By 2022, 60% of organizations will leverage machine-learning-enabled data quality technology for suggestions to reduce manual tasks for data quality improvement.
Market Definition: The term “data quality” relates to the processes and technologies for identifying, understanding and correcting flaws in data that support effective data and analytics governance across operational business processes and decision making. The packaged solutions available include a range of critical functions, such as profiling, parsing, standardization, cleansing, matching, enrichment, monitoring and collaborating.
Informatica, IBM, SAP, SAS, Talend & Precisely are the leaders in "Magic Quadrant for Data Quality Solutions 2020".
No comments:
Post a Comment