Testing in data warehouse projects are till date a less explored area. However, if not done properly, this can be a major reason for data warehousing project failures - especially in user acceptance phase. Given here a mind-map that will help a project manager to think all the aspects of testing in data warehousing.

Testing Mindmap

DWBI Testing

Points to consider for DWBI Testing

  1. Why is it important?

    • To bug-free the code
    • To ensure data quality
    • To increase credibility of BI Reports
    • More BI projects fail after commissioning due to quality issue

  2. What constitutes DWBI Testing?

    • Performance Testing
    • Functional Testing
    • Canned Report Testing
    • Ad-hoc testing
    • Load Reconciliation

  3. What can be done to ease it?

    • Plan for testing
    • Start building DWBI Test competency
    • Design code that generates debug information
    • Build reconciliation mechanism

  4. Why is it difficult?

    • Limited Testing Tool
    • Automated Testing not always possible
    • Data traceability not always available
    • Requires extensive functional knowledge
    • Metadata management tool often fails
    • Deals with bulk data - has performance impact
    • Number of data conditions are huge

Use the above mind-map to plan and prepare the testing activity for your data warehousing project.


Have a question on this subject?

Ask questions to our expert community members and clear your doubts. Asking question or engaging in technical discussion is both easy and rewarding.

Are you on Twitter?

Start following us. This way we will always keep you updated with what's happening in Data Analytics community. We won't spam you. Promise.

  • Decision Support System (DSS)

    Decision Support System (DSS) is a class of information systems (including but not limited to computerized systems) that support business and organizational decision-making activities. A properly designed DSS is an interactive software-based system...

  • Top 10 things to avoid in DWBI project management

    Watch this space...

  • Business Intelligence

    In a 1958 article, IBM researcher Hans Peter Luhn used the term business intelligence. He defined intelligence as: "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."

  • Why people Hate Project Managers – A must read for would-be managers

    "Project Managers" are inevitable. Love them or hate them, but if you are in a project, you have to accept them. They are Omnipresent in any project. They intervene too much on technical things without much knowledge. They create unrealistic...

  • Top 5 Challenges of Data Warehousing

    Data warehousing projects are one of its kinds. All data warehousing projects do not pose same challenges and not all of them are complex but they are always different. This article illustrates the top 5 challenges that often plague modern data...

  • Data Retention and Purging in a Data Warehouse

    By the typical definition of data warehouse, we expect the data warehouse to be non-volatile in nature for its entire design life time. As long as it remain operation, all data loaded in the data warehouse should remain there for the purpose of...

  • Top 10 things you must know before designing a data warehouse

    This paper outlines some of the most important (and equally neglected) things that one must consider before and during the design phase of a data warehouse. In our experience, we have seen data warehouse designers often miss out on these items...

  • What is a data warehouse - A 101 guide to modern data warehousing

    This article discusses data warehousing from a holistic standpoint and quickly touches upon all the relevant concepts that one needs to know. Start here if you do not know where to start from.

  • What is Data Warehousing?

    A data warehouse is a repository of an organization's electronically stored data. Data warehouses are designed to facilitate reporting and analysis.

  • Enterprise Data Warehouse Data Reconciliation Methodology

    An enterprise data warehouse often fetches records from several disparate systems and store them centrally in an enterprise-wide warehouse. But what is the guarantee that the...