ๅฐŠๆ•ฌ็š„ ๅพฎไฟกๆฑ‡็Ž‡๏ผš1ๅ†† โ‰ˆ 0.046078 ๅ…ƒ ๆ”ฏไป˜ๅฎๆฑ‡็Ž‡๏ผš1ๅ†† โ‰ˆ 0.046168ๅ…ƒ [้€€ๅ‡บ็™ปๅฝ•]
SlideShare a Scribd company logo

Datawarehousing and Business Intelligence

โ€ขDownload as PPT, PDFโ€ข
โ€ข
Prithwis Mukerjee
Prithwis Mukerjee

The document provides an introduction to data warehousing and business intelligence. It discusses how a data warehouse can improve decision making by integrating data from various sources and systems. Key benefits include revenue stimulation, cost reduction, productivity improvement and competitive advantage. The architecture of a data warehouse is described, including how it differs from operational systems in terms of data access, organization and time handling. Dimensional data modeling techniques and performance measures are also covered.

EducationTechnologyBusiness
1 of 25
Data Warehousing & Business Intelligence Introduction What do you think of when you hear the words Data Warehousing ? Prithwis Mukerjee, Ph.D.
Conceptual DW Definition ,[object Object],ยฉ Prithwis Mukerjee
The Knowledge Management Framework ยฉ Prithwis Mukerjee Data Structure Technology Infrastructure Management Business Applications Information Technology Process People
How it all fits in .. ยฉ Prithwis Mukerjee Database CRM : Customer Relationship Management Transactional Systems ERP : Enterprise Resource Planning SCM : Supply Chain Management Data Warehouse
Typical Business Uses of the Data Warehouse ยฉ Prithwis Mukerjee Target Advertising campaigns Strategic Initiatives Business Processes Functions Profitability Analysis Market Basket Analysis Product Pricing Cross-selling and upgrade selling Just-in-Time Inventory Category Management Human Resources Management Determine Customer Lifetime Value Predict Customer Behavior Management Reporting Customer Acquisition and Retention
Benefits of the Data Warehouse Program ยฉ Prithwis Mukerjee Improves the way we do business and the bottom line Revenue Stimulation & Revenue Protection Cost Reduction and Cost Avoidance Productivity Improvement Profitability Enhancement Performance Analysis DecisionMaking Market Response Competitive advantage
Non-integrated Decision Support Architecture ยฉ Prithwis Mukerjee DSSs,Report writers, Excel, databases, etc. Data Feeds Budgeting Analysis Sales Forecasting Inventory System Order System Procurement System Accounting System
Basic Data Warehouse Architecture ยฉ Prithwis Mukerjee Enterprise DW/ODS Subject oriented Data Warehouses or Data Marts One Stop Data Shopping Fewer Data Feeds Inventory System Order System Procurement System Accounting System
Performance Measures : Definition & Examples ,[object Object],[object Object],ยฉ Prithwis Mukerjee Innovation & Learning Measures Customer Measures Financial Measures Internal Process Measures ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Differences between OLTP and DW ,[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee Explanations ..
Data access, manipulation and use ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee OLTP DW Differences between OLTP and DW
Data Organisation And integration ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee OLTP DW Differences between OLTP and DW
Time Handling ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee OLTP DW Differences between OLTP and DW
Usage ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee OLTP DW Differences between OLTP and DW
Data Structures & Schemas ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee OLTP DW Differences between OLTP and DW
Basic Datawarehousing Topics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee
Dimensional Data Modeling ,[object Object],ยฉ Prithwis Mukerjee
The Technical Infrastructure ,[object Object],ยฉ Prithwis Mukerjee
Knowledge Management Architecture ยฉ Prithwis Mukerjee Metadata Source Data Purchasing Systems General Ledger Other Internal Systems External Data Sources Data Resource Management And Quality Assurance . Invoicing Systems Data Extraction Integration and Cleansing Processes Extract ODS Purchasing Marketing and Sales Corporate information Product Line Location Translate Attribute Calculate Derive Summarize Synchronize Segmented Data Subsets Summarized Data Data Warehouse Applications Custom Developed Applications Data Mining Statistical Packages Query Access Tools Data Marts Transform
The Business and The IT Perspective ยฉ Prithwis Mukerjee Business What will it do? What value will it bring? How is it built? How does it work? Information Technology Data Warehouse
The Business Perspective of the Data Warehouse ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee Focuses on needs and usage
The IT Perspective of the Data Warehouse ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ยฉ Prithwis Mukerjee Focuses on database, technology, organizational features
DW Methodology ,[object Object],ยฉ Prithwis Mukerjee
Data Warehouse System Development Life Cycle ยฉ Prithwis Mukerjee CONSTRUC- TION IMPLEMEN- TATION DESIGN ANALYSIS PLANNING MANAGING Business Architecture Data Architecture Technology Architecture Management Infrastructure
ยฉ Prithwis Mukerjee stop

