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Data profiling tools for Microsoft SQL Server Reporting Services (SSRS)
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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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.
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| Commercial: | Commercial |
| Desktop/Cloud: | Cloud |
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| Runs on: (for desktop): | - |
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| Statistics of data: | Avg,Max,Min,Stdev |
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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.
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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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| Runs on: (for desktop): | - |
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| Statistics of 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.