1. Chapter 5 Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analytics, and Visualization

2. How to leverage all the data that organizations collect and store?
Answer
Data warehousing
Data acquisition (access)
Data mining
Online analytical processing (OLAP) or Business Analytics
Data Visualization

3. Data, Information, Knowledge
Items that are the most elementary descriptions of things, events, activities, and transactions
May be internal or external
Information
Organized data that convey meaning and value
Knowledge
Processed data or information that conveys understanding, experience, accumulated learning and expertise applicable to a problem or activity

4. What kinds of Data Issues organizations deal with?
Multiple sources
Wide time frame
Data reduction (aggregation)
Various levels of detail
Various amounts of data
Varying degrees of accuracy
Provide random access to database
Security and private databases
End user interface (i.e., ability to interface two or more databases at a time)

6. Preparing data for Warehousing
Cleanse data
When populating warehouse
Data quality action plan
Best practices for data quality
Measure results
Data integrity issues
Uniformity
Version
Completeness check
Conformity check
Genealogy or drill-down

7. Preparing data for Warehousing
Data Integration
Access needed to multiple sources
Often enterprise-wide
Disparate and heterogeneous databases
XML becoming language standard
Web (external data source)
Intelligent agents
Document management systems
Content management systems
External Commercial databases
Sell access to specialized databases

8. Database Models Hierarchical Network Relational Object oriented
Top down, like inverted tree
Fields have only one “parent”, each “parent” can have multiple “children”
Fast
Network
Relationships created through linked lists, using pointers
“Children” can have multiple “parents”
Greater flexibility, substantial overhead
Relational
Flat, two-dimensional tables with multiple access queries
Examines relations between multiple tables
Flexible, quick, and extendable with data independence
Object oriented
Data analyzed at conceptual level
Inheritance, abstraction, encapsulation

9. Database Models Multimedia Based Document Based Intelligent
Multiple data formats
JPEG, GIF, bitmap, PNG, sound, video, virtual reality
Requires specific hardware for full feature availability
Document Based
Document storage and management
Intelligent
Intelligent agents and ANN
Inference engines

10. What is Data Warehousing?
Is the process of taking internal and/or external data, cleansing it and storing it in a data warehouse where it can be accessed by various decision makers in the decision support process.
A data mart is a part of a data warehouse containing a subject area data.
Data warehousing solves the data acquisition or access problem.
The end users perform ad hoc query, reporting, analysis and visualization on the data warehouse or on one or more data marts.

12. Business Intelligence and Analytics
Acquisition of data and information for use in decision-making activities
Business analytics
Models and solution methods
Data mining
Applying models and methods to data to identify patterns and trends

13. What is Multidimensionality?
It is the ability to present in one screen or table several dimensions, e.g., Sales by region, by city, by product, by time period, by salesperson (5 dimensions), and it can be easily changed for different presentations of dimensions.
Data organized according to business standards, not analysts – for slicing and dicing them to gain new insights.

14. What is OLAP?
A database-oriented DSS which uses data warehouse and a set of tools usually with multidimensional capabilities to aid in reporting, querying and data analysis.
Activities performed by end users in OLAP systems
Specific, open-ended query generation
SQL
Requesting Ad hoc reports
Conducting Statistical and other (e.g. data mining) analyses
Building DSS applications
Modeling and visualization capabilities
OLAP tools fall into four product groups:
Multidimensional spreadsheets
Multidimensional query & report writing tools for standard RDMS (e.g., Business Objects)
Fully multidimensional DBMS
Visual information access systems

15. What is Data Mining?
A term used to describe knowledge discovery in databases
Requires accessibility from a user’s workstation to data that may reside in different locations (e.g., corporate warehouse, servers)
Statistical, mathematical, artificial intelligence, and machine-learning techniques are used to identify new patterns in data for knowledge discovery
Automatic, uses intelligent search, and fast

16. Data Mining (contd.) Data mining application classes of problems
Classification
Clustering
Association
Sequencing
Regression
Forecasting
Others
Data mining application areas
Marketing
Banking
Insurance
Health care
Law enforcement
Government and defense

17. What is an Intelligent Database?
Provides the user with an easy access to data
Allows to do complex operations without much user input – the user specifies what she is looking for, and an intelligent agent can execute the request
Business Objects is an example of an intelligent database
“Objects” are created by IS professionals to represent elements in databases such as customers, products or locations. Users click on the objects and business objects automatically generates and executes the appropriate SQL queries

18. Data Visualization
Technologies supporting visualization and interpretation
Digital images (maps), GIS, GUI, tables, multidimensionality, graphs, VR (virtual reality), 3D, animation
Identify relationships and trends
Data manipulation allows real time look at performance data

19. Analytic systems Real-time queries and analysis
Real-time decision-making
Real-time data warehouses updated daily or more frequently
Updates may be made while queries are active
Not all data updated continuously
Deployment of business analytic applications

20. GIS
Computerized system for managing and manipulating data with digitized maps
Geographically oriented
Geographic spreadsheet for models
Software allows web access to maps
Used for modeling and simulations

22. Web Analytics/Intelligence
Application of business analytics to Web sites
Web intelligence
Application of business intelligence techniques to Web sites