Data profiling tools for Informix

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

Global IDs Data Profiling Suite

Global IDs Data Profiling Suite is a data discovery and profiling tool that automates the discovery of data assets, automates data profiling, and provides an active inventory of all data assets.

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): Linux
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: -
Tagging data: Yes

IBM InfoSphere Information Analyzer

IBM InfoSphere Information Analyzer provides data profiling and analysis to accurately evaluate the content and structure of your data for consistency and quality. It utilizes a reusable rules library and supports multi-level evaluations by rule record and pattern. It also facilitates the management of exceptions to established rules to help identify data inconsistencies, redundancies and anomalies, and make inferences about the best choices for structure.

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): Linux,Windows
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: Avg,Stdev
Tagging data: Yes

Aperture Data Studio

Aperture Data Studio is a powerful and easy-to-use data management suite that helps you quickly and easily profile data to understand deficiencies as an essential first step to cleansing, joining, and validating data. It profiles the complete data set and audits every step in readiness for statutory reporting and enhanced transparency of data and processes, de-risking compliance initiatives.

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

Trillium Discovery

Trillium Discovery provides industry-leading data profiling at scale, designed specifically to meet the challenges presented by today’s data environments, with native connectivity to cloud and big data sources to execute data profiling tasks. It lets you visually assess the quality of your data and support data governance with comprehensive profiling, customized to your business

Access control: No
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: No
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: -
Tagging data: No

CloverDX

CloverDX Data Profiler is a CloverDX module that lets you perform various analyses of your data. It is a part of CloverDX Designer and helps to do various profiling tasks, such as finding the maximum value, median, the most unique value, and many others.

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): Linux,Mac OS,Windows
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: Avg,Max,Min,Stdev
Tagging data: No

SAS Data Quality

SAS Data Quality gives you a single interface to manage the entire data quality life cycle: profiling, standardizing, matching, and monitoring. It lets you validate data against standard measures and customized business rules. Uncover relationships across tables, databases, and source applications. Verify that the data in your tables matches the appropriate description. Establish trends and commonalities in business information and examine numerical trends via mean, median, mode, and standard deviation.

It makes it easy to profile and identify problems, preview data, and set up repeatable processes to maintain a high level of data quality.

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

Alation Data Catalog

Alation’s data profiling capabilities help reduce the time spent in the data exploration phase. With Alation’s data profile, data consumers have the metrics they need to easily discern the quality of any data object. Alation displays important characteristics, statistics, and numerical graphs about the data — enabling data scientists and data engineers to quickly take action. The data profiling now also includes new charts and customizations.

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