Remove Data Collection Remove Data Quality Remove Risk Remove Testing
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Bringing an AI Product to Market

O'Reilly on Data

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage.

Marketing 363
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What is data governance? Best practices for managing data assets

CIO Business Intelligence

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.

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Data Mesh 101: How Data Mesh Can Be Used in an Organization

Ontotext

Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage. Establish and enforce data governance by ensuring all data used is accurate, complete, and compliant with regulations. This calls for additional planning, documentation, and testing.

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Our Favorite Questions

O'Reilly on Data

The safest course of action is also the slowest and most expensive: obtain your training data as part of a collection strategy that includes efforts to obtain the correct representative sample under an explicit license for use as training data. How I use it: I like to ask this as early as possible.

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How Data Ethics Supports Governance & Monetisation

Alation

I recently led an online session, Data Monetisation and Governance , looking at the evolution of data governance , defining data ethics (from the Turing Institute ), and touching on the balancing act between using data to monetise (by increasing revenue, decreasing spend, or mitigating risk) and meeting ethical obligations.

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Two Downs Make Two Ups: The Only Success Metrics That Matter For Your Data & Analytics Team

DataKitchen

Under Efficiency, the Number of Data Product Owners metric measures the value of the business’s data products. Under Quality, the Data Quality Incidents metric measures the average data quality of datasets, while the Active Daily Users metric measures user activity across data platforms.

Metrics 130
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Better, faster decisions: Why businesses thrive on real-time data

CIO Business Intelligence

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.