SQL Server
Oracle
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Amazon Redshift
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IBM DB2
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SAP HANA
Snowflake
SQLite
Teradata
Vertica
Data profiling tools for Sisense
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.
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.
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| Commercial: | Commercial |
| Desktop/Cloud: | Desktop |
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| Runs on: (for desktop): | Mac OS,Windows |
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| Statistics of data: | - |
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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: |
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| Commercial: | Commercial |
| Desktop/Cloud: | Cloud |
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| Runs on: (for desktop): | - |
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| Statistics of data: | - |
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Atlan
Atlan automatically profiles your data to identify missing values, outliers & other data anomalies. Data profiles are fully configurable, and admins can schedule data profile updates, run profiles on random/stratified samples or custom filters. Atlan's data profile is an open ecosystem, allowing teams to import data quality metrics from external ecosystems like data pipeline tools for key metrics, such as timeliness, or other internal tools or frameworks.
| Access control: |
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| Commercial: | Commercial |
| Desktop/Cloud: | Cloud |
| Excel workbooks: |
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| Flat files: |
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| Free edition: |
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| Metadata identification: |
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| NoSQL sources: |
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| Runs on: (for desktop): | - |
| Sensitive data discovery: |
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| Statistics of data: | Avg,Stdev |
| Tagging data: |
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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.