ETL Testing or Data Warehouse Testing has a vital role to play for companies as they try to leverage the opportunities hidden in the data.

When referring to business intelligence quality assurance, we often discover that the terms data warehouse (DWH) testing and ETL Testing are used interchangeably as though they are the same.

Data warehousing continues to gain importance as organizations become more fully aware of the benefits of data-driven, business-decision making. One primary element of an efficient data warehouse system is an ETL process that can reliably extract, transform, cleanse, and load data from source systems during normal operation without impacting overall performance, scalability, or reliability.

Often, data quality defects are introduced much earlier, during the multiple stages of warehouse development. Fast-track projects that move rapidly through development and implementation can be especially prone to the unintentional injection of defects.

TRUGlobal’s Data Warehouse and ETL Testing Services provide your team with the necessary expertise, oversight, and hands-on efforts to test throughout the requirements, design, and deployment cycles to discover defects before they even occur. Our goal is to provide your team with an overall Software Quality Analysis process (SQA – e.g., DWH testing strategy/approach, system test plan, test cases, test schedule, defect reports, and metrics). And, as a world-class QA company, we will help your business to catch defects (e.g., database design, source data, ETL process, data quality) early, to help reduce your costs and lower your risks.

TRUGlobal Data warehouse

Key Challenges that we solve:

Testing a data warehouse is challenging and complex. Some of the main challenges to test for when building a data warehouse are:

  • Data Completeness
  • Data Transformation
  • Data Quality
  • Regression Testing

The only way to perform these tests in a reasonable time frame, which will compare huge volumes of data, is through automating the tests.

ETL & DWH Testing tools:

To ensure that we reach the customer expectation level, we work with a wide range of tools that include:

  • RightData
  • QuerySurge
  • QualiDI
  • Data Centric Testing
  • TestBench
  • GTL QAceGen
  • Datagaps ETL Validator
  • Informatica Data Validation

ETL testing includes different types of testing for its three different processes (extract, transform, load).

Data extraction tests checks are:

  • Data extraction code is granted security access to each source system
  • Updating of extract audit logs and time stamping is accomplished
  • Data can be extracted from each required source field
  • All extraction logic for each source system works as required
  • Source to extraction destination is working in terms of completeness and accuracy
  • All extractions are completed within the expected timeframe

Data transformation tests checks are:

  • Transaction processes are transforming the data according to the expected rules and logic
  • One-time transformation for historical initial loads is working
  • Detailed and aggregated data sets are created successfully
  • Transaction audit logs and time stamping are recorded
  • There is no data loss or corruption of data during transformations
  • Transformations are completed within the expected timeframe

Data loading testing might check are:

  • There is no data loss or corruption during the loading process
  • All transformations during loading work as expected
  • Data sets in staging to loading destination work without data loss
  • Incremental data loads work with change data capture
  • Transaction audit logs and time stamping are recorded
  • Loads are completed within the expected timeframe

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