This document provides an overview of business intelligence and analytics (BIA). It discusses how BIA uses technologies and practices to analyze critical business data and provide insights to improve decision making. It also covers challenges like accessing diverse data and big data analytics. The stages of BIA include data warehousing, extraction, transformation and loading of data, analytics like descriptive, predictive and prescriptive analysis, and knowledge discovery techniques. BIA provides businesses insights from large and diverse data generated through applications to help in areas like marketing, finance, and human resources.

1. BUSINESS INTELLIGENCE AND
ANALYTICS
PRESENTED BY
RAJIV KUMAR V
13M510
CSED

2. CONTENTS
• INTRODUCTION
• BIG DATA
• CHALLENGES FACED BY BUSINESSES
• WHAT IS BIA?
• ANALYTICS
• STAGES IN BIA
• CONCLUSION
• REFERENCES

3. INTRODUCTION
• TECHNOLOGIES, SYSTEMS, PRACTICES
• ANALYZE CRITICAL BUSINESS DATA
• BETTER UNDERSTAND ITS BUSINESS AND MARKET
• PROVIDE BUSINESS MANAGERS AND ANALYSTS TO
CONDUCT APPROPRIATE ANALYSES
• IMPROVE BUSINESS DECISION MAKING

4. BIG DATA
• DEFINED AS WHAT FIRMS CANNOT HANDLE WITH
TYPICAL DATABASE SOFTWARE
• COMPUTING SYSTEMS TODAY ARE GENERATING OVER
15 PETABYTES OF NEW INFORMATION EVERY DAY
• OVERWHELMING AMOUNT OF SENSOR-GENERATED
DATA
• USER-GENERATED CONTENTS AVAILABLE FROM WEB,
SOCIAL MEDIA AND MOBILE
• HIGH DIMENSIONALITY
• COMPUTERIZED TRANSACTIONS
• DATA IS GETTING UBIQUITOUS AND CHEAP

5. BIG DATA[CONTD…]
• 80% OF THE DATA GENERATED EVERYDAY IS
TEXTUAL AND UNSTRUCTURED
• 3 VS OF DATA:
• VOLUME (FROM GIGABYTES TO PETABYTES),
• VELOCITY (FROM BATCH TO NEAR-TIME DATA AND
REAL-TIME STREAMS),
• VARIETY (FROM STRUCTURED RECORDS TO SEMI-STRUCTURED
AND UNSTRUCTURED TEXT
• HUGE VOLUMES OF DATA STRAINING OUR
TECHNICAL CAPACITY TO MANAGE IT

6. CHALLENGES FACED BY
BUSINESSES
• BIG DATA ANALYSIS REQUIRES NEW APPROACHES TO
OBTAIN INSIGHTS
• ACCESS TO DIVERSE AND DISPARATE DATA IS
DIFFICULT
• MANIPULATION AND TRANSFORMATION OF BIG
DATA
• DEVELOPING THE CAPABILITY TO UNDERSTAND AND
INTERPRET THE DATA

7. WHAT IS BIA?
• INTERDISCIPLINARY AREA THAT INTEGRATES
• DATA MANAGEMENT
• DATABASE SYSTEMS
• DATA WAREHOUSING
• DATA MINING
• NATURAL LANGUAGE PROCESSING (TEXT ANALYTICS
AND TEXT MINING. I.E. STATISTICAL, LINGUISTIC AND
STRUCTURAL TECHNIQUES FROM TEXTUAL SOURCES)
• NETWORK ANALYSIS/SOCIAL NETWORKING
• STATISTICAL ANALYSIS

8. BIA [CONTD...]
• ANALYZING TRENDS
• CREATING PREDICTIVE MODELS FOR
FORECASTING
• OPTIMIZING BUSINESS PROCESSES
• REPORTING DATA
• TURNING DATA INTO KNOWLEDGE AND
INTELLIGENCE

9. DATA WAREHOUSING

10. DATA CUBE

11. TEXT MINING

12. TEXT MINING[CONTD…]

13. SOCIAL NETWORK ANALYSIS

14. ANALYTICS
• MAIN CATEGORIES OF ANALYTICS:
• (1) DESCRIPTIVE :THE USE OF DATA TO FIND OUT WHAT
HAPPENED IN THE PAST;
• (2) PREDICTIVE :
• USE OF DATA TO FIND OUT WHAT COULD HAPPEN IN THE FUTURE
• APPLICATION OF STATISTICAL OR STRUCTURAL MODELS FOR
PREDICTIVE FORECASTING OR CLASSIFICATION
• (3) PRESCRIPTIVE :THE USE OF DATA TO PRESCRIBE THE BEST
COURSE OF ACTION FOR THE FUTURE.
• THREE BROAD RESEARCH DIRECTIONS:
• (A) BIG DATA ANALYTICS
• (B) TEXT ANALYTICS
• (C) NETWORK ANALYTICS

15. STAGES IN BIA
• DESIGNING TOOLS
• FOR CONVERTING AND INTEGRATING ENTERPRISE-SPECIFIC
DATA
• FOR EXTRACTION
• TRANSFORMATION,
• AND LOADING (ETL) OF DATA
• FOR DATA CHARACTERISTICS
• DATABASE QUERY
• ONLINE ANALYTICAL PROCESSING (OLAP)
• FOR ANALYZING AND VISUALIZING VARIOUS METRICS
USING ADVANCED REPORTING TOOLS

16. STAGES [CONTD…]
• ADVANCED KNOWLEDGE DISCOVERY FOR
ASSOCIATION RULE MINING
• DATABASE SEGMENTATION AND CLUSTERING
• ANOMALY/OUTLIER DETECTION
• PREDICTIVE MODELING IN HUMAN RESOURCES
• ACCOUNTING
• FINANCE
• AND MARKETING APPLICATIONS.

17. CONCLUSION
• BUSINESSES ARE GAINING INSIGHTS FROM THE GROWING
VOLUMES OF DATA GENERATED BY ENTERPRISE-WIDE
APPLICATIONS
• ENTERPRISE RESOURCE PLANNING (ERP)
• CUSTOMER RELATIONSHIP MANAGEMENT (CRM)
• SUPPLY-CHAIN MANAGEMENT (SCM)
• KNOWLEDGE MANAGEMENT
• COLLABORATIVE COMPUTING
• WEB ANALYTICS
• USED IN
• AIRLINES, ASTRONOMY, BUSINESS
• IT AND TELECOMMUNICATION FIRMS
• PHYSICS, SEARCH ENGINES AND MORE

18. REFERENCES:
• BUSINESS INTELLIGENCE AND ANALYTICS: RESEARCH DIRECTIONS
• EE-PENG LIM, HSINCHUN CHEN, GUOQING CHEN.
• BUSINESS INTELLIGENCE AND ANALYTICS EDUCATION, AND PROGRAM DEVELOPMENT: A UNIQUE
OPPORTUNITY FOR THE INFORMATION SYSTEMS DISCIPLINE
• ROGER H. L. CHIANG, PAULO GOES, EDWARD A. STOHR.
• WIKIPEDIA

19. THANK YOU
ANY QUERIES???