Remove Data Integration Remove Data Quality Remove Digital Transformation
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As insurers look to be more agile, data mesh strategies take centerstage

CIO Business Intelligence

Data fabric introduces an intelligent semantic layer that orchestrates disparate data sources, applications, and services into a unified and easily accessible framework. Enabled via a data integration hub, the data fabric architecture connects, organizes, and manages data, providing a consistent view across the data ecosystem.

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What’s the Current State of Data Governance and Automation?

erwin

Digital transformation and data standards/uniformity round out the top five data governance drivers, with 37 and 36 percent, respectively. Constructing a Digital Transformation Strategy: How Data Drives Digital. And close to 50 percent have deployed data catalogs and business glossaries.

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Salesforce and the (single source of) Truth about Customer 360

Andrew White

I argued that one vendors’ book on data quality was really about data governance; I argued that another vendors’ marketing message was totally upside down; and I argued that some approaches to achieving single source of truth were different from traditional approaches. See Salesforce acquisition of Tableau – What does it mean?

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

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Don’t Fear Artificial Intelligence; Embrace it Through Data Governance

CIO Business Intelligence

Despite soundings on this from leading thinkers such as Andrew Ng , the AI community remains largely oblivious to the important data management capabilities, practices, and – importantly – the tools that ensure the success of AI development and deployment. Further, data management activities don’t end once the AI model has been developed.

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How Metadata Makes Data Meaningful

erwin

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., by up to 70 percent.

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6 tough AI discussions every IT leader must have

CIO Business Intelligence

Can the current state of our data operations deliver the results we seek? Another tough topic that CIOs are having to surface to their colleagues: how problems with enterprise data quality stymie their AI ambitions. 1 among the top three risks — followed by statistical validity and model accuracy.

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