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Data quality tools for Oracle
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.
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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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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RightData
RightData is a self-service suite of applications that helps you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities.
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Atlan
Atlan uses DataOps to create a new paradigm for building trust in your data. It auto-generates data quality profiles which make detecting bad data dead easy. From automatic variable type detection & frequency distribution to missing values and outlier detection, Atlan offers everything.
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Collibra Data Quality
Collibra Data Quality lets you use predictive data quality to improve trust in your data. With predictive, continuous, and self-service data quality, you can centralize and automate data quality workflows to gain better control over your organization's end-to-end data pipelines and streamline analytics processes across the enterprise.
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CuriumDQM
CuriumDQM (Data Quality Management) delivers advanced process control over the firm’s data sets without the need to change any aspects of the firm’s underlying data architecture. CuriumDQM is a cost-effective way of giving Operations and Data Management teams the process and oversight they need to deliver effective data governance, as well as reduced risk and better overall confidence in the data management function.
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Syniti Data Quality
Data quality management solutions from Syniti provide a simplified and cost-effective approach to monitor and accurately remediate data that violates your standards for data quality. Derive data quality rules from institutional knowledge, technical needs of downstream systems and interfaces, as well as legal/regulatory requirements. Proactively identify operational insights that allow potential issues to be addressed before process interruptions occur.
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CloverDX
CloverDX's data quality features offer you automated data quality and error handling for your workflows. With CloverDX's data quality features, you can discover and deal with bad data fast. You can automate bad data identification & correction, rule definitions, and reports on data quality. In short, CloverDX gives you the ability to make better decisions with more trustworthy data.
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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.