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Best Data Quality Solution


The old adage, garbage in, garbage out, has never been truer. Not only is the problem of data quality not going away with the advance of technology and the growth of data volumes, velocities, and varieties—but it is getting worse.

To do their work, data scientists must locate huge quantities of relevant data and integrate and cleanse that data for it to be useful, said A.M. Turing Award Laureate and database technology pioneer Michael Stonebraker, who delivered the welcome keynote at Data Summit 2019, titled “Big Data, Technological Disruption, and the 800-Pound Gorilla in the Corner.”

Stonebraker cited the example of a data scientist who said, “I spend 90% of my time finding and cleaning data and then 90% of the other 10% checking on the cleaning” because it is not possible to analyze dirty data. This is an enterprise problem, said Stonebraker, who added. “Even on simple analytics, data quality matters.

Fortunately, there are solutions to help address the vexing and time-consuming issues related to data quality.

Best Data Quality Solution

Syniti (formerly BackOffice Associates) Data Stewardship Platform

Winners' Circle by Zarina Stanford CMO Syniti, formerly BackOffice Associates

We believe great data quality is not an event—it’s cultural. Data flows throughout your organization via conduits of processes where it interacts with people, other data, and systems. Each interaction is an opportunity to further data quality and capture knowledge for the rest of the organization. However, in most data environments, the resulting data is the only artifact of learning retained. Read on.

Finalists

SAS Data Quality

Trillium DQ from Syncsort


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