One of the most challenging aspects when trying to achieve effective BI solutions is the handling of poor data quality. Poor data quality can cause great damage as it might lead the organization to erroneous business decisions based on this data.

In order to avoid this dangerous outcome, organizations invest significant time and resources in manual correction actions of the data, involving long checking and rechecking of reports and never-ending analysis processes of their results.

This type of unstructured maintenance is extensively time consuming not to mention costly. And at the end of the day – still not fully proofed against mistakes.

DQA's features and capabilities

• A fully automated, ongoing quality assurance process.
• Based on data quality “meta data” maintaining a rule-based repository.
• Supports a wide variety of tests that are generated according to definitions established by the user through a GUI interface.
• Provides an engine to perform tests in an optimal manner.
• Handles huge amounts of data.
• Provides distribution methods, including online notification in push mode by SMS, e-mail, and in pull mode by creation of reports with results being handled according to their severity.
• Enables activating data cleansing methods such as referential integrity, missing values or plug numbers for financial systems matching.
  

The best data quality solution for BI & DW projects

• Incorporates unique tests for comparing amounts and attributes, accompanied by business logic, between source to target or target to target.
• Supports the ability to access and compare external sources and data.
• High volumes of data - can process more then 100GB daily, closing the “night window”.
• Influences process flow according to its results.
• Supported by a well-defined methodology and vast experience.

DQA architecture
DQA comprises two main logical areas:

1. DQA repository - a database maintaining all definitions of quality assurance processes and distribution definitions: tests, test parameters, timing and a distribution list according to subjects.

2. DQA log – a database that stores the results of all the tests which were performed during the data quality audit. The defined tests are performed using the "Data Quality Job" which retrieves the parameters from the DQA repository, executes the tests designed for the current processes, and documents all tests results in the DQA log.

DQA is a complete, out-of-the-box solution, seamlessly integrating into the existing loading processes.
DQA repository supports both Oracle and SQL server databases.