Exception reporting with DataLever™

Exception reporting helps you create human-readable reports about the quality of your database or data feeds with respect to known business rules. These reports can answer questions such as: Do the column values fall within prescribed bounds? Is relational integrity maintained? Do textual values conform to patterns? Are keys unique? In order to identify defects in your data, you must be able to define what good data looks like, and then compare your data against this ideal.

DataLever makes it easy to review data elements, examining ranges of values, number of null records, duplicate records, compliance with structural rules, adherence to business logic, and inaccurately recorded information. All of these rules (and the DataLever processes for defining them) can also be used to reengineer the data once you've identified problems. DataLever has a rich expression language and a set of built-in functions used to perform common tasks. These tasks may include testing, string manipulation, pattern matching, mathematics, and date/time processing.

The results of your data tests can be combined into a printable report in HTML or text format, giving a quick summary of results that can be easily reviewed or emailed. Alternately, results of testing can be loaded into meta-data tables for further programmatic processing.