Recommended

DATA WAREHOUSING
DATA WAREHOUSINGDATA WAREHOUSING
DATA WAREHOUSING
King Julian
ย 
Ppt
PptPpt
Ppt
bullsrockr666
ย 
Business intelligence and data warehouses
Business intelligence and data warehousesBusiness intelligence and data warehouses
Business intelligence and data warehouses
Dhani Ahmad
ย 
Big data by Mithlesh sadh
Big data by Mithlesh sadhBig data by Mithlesh sadh
Big data by Mithlesh sadh
Mithlesh Sadh
ย 
Big data ppt
Big data pptBig data ppt
Big data ppt
Deepika ParthaSarathy
ย 
Big Data
Big DataBig Data
Big Data
Subhavinolin Raja
ย 
Data warehousing
Data warehousingData warehousing
Data warehousing
Vigneshwaar Ponnuswamy
ย 
Big Data - Applications and Technologies Overview
Big Data - Applications and Technologies OverviewBig Data - Applications and Technologies Overview
Big Data - Applications and Technologies Overview
Sivashankar Ganapathy
ย 

Recommended

DATA WAREHOUSING
DATA WAREHOUSINGDATA WAREHOUSING
DATA WAREHOUSING
King Julian
ย 
Ppt
PptPpt
Ppt
bullsrockr666
ย 
Business intelligence and data warehouses
Business intelligence and data warehousesBusiness intelligence and data warehouses
Business intelligence and data warehouses
Dhani Ahmad
ย 
Big data by Mithlesh sadh
Big data by Mithlesh sadhBig data by Mithlesh sadh
Big data by Mithlesh sadh
Mithlesh Sadh
ย 
Big data ppt
Big data pptBig data ppt
Big data ppt
Deepika ParthaSarathy
ย 
Big Data
Big DataBig Data
Big Data
Subhavinolin Raja
ย 
Data warehousing
Data warehousingData warehousing
Data warehousing
Vigneshwaar Ponnuswamy
ย 
Big Data - Applications and Technologies Overview
Big Data - Applications and Technologies OverviewBig Data - Applications and Technologies Overview
Big Data - Applications and Technologies Overview
Sivashankar Ganapathy
ย 
Data engineering
Data engineeringData engineering
Data engineering
Parimala Killada
ย 
Big Data Analytics with Hadoop
Big Data Analytics with HadoopBig Data Analytics with Hadoop
Big Data Analytics with Hadoop
Philippe Julio
ย 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
Dr. Dipti Patil
ย 
Data warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika KotechaData warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika Kotecha
Radhika Kotecha
ย 
Big data
Big dataBig data
Big data
Dr. Wilfred Lin (Ph.D.)
ย 
Introduction to Data Warehouse
Introduction to Data WarehouseIntroduction to Data Warehouse
Introduction to Data Warehouse
Shanthi Mukkavilli
ย 
Overview of Big data(ppt)
Overview of Big data(ppt)Overview of Big data(ppt)
Overview of Big data(ppt)
Shatavisha Roy Chowdhury
ย 
What is Big Data?
What is Big Data?What is Big Data?
What is Big Data?
Bernard Marr
ย 
Introduction to Business Intelligence
Introduction to Business IntelligenceIntroduction to Business Intelligence
Introduction to Business Intelligence
Almog Ramrajkar
ย 
Big Data Analytics
Big Data AnalyticsBig Data Analytics
Big Data Analytics
Ghulam Imaduddin
ย 
Big Data Evolution
Big Data EvolutionBig Data Evolution
Big Data Evolution
itnewsafrica
ย 
Introduction to Big Data
Introduction to Big DataIntroduction to Big Data
Introduction to Big Data
Joey Li
ย 
Business Intelligence Overview
Business Intelligence OverviewBusiness Intelligence Overview
Business Intelligence Overview
netpeachteam
ย 
BIG DATA and USE CASES
BIG DATA and USE CASESBIG DATA and USE CASES
BIG DATA and USE CASES
Bhaskara Reddy Sannapureddy
ย 
Data Warehouse 101
Data Warehouse 101Data Warehouse 101
Data Warehouse 101
PanaEk Warawit
ย 
DATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MININGDATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MINING
Lovely Professional University
ย 
Introduction to Data Warehousing
Introduction to Data WarehousingIntroduction to Data Warehousing
Introduction to Data Warehousing
Jason S
ย 
Data Streaming For Big Data
Data Streaming For Big DataData Streaming For Big Data
Data Streaming For Big Data
Seval ร‡apraz
ย 
Fraud and Risk in Big Data
Fraud and Risk in Big DataFraud and Risk in Big Data
Fraud and Risk in Big Data
Umma Khatuna Jannat
ย 
Big data visualization
Big data visualizationBig data visualization
Big data visualization
Anurag Gupta
ย 
Seleqtech Info
Seleqtech InfoSeleqtech Info
Seleqtech Info
David Donaldson
ย 
IT Ready - DW: 1st Day
IT Ready - DW: 1st Day IT Ready - DW: 1st Day
IT Ready - DW: 1st Day
Siwawong Wuttipongprasert
ย 

