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The more complete, accurate and consistent a dataset is, the more informed businessintelligence and business processes become. This is done to uncover errors, inaccuracies, gaps, inconsistent data, duplications, and accessibility barriers.
This has created many different data quality tools and offerings in the market today and we’re thrilled to see the innovation. People will need high-quality data to trust information and make decisions. DataProfiling — Statistics such as min, max, mean, and null can be applied to certain columns to understand its shape.
A data quality standard might specify that when storing client information, we must always include email addresses and phone numbers as part of the contact details. If any of these is missing, the client data is considered incomplete. DataProfilingDataprofiling involves analyzing and summarizing data (e.g.
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