The document discusses big data analytics. It begins with an introduction that defines big data as extremely large data sets that cannot be processed efficiently using traditional data management tools. It then provides a brief history, noting that the first traces of big data occurred in the 1600s. The document outlines the role of big data analytics in helping companies make more informed decisions. It also describes big data architectures, applications, advantages like improved science and healthcare, and disadvantages such as high storage costs and privacy issues. Finally, it concludes that big data is transformative for organizations seeking strategic insights and better customer experiences.

1. Submitted To: Submitted By:
Prof. Brajesh Kumar Kapil Kumar

2. Overview
 Introduction
 History
 Role of Big Data Analytics
 Big Data Analytics Architecture
 Big Data Analytics Application
 Advantages
 Disadvantages
 Conclusion

3. Introduction
Big data is a collection of data that is
huge in volume, yet growing
exponentially with time. It is a data
with so large size and complexity that
none of traditional data management
tools can store it or process it
efficiently. Big data is also a data but
with huge size.

4. History
The first trace of big data is seen
way back in 1663 when John Graunt
dealt with overwhelming amounts
of information while he studied the
bubonic plague, which was haunting
Europe at the time. Graunt was the
first-ever person to use statistical data
analysis.

5. Role of Big Data Analytics
 The primary goal of Big Data Analysis is to
help companies make more informed
business decisions by enabling data
scientists, predictive modelers, and other
analytics professionals to analyze large
volumes of transactional data.
 It include web server logs and Internet click-
stream data, social media content and social
network activity reports.

6. Big Data Architecture

7. Architecture Info
 Big data architecture is the foundation
for big data analytics. It is the overarching
system used to manage large amounts of
data so that it can be analyzed for business
purposes, steer data analytics, and provide
an environment in which big data analytics
tools can extract vital business information
from otherwise ambiguous data.

8. Big Data Analytics Application
 Energy Exploration
 Financial Market Analysis
 Fraud Detection
 Health Related Search
 Environmental Protection
 Web Search or Internet Web
 Information Security

10. Advantages
 It helps in improving science and research.
 It improves healthcare and public health with
availability of record of patients.
 It helps in financial trading sports, polling security /
law enforcement etc.
 Any one can access vast information via surveys and
deliver answer of any query.
 Every second additions are made.
 It helps in optimizing business processes.

11. Disadvantages
 Traditional storage can cost lot of money to store big
data
 Lots of big data is unstructured.
 Big data analysis violates principles of privacy.
 It can be used for manipulation of customer records.
 It may increase social stratification.
 Big data analysis is not useful in short run. It needs to
be analyzed for longer duration to leverage its benefits.
 Big data analysis violates the principles of privacy.

12. Conclusion
 Big Data is a game changer. Many
organizations are using more analytics to
drive strategic actions and offer a better
customer experience. A slight change in the
efficiency or smallest savings can lead to a
huge profit, which is why most
organizations are m.oving towards big data

13. Thank You