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Data Quality

444 Enrolled | 305 Completed

About this course

Instructor: Lowell Fryman, Customer Success Practice Principal

Data Quality has been a topic of discussion for over twenty years. The challenge is that data quality is a complex issue. The sole objective of Data Governance is not to improve data quality, but rather to identify quality data. Evaluation includes front office and back office activities. It includes a strategy, policies, standards, operational life-cycle activities & resources, measurements & dashboards, thresholds for usage and technology support.We need to address data quality from many angles and we begin with a data quality assessment. A Data Quality Assessment is a “point in time” profile and analysis of a specific set of data. It’s important to conduct an analysis and then make recommendations for data quality improvements. The Collibra Data Governance Center has a wide array of tools at your disposal to verify and define data quality. This effort will require various roles and responsibilities from Content Owners, IT Data Custodians, Data Consumers, Data Stewards and of course, the Data Governance team. All of these efforts combined will improve the data quality levels of your organization.

Collibra makes it easy for data citizens to find, understand and trust the organizational data they need to make business decisions every day. Unlike traditional data governance solutions, Collibra is a cross-organizational platform that breaks down the traditional data silos, freeing the data so all users have access.

©2019 Collibra. All Rights Reserved.

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