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A comparative assessment of digital transformation in Italy

CIO Business Intelligence

β€œDigital is a powerful business lever,” says Alessandra Luksch, director of the Digital Transformation Academy Observatory at Politecnico di Milano, which has been mapping trends in ICT spending by Italian organizations since 2016. β€œIn AMA employs about 7,600, serves a catchment area of nearly 2.5 million tons of waste annually.

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that.

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Carhartt turns to data under new CIO

CIO Business Intelligence

Carhartt’s signature workwear is near ubiquitous, and its continuing presence on factory floors and at skate parks alike is fueled in part thanks to an ongoing digital transformation that is advancing the 133-year-old Midwest company’s operations to make the most of advanced digital technologies, including the cloud, data analytics, and AI.

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What is a data architect? Skills, salaries, and how to become a data framework master

CIO Business Intelligence

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations.

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Real estate CIOs drive deals with data

CIO Business Intelligence

The residential real estate industry may not be perceived to be as digitally aggressive as Wall Street titans and multinational manufacturing conglomerates. Augmenting real estate relationships with data Keller Williams, another leading residential player, also kicked off its digital transformation roughly seven years ago.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

Belcorp operates under a direct sales model in 14 countries. The initial stage involved establishing the data architecture, which provided the ability to handle the data more effectively and systematically. β€œWe The team leaned on data scientists and bio scientists for expert support.

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Lay the groundwork now for advanced analytics and AI

CIO Business Intelligence

But reaching all these goals, as well as using enterprise data for generative AI to streamline the business and develop new services, requires a proper foundation. That hard, ongoing work includes integrating siloed data, modeling, and understanding it, as well as maintaining and securing it over time.