More Related Content

What's hot

Data engineering
Data engineeringData engineering
Data engineering
Parimala Killada
ย 
Big Data Analytics with Hadoop
Big Data Analytics with HadoopBig Data Analytics with Hadoop
Big Data Analytics with Hadoop
Philippe Julio
ย 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
Dr. Dipti Patil
ย 
Data warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika KotechaData warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika Kotecha
Radhika Kotecha
ย 
Big data
Big dataBig data
Big data
Dr. Wilfred Lin (Ph.D.)
ย 
Introduction to Data Warehouse
Introduction to Data WarehouseIntroduction to Data Warehouse
Introduction to Data Warehouse
Shanthi Mukkavilli
ย 
Overview of Big data(ppt)
Overview of Big data(ppt)Overview of Big data(ppt)
Overview of Big data(ppt)
Shatavisha Roy Chowdhury
ย 
What is Big Data?
What is Big Data?What is Big Data?
What is Big Data?
Bernard Marr
ย 
Introduction to Business Intelligence
Introduction to Business IntelligenceIntroduction to Business Intelligence
Introduction to Business Intelligence
Almog Ramrajkar
ย 
Big Data Analytics
Big Data AnalyticsBig Data Analytics
Big Data Analytics
Ghulam Imaduddin
ย 
Big Data Evolution
Big Data EvolutionBig Data Evolution
Big Data Evolution
itnewsafrica
ย 
Introduction to Big Data
Introduction to Big DataIntroduction to Big Data
Introduction to Big Data
Joey Li
ย 
Business Intelligence Overview
Business Intelligence OverviewBusiness Intelligence Overview
Business Intelligence Overview
netpeachteam
ย 
BIG DATA and USE CASES
BIG DATA and USE CASESBIG DATA and USE CASES
BIG DATA and USE CASES
Bhaskara Reddy Sannapureddy
ย 
Data Warehouse 101
Data Warehouse 101Data Warehouse 101
Data Warehouse 101
PanaEk Warawit
ย 
DATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MININGDATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MINING
Lovely Professional University
ย 
Introduction to Data Warehousing
Introduction to Data WarehousingIntroduction to Data Warehousing
Introduction to Data Warehousing
Jason S
ย 
Data Streaming For Big Data
Data Streaming For Big DataData Streaming For Big Data
Data Streaming For Big Data
Seval ร‡apraz
ย 
Fraud and Risk in Big Data
Fraud and Risk in Big DataFraud and Risk in Big Data
Fraud and Risk in Big Data
Umma Khatuna Jannat
ย 
Big data visualization
Big data visualizationBig data visualization
Big data visualization
Anurag Gupta
ย 

What's hot (20)

Data engineering
Data engineeringData engineering
Data engineering
ย 
Big Data Analytics with Hadoop
Big Data Analytics with HadoopBig Data Analytics with Hadoop
Big Data Analytics with Hadoop
ย 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
ย 
Data warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika KotechaData warehousing - Dr. Radhika Kotecha
Data warehousing - Dr. Radhika Kotecha
ย 
Big data
Big dataBig data
Big data
ย 
Introduction to Data Warehouse
Introduction to Data WarehouseIntroduction to Data Warehouse
Introduction to Data Warehouse
ย 
Overview of Big data(ppt)
Overview of Big data(ppt)Overview of Big data(ppt)
Overview of Big data(ppt)
ย 
What is Big Data?
What is Big Data?What is Big Data?
What is Big Data?
ย 
Introduction to Business Intelligence
Introduction to Business IntelligenceIntroduction to Business Intelligence
Introduction to Business Intelligence
ย 
Big Data Analytics
Big Data AnalyticsBig Data Analytics
Big Data Analytics
ย 
Big Data Evolution
Big Data EvolutionBig Data Evolution
Big Data Evolution
ย 
Introduction to Big Data
Introduction to Big DataIntroduction to Big Data
Introduction to Big Data
ย 
Business Intelligence Overview
Business Intelligence OverviewBusiness Intelligence Overview
Business Intelligence Overview
ย 
BIG DATA and USE CASES
BIG DATA and USE CASESBIG DATA and USE CASES
BIG DATA and USE CASES
ย 
Data Warehouse 101
Data Warehouse 101Data Warehouse 101
Data Warehouse 101
ย 
DATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MININGDATA WAREHOUSING AND DATA MINING
DATA WAREHOUSING AND DATA MINING
ย 
Introduction to Data Warehousing
Introduction to Data WarehousingIntroduction to Data Warehousing
Introduction to Data Warehousing
ย 
Data Streaming For Big Data
Data Streaming For Big DataData Streaming For Big Data
Data Streaming For Big Data
ย 
Fraud and Risk in Big Data
Fraud and Risk in Big DataFraud and Risk in Big Data
Fraud and Risk in Big Data
ย 
Big data visualization
Big data visualizationBig data visualization
Big data visualization
ย 

