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Teradata
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Data profiling tools for Teradata
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 |
| Desktop/Cloud: | Desktop |
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| Runs on: (for desktop): | Windows |
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| Statistics of data: | Avg,Max,Min,Stdev |
| Tagging data: | - |
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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| Commercial: | Commercial |
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| Runs on: (for desktop): | Linux |
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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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| Commercial: | Commercial |
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| Runs on: (for desktop): | Linux,Windows |
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| Statistics of data: | Avg,Stdev |
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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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| Commercial: | Commercial |
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| Statistics of data: | Avg,Max,Min |
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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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| Commercial: | Commercial |
| Desktop/Cloud: | Cloud |
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Toad Data Point
Toad Data Point is a multi-platform database query, data prep, and reporting tool. It lets you visually profile and sample database tables and data sets for patterns, unique values, duplicates, missing information, min./max. values and more.
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| Commercial: | Commercial |
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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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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
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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 |
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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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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.
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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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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.