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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO Business Intelligence

It’s yet another key piece of evidence showing that there is a tangible return on a data architecture that is cloud-based and modernized – or, as this new research puts it, “coherent.”. Data architecture coherence. Putting data in the hands of the people that need it. more machine learning use casesacross the company.

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The most valuable AI use cases for business

IBM Big Data Hub

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AIOps is one of the fastest ways to boost ROI from digital transformation investments.

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5 Data Governance Mistakes to Avoid

Alation

It’d be difficult to exaggerate the importance of data in today’s global marketplace, especially for firms which are going through digital transformation (DT). Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029. Does our privacy policy reflect current regulations?

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5 Data Governance Mistakes to Avoid

Alation

It’d be difficult to exaggerate the importance of data in today’s global marketplace, especially for firms which are going through digital transformation (DT). Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029. Does our privacy policy reflect current regulations?

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Generac powers business transformation with data, AI

CIO Business Intelligence

The digital platform, which earned a 2023 CIO 100 Award for innovation and IT leadership, was enabled by Generac’s embrace of Microsoft Azure and Azure Data Factory as well as Databricks’ AI platform, all completed over the past two years, Dickson notes. By the end of 2022, the company’s reported revenue was $4.6

IoT 96
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CIO 100 Award winners prove the transformative value of IT

CIO Business Intelligence

The Behavioral Health Acuity Risk (BHAR) model leverages a machine learning technique called random forests, which can be natively hosted in the electronic health record and updated in near-real time, with results immediately available to clinical staff.

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