Data Quality begins with Data Profiling

Data Profiling is the cornerstone of managing enterprise data quality for better business insights out of high-volume data !!

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Tools for Automated Data Profiling

Data Profiling helps data teams to understand the data from a statistical point of view, which is the primary action to ensure the right quality data is consumed for analytics. The following are the list of tools for automating the data profiling process.

IBM Infosphere Information Analyzer

A tool with extensive data profiling capabilities (column Analysis, format analysis, completeness and validity analysis), which helps in identifying missing, incorrect, bad and redundant data before starting a data integration project, There is a dependency on QualityStage for name and address profiling.

Informatica Data Explorer

This tool employs powerful data profiling capabilities to scan every single data record, from any source, to find anomalies and hidden relationships. It is available in 2 versions (Standard and Advanced)

Talend Data Preparation

Talend Data Preparation is a data quality tool which is available as an open source and subscription version. This tool profiles the data and provides a graphical drill-down of the details. It comes with advanced features like Column set analysis, Advanced matching analysis, Time column correlation analysis.

SAS Dataflux Data Management Studio

DataFlux Data Management Studio enables to establish an effective data governance platform, by providing a powerful interface for data profiling, where users can execute a complete assessment of an organization's data, examining the structure, completeness, suitability and relationships of the information assets.

Ataccama ONE

This tool helps to dive deep inside data and see detailed information about any attribute and easily decide what to do next, with profiling on duplicate counts, patterns & masks, primary key analysis, and numeric statistics.

Melissa Data Profiler

This promises to enhance data governance and data warehousing efforts through its data profiling capabilities like metadata repository for resolving data ambiguities and rules management for standardization of incoming data.


This tool has automated data profiling and intuitive visual exploration capabilities that promises to save 50% of the time that is currently spent on data exploration. With an open API architecture, data quality based rules and SLAs can be integrated into ETL tools, pipelines & BI dashboards.

Data profiling brings amazing levels of foresight in data quality management.

Automated data profiling is critical when stakes are high in terms of user’s dependency on analytics for decision making

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