Similar to Datawarehousing and Business Intelligence

Seleqtech Info
Seleqtech InfoSeleqtech Info
Seleqtech Info
David Donaldson
ย 
IT Ready - DW: 1st Day
IT Ready - DW: 1st Day IT Ready - DW: 1st Day
IT Ready - DW: 1st Day
Siwawong Wuttipongprasert
ย 
Analyzta_Presentation V1
Analyzta_Presentation V1Analyzta_Presentation V1
Analyzta_Presentation V1
Anayzta Team
ย 
dw_concepts_2_day_course.ppt
dw_concepts_2_day_course.pptdw_concepts_2_day_course.ppt
dw_concepts_2_day_course.ppt
DougSchoemaker
ย 
Creating a Successful DataOps Framework for Your Business.pdf
Creating a Successful DataOps Framework for Your Business.pdfCreating a Successful DataOps Framework for Your Business.pdf
Creating a Successful DataOps Framework for Your Business.pdf
Enov8
ย 
Critical Success Factors
Critical Success FactorsCritical Success Factors
Critical Success Factors
ูุชุญูŠ ุจุงุตุจูŠุญ
ย 
Information architecture overview
Information architecture overviewInformation architecture overview
Information architecture overview
James M. Dey
ย 
Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned
Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned
Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned
Charles Eubanks
ย 
T/DG's Pulse.Time - Resource and Project Management of Enterprise
T/DG's Pulse.Time - Resource and Project Management of EnterpriseT/DG's Pulse.Time - Resource and Project Management of Enterprise
T/DG's Pulse.Time - Resource and Project Management of Enterprise
The Digital Group
ย 
how to successfully implement a data analytics solution.pdf
how to successfully implement a data analytics solution.pdfhow to successfully implement a data analytics solution.pdf
how to successfully implement a data analytics solution.pdf
basilmph
ย 
09 mdm tool comaprison
09 mdm tool comaprison09 mdm tool comaprison
09 mdm tool comaprison
Sneha Kulkarni
ย 
Financial Services - New Approach to Data Management in the Digital Era
Financial Services - New Approach to Data Management in the Digital EraFinancial Services - New Approach to Data Management in the Digital Era
Financial Services - New Approach to Data Management in the Digital Era
accenture
ย 
Business Intelligence Industry Perspective Session I
Business Intelligence Industry Perspective Session IBusiness Intelligence Industry Perspective Session I
Business Intelligence Industry Perspective Session I
Prithwis Mukerjee
ย 
How to Build a Scalable Customer Analytics Hub
How to Build a Scalable Customer Analytics HubHow to Build a Scalable Customer Analytics Hub
How to Build a Scalable Customer Analytics Hub
CCG
ย 
Leverage Data Strategy as a Catalyst for Innovation
Leverage Data Strategy as a Catalyst for InnovationLeverage Data Strategy as a Catalyst for Innovation
Leverage Data Strategy as a Catalyst for Innovation
Glorium Tech
ย 
Data warehouse
Data warehouseData warehouse
Data warehouse
MR Z
ย 
Big Data Analytics Architecture PowerPoint Presentation Slides
Big Data Analytics Architecture PowerPoint Presentation SlidesBig Data Analytics Architecture PowerPoint Presentation Slides
Big Data Analytics Architecture PowerPoint Presentation Slides
SlideTeam
ย 
Everything you wanted to know about data ops
Everything you wanted to know about data opsEverything you wanted to know about data ops
Everything you wanted to know about data ops
Enov8
ย 
BI_StrategyDM2
BI_StrategyDM2BI_StrategyDM2
BI_StrategyDM2
Dan McDonald
ย 
Reinvent Your Data Management Strategy for Successful Digital Transformation
Reinvent Your Data Management Strategy for Successful Digital TransformationReinvent Your Data Management Strategy for Successful Digital Transformation
Reinvent Your Data Management Strategy for Successful Digital Transformation
Denodo
ย 

Similar to Datawarehousing and Business Intelligence (20)

