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Presented By:
Ankita Mishra (GM16016)
Archana Pathak (GM16018)
Anuja Agarwal(GM16014)
Anil Rana(GM16012)
Ashish Kr. Srivas...
WHAT IS BIG DATA?
Big Data is a collection of data sets that are large and complex in
nature.
OR
The data which is large i...
SOURCES OF BIG DATA
 Social Networking: Facebook, Twitter, Instagram, Google +
etc.
 Sensors: Used in Aircraft, Cars, In...
CHARACTERISTICS OF BIG DATA
There are three characteristics of Big Data:
3 V’s
1. VOLUME- Data in Tera Byte, Zeta Byte, Pe...
Big Data...What it Means to You - YouTube.MP4
Source:-
SAS Thailand
Facts And Figures Related To Big Data
IT FOR MANAGERS 5
WHAT IS ANALYTICS ?
It is a process to take the data then apply some
mathematical and statistical algorithm or tool to bui...
TYPES OF ANALYTICS
1. DESCRIPTIVE- What happened ?
2. DIAGNOSTIC- Why did it happen?
3. PREDICTIVE- What is likely to happ...
Tools Of Analytics
Most used statistical programing tools :
IBM SPSS
SAS
Sata
R (Open Source)
MATLAB
Rest of the tool...
BIG DATAANALYTICS
When we analyze Big Data then that analytics is called Big Data
Analytics, basically it is the process o...
Big Data Analytics Tool And Technology
HADOOP- It is a Open Source Framework where we can
analyze the data cheaper and fas...
Benefits Of Hadoop
Computing Power : Its distributed computing model quickly processes Big Data.
The more computing notes ...
High Scale Computing Platform for Big Data Analytics
HDFS
Structured
data in
RDMS
Sqoop
Unstructured
data
Pig
Online
data
...
Big Data Analytics In Banks
Data creation
Collection of data
Banks own HDFS for storing
Fetching of data
Model formation
K...
IT FOR MANAGERS
14
Benefits Of Big Data Analytics in Banking Sector
Fraud Detection: It help Bank to detect, prevent and eliminate
internal ...
Customer Churn Analysis: It help Banks to retain their
customers by analyzing their behavior and identifying patterns
tha...
Conclusion
Banks are creating large amount of data day by day.
Their creation speed is much faster than our
processor’s sp...
Reference:-
1. Introduction to big data analytics: A Webinar by WizIq Education Online.
2. Big Data analytics using Hadoop...
IT FOR MANAGERS 19
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Big data analytics in banking sector

  1. 1. Presented By: Ankita Mishra (GM16016) Archana Pathak (GM16018) Anuja Agarwal(GM16014) Anil Rana(GM16012) Ashish Kr. Srivastava(16020) Guidence By:- Prof. Hemlata Bhatt PG05 Credit-03
  2. 2. WHAT IS BIG DATA? Big Data is a collection of data sets that are large and complex in nature. OR The data which is large in volume and difficult to process and store. Big data can be analyzed for insights that lead to better decisions and strategic business moves. Big Data basically constitute both semi-structured and unstructured data that grows large so fast that they are not manageable by traditional relational data base system or conventional tools. IT FOR MANAGERS 2
  3. 3. SOURCES OF BIG DATA  Social Networking: Facebook, Twitter, Instagram, Google + etc.  Sensors: Used in Aircraft, Cars, Industrial Machines, Space Technology, CCTV Footage etc.  Data Created From Transportation Services: Aviation, Railways, Shipping etc.  Online Shopping Portal: Amazon, Flipkart, Snapdeal, Alibaba etc.  Mobile Applications: What’s App, Google Hangout, Hike etc.  Data created by Different Firms: Education Institute, Banks, Hospital, Software Companies etc. IT FOR MANAGERS 3
  4. 4. CHARACTERISTICS OF BIG DATA There are three characteristics of Big Data: 3 V’s 1. VOLUME- Data in Tera Byte, Zeta Byte, Peta Byte. 2. VELOCITY- Data is growing very fast that gives challenges in storing and processing. 3. VARIETY- I. Unstructured data- Videos, Audio, Images, Texts. II. Semi-structured data- Log Files. IT FOR MANAGERS 4
  5. 5. Big Data...What it Means to You - YouTube.MP4 Source:- SAS Thailand Facts And Figures Related To Big Data IT FOR MANAGERS 5
  6. 6. WHAT IS ANALYTICS ? It is a process to take the data then apply some mathematical and statistical algorithm or tool to build some model. This model will be predictive and exploratory which is having information that allow us to get insights and insights allow us to take action. USE OF DATA STATISTICAL ANALYSIS MODEL GAIN INSIGHTS ACT ON COMPLEX ISSUES IT FOR MANAGERS 6
  7. 7. TYPES OF ANALYTICS 1. DESCRIPTIVE- What happened ? 2. DIAGNOSTIC- Why did it happen? 3. PREDICTIVE- What is likely to happen? 4. PRESCRIPTIVE- What should i do about it? Level Of Impact Skilllevelpresent 1 2 3 4 IT FOR MANAGERS 7
