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Data quality tools
Data quality tools measure how good and useful a data set is to serve its intended purpose. High quality data can lead to better decision-making and faster insights as well as reduce the costs of identifying and dealing with bad data in the system. It can also save time and allow companies to focus on more important tasks.
DataCleaner
DataCleaner is a premier open source data quality solution. 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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BigID
BigID offers actionable data intelligence by empowering you to find, classify, catalog, profile and get context for all your data in the cloud or data-center, at-rest or in-motion, structured or unstructured at petabyte scale. It lets you identify sensitive data using hundreds of pre-built NLP, Deep Learning, and pattern classifiers.
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DQ*Plus
DQ*Plus data quality software cleanse data, verify addresses, find and consolidate duplicate records in batch and real-time. It accurately matches duplicate records and intelligently merges them into a single best record.
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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. It can transform and combine disparate data, remove inaccuracies, standardize on common values, parse values and cleanse unclean data to create a strategic, trustworthy, valuable asset that enhances decision making power.
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OpenRefine
OpenRefine (previously Google Refine) is a free, open source, and powerful tool for working with messy data: cleaning it, transforming it from one format into another, and extending it with web services and external data.
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Informatica Data Quality
Informatica Data Quality ensures end-to-end support for growing data quality needs across users and data types with AI-driven automation. It uses AI-driven insights to automate the most critical tasks and streamline data discovery to increase productivity and effectiveness. It ensures the delivery of high-quality information with data standardization, validation, enrichment, de-duplication, and consolidation capabilities.
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Microsoft Data Quality Services
Microsoft Data Quality Services (DQS) is a knowledge-driven data quality product. DQS enables you to build a knowledge base and use it to perform a variety of critical data quality tasks, including correction, enrichment, standardization, and de-duplication of your data. DQS enables you to perform data cleansing by using cloud-based reference data services provided by reference data providers. DQS also provides you with profiling that is integrated into its data-quality tasks, enabling you to analyze the integrity of your data.
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Ataccama ONE
Ataccama ONE offers self-driving data quality management by letting you quickly understand the state of your data, validate & improve it, prevent bad data from entering your systems, and continuously monitor data quality.
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DemandTools
DemandTools is a data management platform for cleaning and maintaining CRM data in less time, so you always have report-ready data improving the effectiveness of your revenue operations. With DemandTools, you can dedupe, standardize, and assign records automatically as they come in from spreadsheets, end-user entry, and integrations.
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Infogix Data360 DQ+
Infogix Data360 DQ+ is an enterprise data quality solution that automates data quality checks across the entire data supply chain from the time information enters your organization throughout its whole journey. You can score the likelihood of possible inaccuracies based on historical data characteristics and issue reconciliations by leveraging machine learning algorithms.
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SAP Master Data Governance
SAP Master Data Governance improves the quality and consistency of information across your organization by consolidating and centrally governing the master data lifecycle. It empowers you to collaboratively describe, catalog, and implement rules for data quality evaluation. Initiate and schedule quality evaluations and manage evaluation results. In addition, you can overview current data quality status and KPIs. In short, it lets you define, monitor, improve data quality.
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IBM InfoSphere Information Server for Data Quality
IBM InfoSphere Information Server for Data Quality enables you to cleanse data and monitor data quality on an ongoing basis, helping to turn your data into trusted information. The solution offers end-to-end data quality tools to help you understand your data and its relationships; analyze and monitor data quality continuously; cleanse, standardize and match data; and maintain data lineage.
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Aperture Data Studio
Aperture Data Studio combines self-service data quality with globally curated data sets into a single data quality platform. This empowers modern data practitioners to build a consistent, accurate, and holistic view of their consumer data quickly and effortlessly. It lets you set custom workflows for data profiling, cleansing, validation, transformation, enrichment, and deduplication.
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TIBCO Clarity
TIBCO Clarity is data preparation, profiling, and cleansing tool. You can use TIBCO Clarity to discover, profile, cleanse, and standardize raw data collected from disparate sources, and provide good quality data for accurate analysis and intelligent decision-making.
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Qualdo
Qualdo is a single, centralized tool to measure, monitor, and improve data quality from all your cloud database management tools and data silos. It lets you deploy powerful auto-resolution algorithms to track and isolate critical data issues. Take advantage of robust reports and alerts to manage your enterprise regulatory compliance.
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Data quality tools are the scripts that support the data quality processes and they heavily rely on identification, understanding, and correction of data errors. Data quality tool enhances the accuracy of the data and helps to ensure good data governance all across the data-driven cycle.
The common functions that each data quality tools must perform are:
• Data profiling
• Data monitoring
• Parsing
• Standardization
• Data enrichment
• Data cleansing
Choosing the right data quality tool is essential and impacts the final results. To help you with the right selection, we prepared a list of tools that will assist you with maintaining a high level of data quality.