Seleqtech Info
Seleqtech InfoSeleqtech Info
Seleqtech Info
ย 
IT Ready - DW: 1st Day
IT Ready - DW: 1st Day IT Ready - DW: 1st Day
IT Ready - DW: 1st Day
ย 
Analyzta_Presentation V1
Analyzta_Presentation V1Analyzta_Presentation V1
Analyzta_Presentation V1
ย 
dw_concepts_2_day_course.ppt
dw_concepts_2_day_course.pptdw_concepts_2_day_course.ppt
dw_concepts_2_day_course.ppt
ย 
Creating a Successful DataOps Framework for Your Business.pdf
Creating a Successful DataOps Framework for Your Business.pdfCreating a Successful DataOps Framework for Your Business.pdf
Creating a Successful DataOps Framework for Your Business.pdf
ย 
Critical Success Factors
Critical Success FactorsCritical Success Factors
Critical Success Factors
ย 
Information architecture overview
Information architecture overviewInformation architecture overview
Information architecture overview
ย 
Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned
Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned
Fuse Analytics - HR & Payroll Cloud Transformation Pitfalls, Lessons Learned
ย 
T/DG's Pulse.Time - Resource and Project Management of Enterprise
T/DG's Pulse.Time - Resource and Project Management of EnterpriseT/DG's Pulse.Time - Resource and Project Management of Enterprise
T/DG's Pulse.Time - Resource and Project Management of Enterprise
ย 
how to successfully implement a data analytics solution.pdf
how to successfully implement a data analytics solution.pdfhow to successfully implement a data analytics solution.pdf
how to successfully implement a data analytics solution.pdf
ย 
09 mdm tool comaprison
09 mdm tool comaprison09 mdm tool comaprison
09 mdm tool comaprison
ย 
Financial Services - New Approach to Data Management in the Digital Era
Financial Services - New Approach to Data Management in the Digital EraFinancial Services - New Approach to Data Management in the Digital Era
Financial Services - New Approach to Data Management in the Digital Era
ย 
Business Intelligence Industry Perspective Session I
Business Intelligence Industry Perspective Session IBusiness Intelligence Industry Perspective Session I
Business Intelligence Industry Perspective Session I
ย 
How to Build a Scalable Customer Analytics Hub
How to Build a Scalable Customer Analytics HubHow to Build a Scalable Customer Analytics Hub
How to Build a Scalable Customer Analytics Hub
ย 
Leverage Data Strategy as a Catalyst for Innovation
Leverage Data Strategy as a Catalyst for InnovationLeverage Data Strategy as a Catalyst for Innovation
Leverage Data Strategy as a Catalyst for Innovation
ย 
Data warehouse
Data warehouseData warehouse
Data warehouse
ย 
Big Data Analytics Architecture PowerPoint Presentation Slides
Big Data Analytics Architecture PowerPoint Presentation SlidesBig Data Analytics Architecture PowerPoint Presentation Slides
Big Data Analytics Architecture PowerPoint Presentation Slides
ย 
Everything you wanted to know about data ops
Everything you wanted to know about data opsEverything you wanted to know about data ops
Everything you wanted to know about data ops
ย 
BI_StrategyDM2
BI_StrategyDM2BI_StrategyDM2
BI_StrategyDM2
ย 
Reinvent Your Data Management Strategy for Successful Digital Transformation
Reinvent Your Data Management Strategy for Successful Digital TransformationReinvent Your Data Management Strategy for Successful Digital Transformation
Reinvent Your Data Management Strategy for Successful Digital Transformation
ย 

More from Prithwis Mukerjee

Bitcoin, Blockchain and the Crypto Contracts - Part 2
Bitcoin, Blockchain and the Crypto Contracts - Part 2Bitcoin, Blockchain and the Crypto Contracts - Part 2
Bitcoin, Blockchain and the Crypto Contracts - Part 2
Prithwis Mukerjee
ย 
Bitcoin, Blockchain and Crypto Contracts - Part 3
Bitcoin, Blockchain and Crypto Contracts - Part 3Bitcoin, Blockchain and Crypto Contracts - Part 3
Bitcoin, Blockchain and Crypto Contracts - Part 3
Prithwis Mukerjee
ย 
Internet of Things
Internet of ThingsInternet of Things
Internet of Things
Prithwis Mukerjee
ย 
Thought controlled devices
Thought controlled devicesThought controlled devices
Thought controlled devices
Prithwis Mukerjee
ย 
Cloudcasting
CloudcastingCloudcasting
Cloudcasting
Prithwis Mukerjee
ย 
Currency, Commodity and Bitcoins
Currency, Commodity and BitcoinsCurrency, Commodity and Bitcoins
Currency, Commodity and Bitcoins
Prithwis Mukerjee
ย 
Data Science
Data ScienceData Science
Data Science
Prithwis Mukerjee
ย 
05 OLAP v6 weekend
05 OLAP v6 weekend05 OLAP v6 weekend
05 OLAP v6 weekend
Prithwis Mukerjee
ย 
04 Dimensional Analysis - v6
04 Dimensional Analysis - v604 Dimensional Analysis - v6
04 Dimensional Analysis - v6
Prithwis Mukerjee
ย 
Thought control
Thought controlThought control
Thought control
Prithwis Mukerjee
ย 
World of data @ praxis 2013 v2
World of data @ praxis 2013 v2World of data @ praxis 2013 v2
World of data @ praxis 2013 v2
Prithwis Mukerjee
ย 
BIS 08a - Application Development - II Version 2
BIS 08a - Application Development - II Version 2BIS 08a - Application Development - II Version 2
BIS 08a - Application Development - II Version 2
Prithwis Mukerjee
ย 
Lecture02 - Data Mining & Analytics
Lecture02 - Data Mining & AnalyticsLecture02 - Data Mining & Analytics
Lecture02 - Data Mining & Analytics
Prithwis Mukerjee
ย 
เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?
เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?
เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?
Prithwis Mukerjee
ย 
Data mining clustering-2009-v0
Data mining clustering-2009-v0Data mining clustering-2009-v0
Data mining clustering-2009-v0
Prithwis Mukerjee
ย 
Data mining classification-2009-v0
Data mining classification-2009-v0Data mining classification-2009-v0
Data mining classification-2009-v0
Prithwis Mukerjee
ย 
Data mining arm-2009-v0
Data mining arm-2009-v0Data mining arm-2009-v0
Data mining arm-2009-v0
Prithwis Mukerjee
ย 
Data mining intro-2009-v2
Data mining intro-2009-v2Data mining intro-2009-v2
Data mining intro-2009-v2
Prithwis Mukerjee
ย 
PPM Lite
PPM LitePPM Lite
PPM Lite
Prithwis Mukerjee
ย 
OLAP Cubes in Datawarehousing
OLAP Cubes in DatawarehousingOLAP Cubes in Datawarehousing
OLAP Cubes in Datawarehousing
Prithwis Mukerjee
ย 

