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Data profiling tools
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.
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| Commercial: | Commercial |
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| Statistics of data: | Avg,Max,Min,Stdev |
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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.
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| Statistics of data: | Avg,Stdev |
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Datamartist
Datamartist is an easy-to-use data profiling tool for analyzing format, types, completeness, and value counts. It understands data quality issues clearly and quickly. It performs automated data profiling tasks, which can be used to create a periodic snapshot of key data quality metrics, letting an organization track and report on data quality.
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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.
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Experian Pandora for Data Profiling
Experian Pandora for Data Profiling helps to focus on fixing data errors by enabling business users to conduct profiling analysis and relationship discovery with incredible speed. It automatically discovers broken keys, orphaned records, and thousands of content quality issues using the highly intuitive fault detection features of our data management platform.
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Datiris Profiler (discontinued)
Datiris Profiler is an intuitive data profiling tool. Its key features include cross-table analysis, domain validation, pattern analysis, conditional profiling, command-line interface, and many more. Besides that, with features such as batch profiling, you can queue up and profile data quickly and spend your time analyzing instead of gathering it.
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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.
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Oracle Data Profiling and Data Quality for Data Integrator
Oracle Data Profiling is a data investigation and quality monitoring tool. It allows business users to assess the quality of their data through metrics, to discover or infer rules based on this data, and to monitor the evolution of data quality over time.
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Open Source Data Quality and Profiling
Open Source Data Quality and Profiling tool is an open source project dedicated to data quality and data preparation solutions. This tool is developing high performance integrated data management platform which will seamlessly do data integration, data profiling, data quality, data preparation, dummy data creation, meta data discovery, anomaly discovery, data cleansing, reporting, and analytic.
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Acuate Data Profiling
Acuate Data Profiling tool enables you to find data problems quickly. It lets you select from a range of profiling rules to analyze your data. It can analyze data by character type or by word and lets you dive deeper into the details by drilling down into the data.
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Data Ladder
Data Ladder’s DataMatch Enterprise offers one of the easiest to use data profiling tools in the market. It quickly provides enough metadata to construct a cogent profile analysis of data quality and quantifies the scope and depth of necessary add-ons to make the project successful. Once it does the profiling, it proceeds to perform data matching, cleansing, deduplication and standardization, finally achieving data validation.
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Ataccama ONE
Ataccama One lets you discover, analyze, understand critical patterns in your data. You can see data domains and data quality highlights for each attribute. Re-profile data in one click and check whether the problems you identified were fixed. You can select as many tables in a data source as you need and profile them all in one click.
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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.
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DataRobot Data Prep
DataRobot Data Prep enables both novice and expert users to quickly and interactively explore, profile, clean, enrich and shape diverse data into AI assets ready for machine learning model development and deployment. It offers a visually interactive user interface that presents data in familiar tabular or spreadsheet style with no coding required. DataRobot provides profiles for every record and feature, including how many values are unique or missing and the statistical mean, standard deviation, median, minimum value, and maximum value.
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Melissa Data Profiler
Melissa Data Profiler analyzes data before it’s merged into your warehouse, then helps ensure consistent data quality once it’s there. It lets you identify data quality issues, monitor improvements over time, and utilize reference data to determine if your input is consistent with expected data. It can also determine if the input data is consistently fielded using the data contained in the entire record to analyze the context 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.