A data warehouse is simply a single, complete, and consistent store of data obtained from a variety of sources and made available to end users in a way they can understand and use it in a business context.”

1. Dr.Hiyam Hatem

2. Data Warehouse
Source Systems Data Staging Area Data Warehouse
(OLTP)
Data is periodically
extracted
Data is cleansed and
transformed
Users query the data
warehouse
A data warehouse is simply a single, complete, and
consistent store of data obtained from a variety of sources
and made available to end users in a way they can
understand and use it in a business context.”

3. Organizations’ use of data warehousing.
 A data warehouse is simply a single, complete, and
consistent store of data obtained from a variety of
sources and made available to end users in a way
they can understand and use it in a business
context.”
Dr. Hiyam Hatem
Data Warehouse

4. Inmon
 Father of the data
warehouse(1990)
 He has 35 years of experience in
database technology management
and data warehouse design.
 He has written about a variety of
topics on the building, usage, &
maintenance of the data
warehouse.
 He has written more than 650
articles and published 45 books.
Dr.Hiyam Hatem Data Warehouse

5. Organizations’ use of data warehousing.
Dr. Hiyam Hatem
Data Warehouse

6. Data warehouse: building blocks or
components.
Dr. Hiyam Hatem
Data Warehouse

7. Advantages of Warehousing
Approach
 High query performance
 But not necessarily most current information
 Doesn’t interfere with local processing at sources
 Complex queries at warehouse
 OLTP at information sources
 Information copied at warehouse
 Can modify, annotate, summarize, restructure, etc.
 Can store historical information
 Security, no auditing
 Has caught on in industry
Dr.Hiyam Hatem
Data Warehouse

8. Generic Warehouse
Architecture
Dr.Hiyam Hatem Data Warehouse
Extractor/
Monitor
Extractor/
Monitor
Extractor/
Monitor
Integrator
Warehouse
Client Client
Design Phase
Maintenance
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Metadata
Optimization
Query & Analysis

9. Data Warehouse
 In order for data to be effective, DW must be:
 Consistent.
 Well integrated.
 Well defined.
 Time stamped.
 DW environment:
 The data store, data mart & the metadata.
Dr.Hiyam Hatem Data Warehouse

10. The Data Store
 An operational data store (ODS) stores data for
a specific application. It feeds the data
warehouse a stream of desired raw data.
 Is the most common component of DW
environment.
 Data store is generally subject oriented, volatile,
current commonly focused on customers,
products, orders, policies, claims, etc…
Dr.Hiyam Hatem Data Warehouse

11. Data Store & Data Warehouse
 Data store & Data warehouse
Dr.Hiyam Hatem Data Warehouse

12. The Storage
 Relational databases
 Measurements are numbers that quantify the business
process
 Dimensions are attributes that describe measurements
 Its day-to-day function is to store the data for a single
specific set of operational application.
 Its function is to feed the data warehouse data for the
purpose of analysis.
Dr.Hiyam Hatem Data Warehouse

13. The Data Mart
 It is lower-cost, scaled down version of the DW.
 Data Mart offer a targeted and less costly method of
gaining the advantages associated with data
warehousing and can be scaled up to a full DW
environment over time.
Dr.Hiyam Hatem Data Warehouse

14. The Meta Data
 Last component of DW environments.
 It is information that is kept about the warehouse
rather than information kept within the
warehouse.
 Legacy systems generally don’t keep a record of
characteristics of the data (such as what pieces of
data exist and where they are located).
 The metadata is simply data about data.
Dr.Hiyam Hatem Data Warehouse

15. Metadata
 Database that describes various aspects of data in the
warehouse
 Administrative Metadata: Source database and
contents, Transformations required, History of
Migrated data
 End User Metadata:
Definition of warehouse data
Descriptions of it
Consolidation Hierarchy
Dr.Hiyam Hatem Data Warehouse

16.  OLTP: On Line Transaction Processing
 Describes processing at operational sites
 OLAP: On Line Analytical Processing
 Describes processing at warehouse
OLTP vs. OLAP
Dr.Hiyam Hatem Data Warehouse

17. Warehouse is a Specialized DB
Standard DB (OLTP)
 Mostly updates
 Many small transactions
 Mb - Gb of data
 Current snapshot
 Index/hash on p.k.
 Raw data
 Thousands of users (e.g.,
clerical users)
Dr.Hiyam Hatem Data Warehouse
Warehouse (OLAP)
 Mostly reads
 Queries are long and complex
 Gb - Tb of data
 History
 Lots of scans
 Summarized, reconciled data
 Hundreds of users (e.g.,
decision-makers, analysts)