More from Prithwis Mukerjee (20)

Bitcoin, Blockchain and the Crypto Contracts - Part 2
Bitcoin, Blockchain and the Crypto Contracts - Part 2Bitcoin, Blockchain and the Crypto Contracts - Part 2
Bitcoin, Blockchain and the Crypto Contracts - Part 2
ย 
Bitcoin, Blockchain and Crypto Contracts - Part 3
Bitcoin, Blockchain and Crypto Contracts - Part 3Bitcoin, Blockchain and Crypto Contracts - Part 3
Bitcoin, Blockchain and Crypto Contracts - Part 3
ย 
Internet of Things
Internet of ThingsInternet of Things
Internet of Things
ย 
Thought controlled devices
Thought controlled devicesThought controlled devices
Thought controlled devices
ย 
Cloudcasting
CloudcastingCloudcasting
Cloudcasting
ย 
Currency, Commodity and Bitcoins
Currency, Commodity and BitcoinsCurrency, Commodity and Bitcoins
Currency, Commodity and Bitcoins
ย 
Data Science
Data ScienceData Science
Data Science
ย 
05 OLAP v6 weekend
05 OLAP v6 weekend05 OLAP v6 weekend
05 OLAP v6 weekend
ย 
04 Dimensional Analysis - v6
04 Dimensional Analysis - v604 Dimensional Analysis - v6
04 Dimensional Analysis - v6
ย 
Thought control
Thought controlThought control
Thought control
ย 
World of data @ praxis 2013 v2
World of data @ praxis 2013 v2World of data @ praxis 2013 v2
World of data @ praxis 2013 v2
ย 
BIS 08a - Application Development - II Version 2
BIS 08a - Application Development - II Version 2BIS 08a - Application Development - II Version 2
BIS 08a - Application Development - II Version 2
ย 
Lecture02 - Data Mining & Analytics
Lecture02 - Data Mining & AnalyticsLecture02 - Data Mining & Analytics
Lecture02 - Data Mining & Analytics
ย 
เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?
เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?
เฆ‡เฆจเงเฆŸเฆพเฆฐเงเฆจเง‡เฆŸ เฆ•เฆฟ เฆเฆฌเฆ‚ เฆ•เง‡เฆจ ?
ย 
Data mining clustering-2009-v0
Data mining clustering-2009-v0Data mining clustering-2009-v0
Data mining clustering-2009-v0
ย 
Data mining classification-2009-v0
Data mining classification-2009-v0Data mining classification-2009-v0
Data mining classification-2009-v0
ย 
Data mining arm-2009-v0
Data mining arm-2009-v0Data mining arm-2009-v0
Data mining arm-2009-v0
ย 
Data mining intro-2009-v2
Data mining intro-2009-v2Data mining intro-2009-v2
Data mining intro-2009-v2
ย 
PPM Lite
PPM LitePPM Lite
PPM Lite
ย 
OLAP Cubes in Datawarehousing
OLAP Cubes in DatawarehousingOLAP Cubes in Datawarehousing
OLAP Cubes in Datawarehousing
ย 

