1. DATABASES AND DATA WAREHOUSES
Building Business Intelligence

2. INTRODUCTION Businesses need business intelligence (BI)
Business intelligence – knowledge about your customers, competitors, business partners, environment, and internal operations
Enables effective decision making
Information on steroids
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3. INTRODUCTION
IT tools help process information to create business intelligence according to…
OLTP (online transaction processing)
OLAP (online analytical processing)
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4. INTRODUCTION
OLTP – gathering and processing transaction information and updating existing information to reflect transaction
Databases support OLTP
Operational database – database that supports OLTP
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5. INTRODUCTION
OLAP – manipulation of information to support decision making
Databases can help some
Data warehouses support only OLAP, not OLTP
Data warehouses – special forms of databases that support decision making
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6. DATA WAREHOUSES & DATA MINING
Data warehouses support OLAP and decision making
Data warehouses do not support OLTP
Data-mining tools are tools for working with data warehouse information
DBMS software = database
Data-mining tools = data warehouse
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7. What Is a Data Warehouse?
Data warehouse – logical collection of information – gathered from operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks
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8. What Is a Data Warehouse?
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9. What Is a Data Warehouse?
Multidimensional
Rows and columns
Also layers
Many times called hypercubes
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10. What Are Data-Mining Tools?
Data-mining tools – software tools that you use to query information in a data warehouse
Query-and-reporting tools
Intelligent agents
Multidimensional analysis tools
Statistical tools
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11. What Are Data-Mining Tools?
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12. Query-and-Reporting Tools
Query-and-reporting tools – similar to QBE tools, SQL, and report generators in the typical database environment
Also similar to pivot tables in Excel
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13. Intelligent Agents
Use various Artificial Intelligence tools such as neural networks and fuzzy logic to form the basis for “information discovery” and building BI
Help you find hidden patterns in information
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14. Multidimensional Analysis Tools
Multidimensional analysis (MDA) tools – slice-and-dice techniques that allow you to view multidimensional information from different perspectives
Bring new layers to the front
Reorganize rows and columns
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15. Statistical Tools
Help you apply various mathematical models to the information stored in a data warehouse to discover new information
Regression
Analysis of variance
And so on
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16. Data Marts Data warehouses are organizationwide
Data marts have subsets of an organizationwide data warehouse
Data mart – subset of a data warehouse in which only a focused portion of the data warehouse information is kept
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17. Data Marts McGraw-Hill
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18. Data Mining as a Career Opportunity
Knowledge of data mining can be a substantial career opportunity for you
Business Objects
SAS
Cognos
Informatica
Many others
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19. Considerations in Using a Data Warehouse
Do you need a data warehouse?
DBMS may offer all you need
Do all employees need the entire data warehouse?
Consider a data mart
How up-to-date must information be?
“Snapshot” concept
What data-mining tools do you need?
Training can be expensive
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20. INFORMATION OWNERSHIP
Strategic management support
The sharing of information with responsibility
Information cleanliness
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21. The Sharing of Information with Responsibility
If you create it, you “own” it
You will also share it with others
Because you “own” it, you are responsible for its quality
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22. Information Cleanliness
Database and data warehouse information must be “clean”
No errors
No duplicates
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23. Information Cleanliness
Extraction, transformation, and loading (ETL) – what information you want from each database, how the information is associated, and what rules to follow in consolidating the information to ensure its cleanliness in a data warehouse
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