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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

The company has been on a continuous journey to adapt its internal and external processes to new business needs and opportunities since 2001.” “Digital transformation is not a new concept for Ipsos,” says global CIO Humair Mohammed. js and React.js.

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What is TOGAF? An enterprise architecture methodology for business

CIO Business Intelligence

It’s an extensive document — but you don’t have to adopt every part of TOGAF. Organizations can start with the core fundamentals, and then pick and choose parts to adopt from the extended guidance portion of the document. The Open Group also streamlined the documentation, removing anything redundant or outdated.

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FOS CIO shakes up IT department, starts cloud migration

CIO Business Intelligence

Established by the UK Parliament in 2001 to settle complaints about financial-services companies, the Financial Ombudsman’s Service (FOS) has served an increasing number of consumers, recently dealing with more than a million people a year.

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Agile Reporting for the Manufacturing Industry: 5 Tips for Success

Jet Global

In 2001, a group of software developers got together at a ski resort in the Wasatch mountains of Utah and drew up a document they called the “Agile Manifesto.” They rejected the classic waterfall model of software development in favor of an iterative approach in which initial prototypes are delivered and tested early in the process.

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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. In more detail, they explained that just as the hypertext Web changed how we think about the availability of documents, the Semantic Web is a radical way of thinking about data.

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Data Science at The New York Times

Domino Data Lab

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. As the story goes, the general history of DG is punctuated by four eras: “Application Era” (1960–1990) – some data modeling, ?though There are models everywhere. It’s a mess.