Data Quality Document Measurement Risk Management 
CIO Business Intelligence
MARCH 24, 2023
The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Data-related decisions, processes, and controls subject to data governance must be auditable.
erwin
MARCH 25, 2021
And with many competing projects and activities vying for people’s time, it must be clear to people why choosing data governance activities will have a direct benefit to them. Usually we talk about benefits which are rather qualitative measures, but what we need for decision-making processes are values,” Pörschmann says. “We
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Alation
AUGUST 17, 2022
Data governance policy should be owned by the top of the organization so data governance is given appropriate attention — including defining what’s a potential risk and what is poor data quality.” It comes down to the question: What is the value of your data? Enterprise risk management.
CIO Business Intelligence
MARCH 24, 2023
Overcoming data challenges Despite their growing commitment to ESG, financial firms have learned the path to sustainability and prosperity can be rocky. “ESG ESG data quality is the biggest challenge. revenue growth from businesses showing a lower commitment to ESG.
DataRobot
JULY 16, 2021
They all serve to answer the question, “How well can my model make predictions based on data?” In performance, the trust dimensions are the following: Data quality — the performance of any machine learning model is intimately tied to the data it was trained on and validated against.
O'Reilly on Data
DECEMBER 12, 2019
In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8]. That’s where model debugging comes in.
Alation
MARCH 14, 2023
All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Some business processes may need reviewing to include data analysis — even going as far as requiring specific data to make a business decision.
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