Watch the Webinar

The dirty little secret of data analytics is that the quality of enterprise data is often quite poor. Data analysts still spend an inordinate amount of time harmonizing data from different systems. Minor changes in source systems and processing anomalies break downstream data pipelines, creating fire drills for data managers and grumpy business users who can’t access reports and data. Until data teams figure out a way to automate the delivery of high-quality data across the enterprise, they will never become a trusted business partner and harness the full power of data.

This webinar will present a framework for modernizing data quality and master data management (MDM). It will show how modern data platforms automate the creation and execution of data quality rules for cleaning data and harmonizing master data across the enterprise. These modern platforms use machine learning to automate manual processes involved in data classification, rules creation, data cleansing, data matching, metadata tagging, and data lineage. They also use scalable data processing engines (i.e., Spark) to validate, clean, and harmonize enterprise data at scale and speed.

You Will Learn:

• The obstacles to modernizing data quality and master data management processes.
• How modern data platforms automate the creation and execution of data quality and master data rules and processes.
• How modern data platforms process any kind of data at scale and speed.

How machine learning automates routing data governance processes, such as data classification, data matching, data cleansing, and data lineage.

Sponsor: Ataccama Corp.