Data profiling is the process of reviewing source data, understanding structure, content and interrelationships, and identifying potential for data initiatives. You profile data to determine the accuracy, completeness, and validity of your data. Data profiling can be done for many reasons, but it is most commonly part of helping to determine data quality.

Data Profiling can’t get any easier than using a simple 3 step approach:

1 – Discover Metadata

2 – Select Data Object and Columns

3 – Run Data Profiling

Collect comprehensive profiling information with one single click.

Column Analysis helps to discover metadata information, minimum and maximum value, plus column length distribution.

Profile Quality enables to measure the amount and percentage of nullable, duplicates, distinct, unique & non-unique values.

Metadata Index helps to assess whether known metadata accurately describes the actual values of the data profiling object and to understand data challenges early.

Single-dimension index provides frequency distribution of different values.

Multi-dimension index exposes embedded value dependencies in a cross-columns analysis.

Need to have data profiling results for further analysis in Excel? No problem, all information can be exported.