Data profiling tools for Big Data

Data Profiling tools allow analyzing, monitoring, and reviewing data from existing databases in order to provide critical insights. Data profiling can help organizations improve data quality and decision-making process by identifying problems and addressing them before they arise.

Dataedo

Dataedo is a metadata management & data catalog tool with a data profiling feature. It allows you to use sample data to learn what data is stored in your data assets. You can browse min, max, average and median values, see top values, as well as value and row distribution to understand the data better before using it.

Access control: Yes
Commercial: Commercial
Desktop/Cloud: Desktop
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): Windows
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: Avg,Max,Min,Stdev
Tagging data: -
Dataedo Data Profiling
Data Profiling in Desktop

Talend Data Fabric

Talend Data Fabric combines data integration, integrity, and governance in a single, unified platform. Talend Data Fabric's capabilities allow you to extract, process, and profile data from virtually any source to your data warehouse. Data profiling lets you quickly identify data quality issues, discover hidden patterns, and spot anomalies through summary statistics and graphical representations.

Access control: No
Commercial: Commercial
Desktop/Cloud: Desktop
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): Mac OS,Windows
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: -
Tagging data: Yes

Informatica Data Profiling

Informatica’s data profiling solution, Data Explorer, is available in two editions—Standard and Advanced—that employ powerful data profiling capabilities to scan every single data record, from any source, to find anomalies and hidden relationships. It works regardless of complexity or of the relationship between your data sources.

Access control: No
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): -
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: Avg,Max,Min,Stdev
Tagging data: Yes

The use of data profiling tools can lead to higher-quality, more reliable data or eliminating errors that add costs to data-driven projects. Eliminating these costly errors involve processes such as:

• Collecting descriptive statistics.
• Collecting data types, length and recurring patterns.
• Tagging data with keywords, descriptions or categories.
• Performing data quality assessment.
• Discovering metadata and assessing its accuracy.

The most efficient way of handling the data profiling process is to automate it with a data management solution. We prepared a list of open-source data profiling tools that help you carry out the analysis of your data and identify the issues.