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Zusammenfassung

Business Intelligence Notes and Summary
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Comprehensive Summary and Notes of the Business Intelligence 1 course at Fontys. Includes a clickable table of contents. The course is guided along "Business Intelligence, Analytics and Data Science" by Sharda, Delen, Turban, King

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  • Basics of business intelligence sections
  • 10. april 2020
  • 32
  • 2019/2020
  • Zusammenfassung

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Contents
Business Intelligence: .............................................................................................................................................................................................. 4
Changing Business Environments ............................................................................................................................................................................ 4
Evolution of BI ......................................................................................................................................................................................................... 4
Transaction Processing Versus Analytic Processing ................................................................................................................................................. 4
Investing in BI .......................................................................................................................................................................................................... 4
Real-Time BI ............................................................................................................................................................................................................ 5
Analytics .................................................................................................................................................................................................................. 5
Prescriptive Analytics ......................................................................................................................................................................................... 5
Examples: Analytics in Retail Value Chain ............................................................................................................................................................... 6
Start: Vendors .................................................................................................................................................................................................... 6
Final: Customers ................................................................................................................................................................................................ 6
Inventory Optimization ...................................................................................................................................................................................... 6
Price Elasticity .................................................................................................................................................................................................... 6
Big Data ................................................................................................................................................................................................................... 6
Data Continuum ................................................................................................................................................................................................. 7
Taxonomy of data – Structured vs Unstructured ............................................................................................................................................... 7
Data Preprocessing ............................................................................................................................................................................................ 7
START: Raw data sources.............................................................................................................................................................................. 7
1) Data Consolidation ............................................................................................................................................................................ 7
2) Data Cleaning..................................................................................................................................................................................... 7
3) Data Transformation.......................................................................................................................................................................... 7
4) Data Reduction .................................................................................................................................................................................. 7
OUTCOME: Well-Formed Data ..................................................................................................................................................................... 7
Business Reporting .................................................................................................................................................................................................. 8
Standard Reporting ............................................................................................................................................................................................ 8
Ad-hoc Reporting ............................................................................................................................................................................................... 8
Process Business Reporting................................................................................................................................................................................ 8
Types of Business Reports.................................................................................................................................................................................. 8
Metric management reports ........................................................................................................................................................................ 8
Dashboard-Type Reports .............................................................................................................................................................................. 8
Balanced Scorecard-Type Reports ................................................................................................................................................................ 8
Data Visualization .................................................................................................................................................................................................... 8
Chart Types ........................................................................................................................................................................................................ 8
Market of BI & Visualization .............................................................................................................................................................................. 9
Visual Analytics .................................................................................................................................................................................................. 9
Dashboards ........................................................................................................................................................................................................ 9
Data Warehouse...................................................................................................................................................................................................... 9
Characteristics of Data Warehouses .................................................................................................................................................................. 9
Data Warehouse Development .......................................................................................................................................................................... 9
1) Inmon Model: EDW approach (top-down .......................................................................................................................................... 9
2) Kimball Mode: DM approach (bottom-top) ....................................................................................................................................... 9
3) Hosted DW ........................................................................................................................................................................................ 9
Data Warehouse Architecture ......................................................................................................................................................................... 10



