Testing Data Warehouse

Testing data warehouse implementations has become an important part of enabling a data warehouse to deliver superior business intelligence. Testing data warehouse projects typically involves verifying data completeness, ensuring data transformation, evaluating data quality and performing regression testing.

While testing data warehouse solutions is a critical step in getting value from the data warehouse environment, traditional testing tools have tended to be cumbersome, inefficient and time-consuming, driving up the cost and reducing the value of testing methodologies.

For enterprises seeking an easier, faster and more affordable solution for testing data warehouse implementations, Qlik (Attunity) provides an industry-leading solution.

Qlik (Attunity) for designing, development and testing data warehouse projects

Qlik (Attunity) automates steps fordesigning, influencing and testing data warehouse implementations, as well as data marts or a cloud data warehouse. By automating data modeling, ETL generation and workflow, Qlik (Attunity) enables an agile data warehouse and minimizes manual and error-prone data warehouse design, and enables project managers and data architects to optimize processes, accelerate analytics and reduce risk.

When testing data warehouse projects, Qlik (Attunity) accelerates testing initiatives with the ability to create and deploy project packages directly from the user interface. Qlik (Attunity) also provides additional key operational features that include:

  • A built-in workflow designer and scheduler that runs all data warehouse and data mart ETL tasks as a single end-to-end process.
  • Monitoring and notification features that monitor the status of all automatically generated tasks and workflows and proactively manage their environment by configuring automatic notification messages.
  • Lineage and impact analysis tools that automatically create metadata during design phases or during implementation processes. Qlik (Attunity) provides a visual map of data flow from source to data warehouse and data marts to simplify planning and monitoring.
  • Centralized and automated version control features, enabling developers to easily roll back to earlier versions of a project while minimizing disruption to other team members.

Benefits for testing data warehouse implementations

Using Qlik (Attunity) for designing, deploying and testing data warehouse projects, enterprises can:

  • Easily extract and sink data from sources. Administrators can load source feeds in real time with database CDC, while zero footprint technology requires no agent on source systems.
  • Automate model design and source mapping. Qlik (Attunity) allows administrators to create or import data models, modify and enhance the data model iteratively and automatically map sources to data models.
  • Generate data warehouse and ETL automatically. Qlik (Attunity) auto-generates ETL code to populate and load data warehouses and data marts.
  • Deploy data marts without manual coding. With Qlik (Attunity), administrators can define and manage data marts with a few clicks of a mouse.