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Data quality tools for SAP IQ
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.
Dataedo
Dataedo is a data governance & data catalog tool that helps you ensure data quality while documenting data. It allows you to understand where your data is coming from through data lineage, peak into values itself to validate quality with data profiling, and gather invaluable feedback from the community.
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Global IDs Data Quality Suite
Global IDs Data Quality Suite ensures the quality of the data by establishing control points and read-only quality controls at the database level. It continuously monitors quality metrics, while it also automates control generation for critical data elements across all kinds of data sources.
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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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Trillium Quality
Trillium Quality rapidly transform high-volume, disconnected data into trusted and actionable business insights with scalable enterprise data quality. It has been designed to run natively in cloud or on-premises big data environments, ensuring your business information is integrated, fit-for-purpose, and accessible across the enterprise, regardless of volume.
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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.