  8. 8. Tools Of Analytics Most used statistical programing tools : IBM SPSS SAS Sata R (Open Source) MATLAB Rest of the tools except ‘R’ are commercial and very expensive. R and MATLAB has most comprehensive support of statistical functions. R is most popular among Yahoo ,Google etc. IT FOR MANAGERS 8
  9. 9. BIG DATAANALYTICS When we analyze Big Data then that analytics is called Big Data Analytics, basically it is the process of collecting , organizing and analyzing data to discover pattern and other useful information that allow us to take proper action. ANALYTICS CHALLENGES WITH BIG DATA • Traditional RDBMS fail to use Big Data. • Big Data can not fit in the single computer. • Processing of Big Data in single computer will take a lot of time. • Through traditional analytics it would be costly to analyze Big Data. • Scaling of Big Data through traditional RDBMS is expensive. IT FOR MANAGERS 9
  10. 10. Big Data Analytics Tool And Technology HADOOP- It is a Open Source Framework where we can analyze the data cheaper and faster with the cluster of commodity hardware. It provide massive storage for any kind of data with enormous processing power . HDFS (Hadoop Distributed File System): The java based scalable that stores data across multiple machines without prior organization. Map Reduce: It is a software programing model for processing large sets of data in parallel. Hadoop= HDFS + Map Reduce IT FOR MANAGERS10
  11. 11. Benefits Of Hadoop Computing Power : Its distributed computing model quickly processes Big Data. The more computing notes we use the more processing power we have. Flexibility: We can store as much data as we want and decide how to use it later. That include unstructured data like text, images and videos. Low Cost: It is open source framework id free and uses commodity hardware to store large quantity of data. Scalability: We can easily grow our system simply by adding more nodes. IT FOR MANAGERS 11
  12. 12. High Scale Computing Platform for Big Data Analytics HDFS Structured data in RDMS Sqoop Unstructured data Pig Online data stream Real time learning system System/ web logs Flume Internal data transformation Pig R Hadoop Hive Internal data transformation IT FOR MANAGERS 12
  13. 13. Big Data Analytics In Banks Data creation Collection of data Banks own HDFS for storing Fetching of data Model formation Knowing the insights of model Taking action IT FOR MANAGERS 13
  14. 14. IT FOR MANAGERS 14
  15. 15. Benefits Of Big Data Analytics in Banking Sector Fraud Detection: It help Bank to detect, prevent and eliminate internal and external fraud as well as reduce the associated cost. Risk Management: Bank anlyse transaction data to determine risk and exposures based on simulated market behavior, scoring customer and potential clients. Contacts Center Efficiency Optimization: It help Banks to resolve problems of customers quickly by allowing Banks to anticipate customers need ahead of time. Customer Segmentation For Optimize Offers: It provides a way to understand customers’ needs at a granular level so that Banks can deliver targeted offers more effectively. IT FOR MANAGERS 15
  16. 16. Customer Churn Analysis: It help Banks to retain their customers by analyzing their behavior and identifying patterns that lead to a customer abandonment. Sentiment Analyst: This tool help the Bank to analyse social media to monitor user sentiment toward a firm, brand or product. Customer Experience Analytics: It can provide better insight and understanding, allowing Banks to match offers to a customers’ needs. Continued… IT FOR MANAGERS 16
  17. 17. Conclusion Banks are creating large amount of data day by day. Their creation speed is much faster than our processor’s speed. So the handling of bulk amount of data is difficult for our system. But storing and processing of Big Data is faster when it stored in distributed manner. ‘Hadoop’ framework provides such kind of network where Big Data distributed among different systems. By adding more nodes data can be stored in different location. If any node fails then there is no loss of data. By the use of big data banks run more profitably. IT FOR MANAGERS 17
  18. 18. Reference:- 1. Introduction to big data analytics: A Webinar by WizIq Education Online. 2. Big Data analytics using Hadoop: A Lecture by Durga Software Solutions. 3. Book Followed: Information Technology for Management by Efraim Turban, Linda Volonino. 4. Website Followed: www.flysas.com www.smartdatacollective.com IT FOR MANAGERS 18
  19. 19. IT FOR MANAGERS 19
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