This document discusses testing of data warehouses. It outlines different types of data warehouse testing including testing the extraction, transformation, and loading (ETL) process. The document recommends checking data quality by ensuring completeness and proper data transformation according to business rules. It identifies four important aspects of data warehouse testing: recognizing the importance of testing, planning test phases, planning QA staffing, and avoiding risks. Key focus points for testing include underlying data and different data warehouse components. The challenges of data warehouse testing include data selection from multiple sources, large data volumes and complexity, inconsistent data, lack of a comprehensive test bed, and the critical nature of the data for business decisions.

1. TESTING A DATA WAREHOUSES
SUBMITTED
TO
DR. HIMANSHU HORA
SUBMITTED
BY
TANMI KAPOOR
&
SHANTANU CHAKRABORTY
M.TECH (Software Engineering)

2. CONTENTS
1.
2.
3.
4.
5.
6.
7.
8.
Data Ware House
Testing Data Warehouses
Data Warehouse Testing Type
Data Warehouse Testing Process
Four Things To Do
Data Warehouse Testing: Focus Points
Data Base Testing vs Data Ware House Testing
Challenges for Testing a Data Warehouse

3. Data Ware House

“Subject-oriented, integrated, timevarying, non-volatile
collection of data that is used primarily in organizational
decision making”

Historical Data for decision support

Seperate from organization’s operational databases (OLTP)

4. Testing Data Warehouses





Organizations today need data warehouse testing more than
ever before.
Organizations are focusing testing on the ETL
(extraction, transformation, load) process, business
intelligence infrastructures, and applications that rely on data
warehouses.
Check the quality of the data
Data Completeness: Ensures that all the expected data is
loaded
Data Transformation: Ensures that all data is transformed
correctly according to business rules and/or design
specifications.

5. Testing Data Warehouses: Best Practices

6. Data Warehouse Testing Type

7. Data Warehouse Testing Process

8. Four Things To Do
1.
Recognizing the importance of testing
2.
Planning the phases for testing
3.
Planning for QA staffing
4.
Avoiding risks

9. Data Warehouse Testing: Focus Points
1. Underlying Data

10. 2. Data Warehouse Components

11. Data Base Testing vs Data Ware House Testing

12. Challenges for Testing a Data Warehouse

Data selection from multiple source systems.

Volume and the complexity of the data.

Inconsistent and redundant data in a data warehouse.

Non-Availability of comprehensive test bed.

Critical data for Business.

13. SUBMITTED
BY
tANMI KAPOOR&
SHANTANU CHAKRABORTY
M.TECH (Software Engineering)