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Rising Tide Rents and Robber Baron Rents

O'Reilly on Data

Perhaps a more direct way to say this in the context of economic value creation is that companies such as Amazon and Google and Facebook had developed a set of remarkable advances in networked and data-enabled market coordination. But over time, something went very wrong. I think not.

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A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

are more efficient in prioritizing data delivery demands.” Release New Data Engineering Work Often With Low Risk: “Testing and release processes are heavily manual tasks… automate these processes.” Learn, improve, and iterate quickly (with feedback from the customer) with low risk.

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7 famous analytics and AI disasters

CIO Business Intelligence

The use of mislabeled data or data from unknown sources was a common culprit. Derek Driggs, a machine learning researcher at the University of Cambridge, together with his colleagues, published a paper in Nature Machine Intelligence that explored the use of deep learning models for diagnosing the virus.

Analytics 140
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How The CIO Can Become The CMO’s Best Ally In The Use Of Data

CIO Business Intelligence

CMOs need to look for ways to leverage customer data to deliver superior and highly tailored experiences to customers. CIOs need to ensure that the business’ use of data is compliant, secure, and done according to best practices. They need to assure the board that the risk from data is minimised.

Risk 79
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The Failed Promises of Digital Transformation and What to Do About It

Ontotext

The use cases span all the things near and dear to most C-level executives’ hearts – driving more revenue, improving operational efficiency, reducing risk, or increasing innovation and agility. ” (See “Market Guide for Graph Database Management Systems”, Published 30 August 2022, by Merv Adrian and Afraz Jaffri).

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Introducing watsonx: The future of AI for business

IBM Big Data Hub

At IBM, we believe it is time to place the power of AI in the hands of all kinds of “AI builders” — from data scientists to developers to everyday users who have never written a single line of code. Watsonx, IBM’s next-generation AI platform, is designed to do just that.

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The Power of Ontologies and Knowledge Graphs: Practical Examples from the Financial Industry

Ontotext

Example: Refinitiv PermID Refinitiv reuses part of FIBO’s Entities and Corporate bodies ontology when publishing company data in the permid.org related products. A knowledge graph-powered system, utilizing the FIBO-V product, can power a solution that enables the capabilities in the generalized use cases as shown in the diagram below.