Quality
Rules , rules .. and more rules ..
Users can navigate to Quality under Settings to view all of the out-of-the-box measures categorized under Reliability, Distribution, Frequency, and Statistics.
They can select whether the measure is:
● Active or Inactive,
● Valid or Invalid,
● Include it in scoring
● Monitor
Best practice to use the quality page:
● Document the requirement/business case for each asset or a business as a whole
● Identify the Out of the measures from the below-mentioned section, and enable them before configuring an asset
● Ensure to choose scoring/monitoring on a need-to-basis
● Configure the assets after the settings to auto-enable the selected measures for any asset that is configured in the platform
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Define health-related measures to measure data reliability or health check of the dataset. These map back to the DAMA six pillars of Data Quality.
Obviously you can add your own Custom Dimensions.
Aimed toward the Data Analyst or Data Steward who are concerned with, for example, character checks, character distribution at the column level. Basically checks to measure and understand the content of data assets.
Define frequency-related measures to understand the format and enumeration of data assets.
Define statistics-related measures to figure out the suitability of the data for its intended applications in data analytics, data science, or machine learning.
Shows all the out of the box measure under one table.
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