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Data profiling tools for Excel
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.
WinPure Clean & Match
The Data Profiling / Statistics module within WinPure Clean & Match is a user-friendly and powerful data profiling tool that can help your business to discover patterns and meaning in your data and to check the quality of your data by analyzing formats, types, completeness, and value counts. It presents you with a complete set of statistics that you can use to help clean and correct your data, and to prepare it better for data matching.
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| Commercial: | Commercial |
| Desktop/Cloud: | Desktop |
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| Runs on: (for desktop): | Windows |
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| Statistics of data: | - |
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Astera Centerprise
Astera Centerprise is an end-to-end data integration software that enables you to integrate, cleanse, and transform data in a code-free environment. Its built-in data profiling feature lets you easily examine your source data and get detailed information about its structure, quality, and integrity. Custom data integration and quality rules can also be defined to validate incoming data and identify missing or invalid records.
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| Commercial: | Commercial |
| Desktop/Cloud: | Desktop |
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| Runs on: (for desktop): | Windows |
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| Statistics of data: | Avg,Max,Min |
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DataCleaner
The heart of DataCleaner is a strong data profiling engine for discovering and analyzing the quality of your data. Find the patterns, missing values, character sets and other characteristics of your data values.
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| Commercial: | Free |
| Desktop/Cloud: | Desktop |
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| Runs on: (for desktop): | Linux,Mac OS,Windows |
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| Statistics of data: | - |
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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.
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| Commercial: | Commercial |
| Desktop/Cloud: | Desktop |
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| Runs on: (for desktop): | Linux,Mac OS,Windows |
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| Statistics of data: | Avg,Max,Min,Stdev |
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OpenDQ
OpenDQ integrates data profiling, standardization, enhancement, fuzzy matching, and de-duplication components with enterprise-class data extraction, transformation, and loading software, to create a comprehensive and complete view of enterprise data. It lets you identify your data’s current state, resolve missing values/erroneous values, discover formats and patterns, reveal hidden business rules, report on column minimums, averages, and maximums, measure business rule compliance across data sets, and provide point in time data profiling history.
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| Commercial: | Free |
| Desktop/Cloud: | Desktop |
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| Statistics of data: | Avg,Max,Min |
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MIOvantage
MIOvantage is a single solution platform that lets you profile data, run rules, deduplicate data, identify entities, generate reports, and more. From entity resolution to complex deduplication, MIOvantage builds a better, clearer picture from your data.
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| Commercial: | Commercial |
| Desktop/Cloud: | Desktop |
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Trifacta
Trifacta is an open and interactive cloud platform for data engineers and analysts to collaboratively profile, prepare, and pipeline data for analytics and machine learning. For ease of data profiling, Trifacta automatically identifies dataset formats, schemas, specific attributes, and relationships across attributes and datasets, along with associated metadata for each dataset.
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| Commercial: | Commercial |
| Desktop/Cloud: | Cloud |
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| Statistics of data: | Avg,Max,Min,Stdev |
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StarDQ
StarDQ is a powerful enterprise solution for profiling, cleansing, augmenting, and standardizing the data to significantly improve returns on corporate intelligence initiatives.
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| Commercial: | Commercial |
| Desktop/Cloud: | Cloud |
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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.