Recently uploaded

The Science of Learning: implications for modern teaching
The Science of Learning: implications for modern teachingThe Science of Learning: implications for modern teaching
The Science of Learning: implications for modern teaching
Derek Wenmoth
ย 
Opportunity scholarships and the schools that receive them
Opportunity scholarships and the schools that receive themOpportunity scholarships and the schools that receive them
Opportunity scholarships and the schools that receive them
EducationNC
ย 
How to Create a Stage or a Pipeline in Odoo 17 CRM
How to Create a Stage or a Pipeline in Odoo 17 CRMHow to Create a Stage or a Pipeline in Odoo 17 CRM
How to Create a Stage or a Pipeline in Odoo 17 CRM
Celine George
ย 
How to stay relevant as a cyber professional: Skills, trends and career paths...
How to stay relevant as a cyber professional: Skills, trends and career paths...How to stay relevant as a cyber professional: Skills, trends and career paths...
How to stay relevant as a cyber professional: Skills, trends and career paths...
Infosec
ย 
pol sci Election and Representation Class 11 Notes.pdf
pol sci Election and Representation Class 11 Notes.pdfpol sci Election and Representation Class 11 Notes.pdf
pol sci Election and Representation Class 11 Notes.pdf
BiplabHalder13
ย 
Creating Images and Videos through AI.pptx
Creating Images and Videos through AI.pptxCreating Images and Videos through AI.pptx
Creating Images and Videos through AI.pptx
Forum of Blended Learning
ย 
Non-Verbal Communication for Tech Professionals
Non-Verbal Communication for Tech ProfessionalsNon-Verbal Communication for Tech Professionals
Non-Verbal Communication for Tech Professionals
MattVassar1
ย 
220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...
220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...
220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...
Kalna College
ย 
Keynote given on June 24 for MASSP at Grand Traverse City
Keynote given on June 24 for MASSP at Grand Traverse CityKeynote given on June 24 for MASSP at Grand Traverse City
Keynote given on June 24 for MASSP at Grand Traverse City
PJ Caposey
ย 
Diversity Quiz Prelims by Quiz Club, IIT Kanpur
Diversity Quiz Prelims by Quiz Club, IIT KanpurDiversity Quiz Prelims by Quiz Club, IIT Kanpur
Diversity Quiz Prelims by Quiz Club, IIT Kanpur
Quiz Club IIT Kanpur
ย 
(T.L.E.) Agriculture: "Ornamental Plants"
(T.L.E.) Agriculture: "Ornamental Plants"(T.L.E.) Agriculture: "Ornamental Plants"
(T.L.E.) Agriculture: "Ornamental Plants"
MJDuyan
ย 
managing Behaviour in early childhood education.pptx
managing Behaviour in early childhood education.pptxmanaging Behaviour in early childhood education.pptx
managing Behaviour in early childhood education.pptx
nabaegha
ย 
Diversity Quiz Finals by Quiz Club, IIT Kanpur
Diversity Quiz Finals by Quiz Club, IIT KanpurDiversity Quiz Finals by Quiz Club, IIT Kanpur
Diversity Quiz Finals by Quiz Club, IIT Kanpur
Quiz Club IIT Kanpur
ย 
Erasmus + DISSEMINATION ACTIVITIES Croatia
Erasmus + DISSEMINATION ACTIVITIES CroatiaErasmus + DISSEMINATION ACTIVITIES Croatia
Erasmus + DISSEMINATION ACTIVITIES Croatia
whatchangedhowreflec
ย 
Talking Tech through Compelling Visual Aids
Talking Tech through Compelling Visual AidsTalking Tech through Compelling Visual Aids
Talking Tech through Compelling Visual Aids
MattVassar1
ย 
Cross-Cultural Leadership and Communication
Cross-Cultural Leadership and CommunicationCross-Cultural Leadership and Communication
Cross-Cultural Leadership and Communication
MattVassar1
ย 
Information and Communication Technology in Education
Information and Communication Technology in EducationInformation and Communication Technology in Education
Information and Communication Technology in Education
MJDuyan
ย 
Art Integrated Project between Maharashtra and Sikkim
Art Integrated Project between Maharashtra and SikkimArt Integrated Project between Maharashtra and Sikkim
Art Integrated Project between Maharashtra and Sikkim
pranavsawarbandhe24
ย 
Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024
Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024
Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024
yarusun
ย 
220711130100 udita Chakraborty Aims and objectives of national policy on inf...
220711130100 udita Chakraborty Aims and objectives of national policy on inf...220711130100 udita Chakraborty Aims and objectives of national policy on inf...
220711130100 udita Chakraborty Aims and objectives of national policy on inf...
Kalna College
ย 

Recently uploaded (20)

The Science of Learning: implications for modern teaching
The Science of Learning: implications for modern teachingThe Science of Learning: implications for modern teaching
The Science of Learning: implications for modern teaching
ย 
Opportunity scholarships and the schools that receive them
Opportunity scholarships and the schools that receive themOpportunity scholarships and the schools that receive them
Opportunity scholarships and the schools that receive them
ย 
How to Create a Stage or a Pipeline in Odoo 17 CRM
How to Create a Stage or a Pipeline in Odoo 17 CRMHow to Create a Stage or a Pipeline in Odoo 17 CRM
How to Create a Stage or a Pipeline in Odoo 17 CRM
ย 
How to stay relevant as a cyber professional: Skills, trends and career paths...
How to stay relevant as a cyber professional: Skills, trends and career paths...How to stay relevant as a cyber professional: Skills, trends and career paths...
How to stay relevant as a cyber professional: Skills, trends and career paths...
ย 
pol sci Election and Representation Class 11 Notes.pdf
pol sci Election and Representation Class 11 Notes.pdfpol sci Election and Representation Class 11 Notes.pdf
pol sci Election and Representation Class 11 Notes.pdf
ย 
Creating Images and Videos through AI.pptx
Creating Images and Videos through AI.pptxCreating Images and Videos through AI.pptx
Creating Images and Videos through AI.pptx
ย 
Non-Verbal Communication for Tech Professionals
Non-Verbal Communication for Tech ProfessionalsNon-Verbal Communication for Tech Professionals
Non-Verbal Communication for Tech Professionals
ย 
220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...
220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...
220711130086 Sukanta Singh E learning and mobile learning EPC 3 Internal Asse...
ย 
Keynote given on June 24 for MASSP at Grand Traverse City
Keynote given on June 24 for MASSP at Grand Traverse CityKeynote given on June 24 for MASSP at Grand Traverse City
Keynote given on June 24 for MASSP at Grand Traverse City
ย 
Diversity Quiz Prelims by Quiz Club, IIT Kanpur
Diversity Quiz Prelims by Quiz Club, IIT KanpurDiversity Quiz Prelims by Quiz Club, IIT Kanpur
Diversity Quiz Prelims by Quiz Club, IIT Kanpur
ย 
(T.L.E.) Agriculture: "Ornamental Plants"
(T.L.E.) Agriculture: "Ornamental Plants"(T.L.E.) Agriculture: "Ornamental Plants"
(T.L.E.) Agriculture: "Ornamental Plants"
ย 
managing Behaviour in early childhood education.pptx
managing Behaviour in early childhood education.pptxmanaging Behaviour in early childhood education.pptx
managing Behaviour in early childhood education.pptx
ย 
Diversity Quiz Finals by Quiz Club, IIT Kanpur
Diversity Quiz Finals by Quiz Club, IIT KanpurDiversity Quiz Finals by Quiz Club, IIT Kanpur
Diversity Quiz Finals by Quiz Club, IIT Kanpur
ย 
Erasmus + DISSEMINATION ACTIVITIES Croatia
Erasmus + DISSEMINATION ACTIVITIES CroatiaErasmus + DISSEMINATION ACTIVITIES Croatia
Erasmus + DISSEMINATION ACTIVITIES Croatia
ย 
Talking Tech through Compelling Visual Aids
Talking Tech through Compelling Visual AidsTalking Tech through Compelling Visual Aids
Talking Tech through Compelling Visual Aids
ย 
Cross-Cultural Leadership and Communication
Cross-Cultural Leadership and CommunicationCross-Cultural Leadership and Communication
Cross-Cultural Leadership and Communication
ย 
Information and Communication Technology in Education
Information and Communication Technology in EducationInformation and Communication Technology in Education
Information and Communication Technology in Education
ย 
Art Integrated Project between Maharashtra and Sikkim
Art Integrated Project between Maharashtra and SikkimArt Integrated Project between Maharashtra and Sikkim
Art Integrated Project between Maharashtra and Sikkim
ย 
Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024
Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024
Get Success with the Latest UiPath UIPATH-ADPV1 Exam Dumps (V11.02) 2024
ย 
220711130100 udita Chakraborty Aims and objectives of national policy on inf...
220711130100 udita Chakraborty Aims and objectives of national policy on inf...220711130100 udita Chakraborty Aims and objectives of national policy on inf...
220711130100 udita Chakraborty Aims and objectives of national policy on inf...
ย 

