This document discusses big data analytics. It covers the four V's of big data (volume, variety, velocity, and veracity), drivers of big data, an introduction to big data analytics including what it is and key technologies used, benefits including improved customer service and decision making, and applications in various industries like healthcare, manufacturing, and banking. The learning objectives are to understand the four V's of big data, drivers of big data, what big data analytics is, and its benefits and applications.

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