1

, Data Mart......................................................................................................................................................................................................... 10
1) Dependent data mart ............................................................................................................................................................................ 10
2) Independent data mart ......................................................................................................................................................................... 10
Data Warehouse architecture decision ............................................................................................................................................................ 10
End-user tasks ....................................................................................................................................................................................................... 10
Organization change and data warehouses ..................................................................................................................................................... 11
Data Integration ......................................................................................................................................................................................... 11
ETL Process = Extract Transform Load ........................................................................................................................................................ 11
Purchasing an ETL Tool ............................................................................................................................................................................... 11
Multidimensionality in DW .............................................................................................................................................................................. 11
4 Dimensions: ............................................................................................................................................................................................. 11
Analysis of Data in Data Warehouse (OLTP vs OLAP) ....................................................................................................................................... 11
OLAP Operations: ....................................................................................................................................................................................... 12
Massive DW and Scalability ............................................................................................................................................................................. 12
Data Warehouse Security ................................................................................................................................................................................ 12
Data Warehouse Location choice .................................................................................................................................................................... 12
Future of Data Warehouse .............................................................................................................................................................................. 12
Data Lake ......................................................................................................................................................................................................... 12
Performance Management ................................................................................................................................................................................... 13
Three key components of performance management..................................................................................................................................... 13
Closed-Loop Process to optimize Business Performance ...................................................................................................................................... 13
1) Strategize (Where do we want to go?) ........................................................................................................................................................ 13
Levels of strategy: ....................................................................................................................................................................................... 13
Strategic planning common tasks: .............................................................................................................................................................. 14
Evaluate strategy ........................................................................................................................................................................................ 14
2) Plan (How do we get there?) ....................................................................................................................................................................... 15
3) Monitor/Analyze (How are we doing?) ........................................................................................................................................................ 15
4) Act and Adjust (What do we need to do differently?) ................................................................................................................................. 15
Performance Measurement .................................................................................................................................................................................. 16
KPIs and Operational Metrics........................................................................................................................................................................... 16
Performance Management System ................................................................................................................................................................. 16
Balanced Scorecard.......................................................................................................................................................................................... 17
Data Mining (Knowledge Discovery) ..................................................................................................................................................................... 17
How data mining works ................................................................................................................................................................................... 17
Data Mining Methods ...................................................................................................................................................................................... 18
1) Classification .................................................................................................................................................................................... 19
2) Clustering (Cluster Analysis) ............................................................................................................................................................ 19
3) Association Rule Mining (market-based analysis) ............................................................................................................................ 19
Data Mining Applications ................................................................................................................................................................................. 20
Text Analysis.......................................................................................................................................................................................................... 21
Text mining ...................................................................................................................................................................................................... 21
Text mining Process .................................................................................................................................................................................... 22
Natural Language Processing (NLP).................................................................................................................................................................. 22
Sentiment Analysis ................................................................................................................................................................................................ 23
Web Mining (Web Data Mining)............................................................................................................................................................................ 23


2

, Content/Structure/Web Usage Mining ............................................................................................................................................................ 23
Metrics ....................................................................................................................................................................................................... 24
Social Analytics (Social Network Analysis) ............................................................................................................................................................. 24
Social -vs- Industrial Media .............................................................................................................................................................................. 25
Use of SM over time ........................................................................................................................................................................................ 25
Prescriptive Analytics ............................................................................................................................................................................................ 25
Model-based decision making ......................................................................................................................................................................... 26
Levels of Risk in Decision Making ..................................................................................................................................................................... 27
How to Model Decisions .................................................................................................................................................................................. 27
Multiple Goals .................................................................................................................................................................................................. 27
Big Data ................................................................................................................................................................................................................. 29
Trends in BI ........................................................................................................................................................................................................... 30
IoT .................................................................................................................................................................................................................... 30
Cloud Computing ............................................................................................................................................................................................. 31
Location-Based Analytics ................................................................................................................................................................................. 31
Ethical Considerations ........................................................................................................................................................................................... 32




3

, Business Intelligence:
• Global Term
• Decision making
o Based on information tech

Changing Business Environments
• Increased capabilities
o Hardware,
o Software
o Network
• Group Communication and collaboration
• Data management
o Data warehouses
o Big Data
• Analytical Support
• Knowledge management
• Anywhere, anytime



Evolution of BI




Transaction Processing Versus Analytic Processing
• (Online) Transaction Processing (OLTP)
• Operational databases
• ERP, SCM, CRM, …
• Goal: data capture
• (Online) Analytical Processing (OLAP)
• Data warehouses
• Goal: decision support
• What is the relationship between OLTP and OLAP?



Investing in BI
• Strategic decision
o Cost-Benefit Analysis
o Make or buy
o Security?
• Protection of info and privacy
o Integration to other systems and Applications

• Many companies have dedicated department
o Manages how BI is linked go overall strategy
o Enables interaction between potential business users
o Shares practices and trains users
o Defines standards


4

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