Big Data Analytics In Banking Sector

Presented By:Ankita Mishra (GM16016)Archana Pathak (GM16018)Anuja Agarwal(GM16014)Anil Rana(GM16012)Ashish Kr. Srivastava(16020)

Guidence By:-Prof. Hemlata Bhatt

PG05Credit-03

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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.

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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.

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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.

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Big Data...What it Means to You - YouTube.MP4

Source:-SAS Thailand

Facts And Figures Related To Big Data

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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 INSIGHTSACT ON COMPLEX ISSUES

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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

Skill

leve

l pre

sent

1

2

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Tools Of AnalyticsMost used statistical programing tools :IBM SPSS SASSataR (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.

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BIG DATA ANALYTICS

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.

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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

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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

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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

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Big Data Analytics In BanksData creation

Collection of data

Banks own HDFS for storing

Fetching of data

Model formation

Knowing the insights of model

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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.

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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…

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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.

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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

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THANK YOU !