences.
-Information about the popularity of the products and
many other data.
Introduction to Big Data Analytics

18. Benefits of Big Data
-Organizations derive some patterns and provide the
best customer service like displaying the popular
products that are being sold.
-Show the products that are related to the products that a
customer bought.
-Provide secure money transitions and identify if there
are any fraudulent transactions being made.
-Forecast the demand for the products and many more.
Introduction to Big Data Analytics

19. Big data Analytics Application
-Healthcare
-Manufacturing
-Media and Entertainment
-IOT
-Government
-Banking Sector
-Education

20. Quick Review
-Characteristics of big data are four v’s
-Drivers of Big Data are digitization of Society, plummeting
of technology costs, Connectivity through cloud computing,
Increased knowledge about data science, Social media
applications, Internet-of-Things (IoT).
-Big data analytics is the process of collecting,organizing
and analyzing large amount of information to uncover
information contained in data
-The primary goal of big data applications is to help
companies to make more business by analyzing large data

21. Thank You