Business Intelligence, Analytics, and Data Science
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
Test Bank For Business Intelligence, Analytics, and Data Science: A Managerial Perspective 4th Edition by Sharda; Delen & Turban, ISBN: 9780134633282, All 8 Chapters Covered, Verified Latest Edition
Test Bank For Business Intelligence, Analytics, and Data Science: A Managerial Perspective 4th Edition by Sharda; Delen & Turban, ISBN: 9780134633282, All 8 Chapters Covered, Verified Latest Edition
Test Bank For Business Intelligence, Analytics, and Data Science: A Managerial Perspective 4th Edition by Sharda; Delen & Turban All 1-8 Chapters Covered ,Latest Edition, ISBN:9780134633282
Alles voor dit studieboek
(14)
Geschreven voor
Fontys
International Business
Business Intelligence
Alle documenten voor dit vak (2)
Verkoper
Volgen
lennartfuchs
Voorbeeld van de inhoud
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
Voordelen van het kopen van samenvattingen bij Stuvia op een rij:
Verzekerd van kwaliteit door reviews
Stuvia-klanten hebben meer dan 700.000 samenvattingen beoordeeld. Zo weet je zeker dat je de beste documenten koopt!
Snel en makkelijk kopen
Je betaalt supersnel en eenmalig met iDeal, creditcard of Stuvia-tegoed voor de samenvatting. Zonder lidmaatschap.
Focus op de essentie
Samenvattingen worden geschreven voor en door anderen. Daarom zijn de samenvattingen altijd betrouwbaar en actueel. Zo kom je snel tot de kern!
Veelgestelde vragen
Wat krijg ik als ik dit document koop?
Je krijgt een PDF, die direct beschikbaar is na je aankoop. Het gekochte document is altijd, overal en oneindig toegankelijk via je profiel.
Tevredenheidsgarantie: hoe werkt dat?
Onze tevredenheidsgarantie zorgt ervoor dat je altijd een studiedocument vindt dat goed bij je past. Je vult een formulier in en onze klantenservice regelt de rest.
Van wie koop ik deze samenvatting?
Stuvia is een marktplaats, je koop dit document dus niet van ons, maar van verkoper lennartfuchs. Stuvia faciliteert de betaling aan de verkoper.
Zit ik meteen vast aan een abonnement?
Nee, je koopt alleen deze samenvatting voor €6,49. Je zit daarna nergens aan vast.