Datawarehousing and Business Intelligence

  • 1. Data Warehousing & Business Intelligence Introduction What do you think of when you hear the words Data Warehousing ? Prithwis Mukerjee, Ph.D.
  • 2.
  • 3. The Knowledge Management Framework ยฉ Prithwis Mukerjee Data Structure Technology Infrastructure Management Business Applications Information Technology Process People
  • 4. How it all fits in .. ยฉ Prithwis Mukerjee Database CRM : Customer Relationship Management Transactional Systems ERP : Enterprise Resource Planning SCM : Supply Chain Management Data Warehouse
  • 5. Typical Business Uses of the Data Warehouse ยฉ Prithwis Mukerjee Target Advertising campaigns Strategic Initiatives Business Processes Functions Profitability Analysis Market Basket Analysis Product Pricing Cross-selling and upgrade selling Just-in-Time Inventory Category Management Human Resources Management Determine Customer Lifetime Value Predict Customer Behavior Management Reporting Customer Acquisition and Retention
  • 6. Benefits of the Data Warehouse Program ยฉ Prithwis Mukerjee Improves the way we do business and the bottom line Revenue Stimulation & Revenue Protection Cost Reduction and Cost Avoidance Productivity Improvement Profitability Enhancement Performance Analysis DecisionMaking Market Response Competitive advantage
  • 7. Non-integrated Decision Support Architecture ยฉ Prithwis Mukerjee DSSs,Report writers, Excel, databases, etc. Data Feeds Budgeting Analysis Sales Forecasting Inventory System Order System Procurement System Accounting System
  • 8. Basic Data Warehouse Architecture ยฉ Prithwis Mukerjee Enterprise DW/ODS Subject oriented Data Warehouses or Data Marts One Stop Data Shopping Fewer Data Feeds Inventory System Order System Procurement System Accounting System
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19. Knowledge Management Architecture ยฉ Prithwis Mukerjee Metadata Source Data Purchasing Systems General Ledger Other Internal Systems External Data Sources Data Resource Management And Quality Assurance . Invoicing Systems Data Extraction Integration and Cleansing Processes Extract ODS Purchasing Marketing and Sales Corporate information Product Line Location Translate Attribute Calculate Derive Summarize Synchronize Segmented Data Subsets Summarized Data Data Warehouse Applications Custom Developed Applications Data Mining Statistical Packages Query Access Tools Data Marts Transform
  • 20. The Business and The IT Perspective ยฉ Prithwis Mukerjee Business What will it do? What value will it bring? How is it built? How does it work? Information Technology Data Warehouse
  • 21.
  • 22.
  • 23.
  • 24. Data Warehouse System Development Life Cycle ยฉ Prithwis Mukerjee CONSTRUC- TION IMPLEMEN- TATION DESIGN ANALYSIS PLANNING MANAGING Business Architecture Data Architecture Technology Architecture Management Infrastructure
  • 25. ยฉ Prithwis Mukerjee stop
  ็ฟป่ฏ‘๏ผš