Ataccama - DQ Analyzer Overview
Easy, powerful data profiling and analysis
A critical task for today’s businesses of every size is identifying data issues before they become business issues. DQ Analyzer (DQA) combines advanced data profiling and analysis capabilities with a point-and-click interface that is simple enough for business managers to use without extensive training.
Features of DQA
- Speed. Analyze millions of records in a matter of minutes.
- Ease of use. Start profiling immediately using an easy-to-use wizard interface.
- Flexibility. Use files or databases as an input.
- Powerful. Get much more than "standard" data profiling statistics—such as pattern analysis, business rules checks, and drill-through capabilities using an embedded relational database.
- Handles unstructured data. Parse and standardize cluttered data fields.
- Preprocessing. Prepare your data before analyzing it—split it, join multiple sources, add new columns, or calculate values.
- Rich expression language. Unlimited flexibility is based on the rich expression language, including regular expressions, which can assist users with validating formats and identifying specific strings of data within unstructured text.
Using DQ Analyzer is easy and convenient for beginners and seasoned data gurus alike. A wizard-like user interface for quick tasks is complemented by standard Ataccama configuration plans for advanced use.
DQ Analyzer allows you to profile millions of records in a matter of minutes without the need to consume database processing time. This means that you can use data profiling at the time when you really need it, instead of waiting overnight to obtain your results.
Use regexp, business rules and rich expression language
If you know what these terms mean, you know how powerful they are. Parsing, standardization, preprocessing of data, joining multiple data sources—it's all available for advanced users.
With the "drill-through" feature, you can easily identify particular records in the source data behind each profile statistic, be it frequency analysis, domain analysis, or duplicate records.