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Solving the Data Daze – Analytics at the Speed of Business Questions

Rocket-Powered Data Science

In the early days of the current data analytics revolution, one would often hear business owners say that they need their data to move at the speed of business. Well, it soon became clear that the real problem was the reverse: how can we have our business move at the speed of our data? Source: [link]

Analytics 167
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Incorporating Artificial Intelligence for Businesses : The Modern Approach to Data Analytics

BizAcuity

Combined, it has come to a point where data analytics is your safety net first, and business driver second. AI Adoption and Data Strategy. Lack of a solid data strategy. In order to adopt AI solutions for your business, the best way forward is to first ensure that you have a strong data strategy in place.

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AI In Analytics: Today and Tomorrow!

Smarten

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

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Themes and Conferences per Pacoid, Episode 13

Domino Data Lab

This was alongside keynotes by: Rebecca Williams from OMB at the Whitehouse—who helped develop the US federal data strategy and year-1 action plan —check out her slides for the “Federal Data Strategy” keynote. Monica Youngman, director of data stewardship—check out her slides for the “Data Archiving at NOAA” keynote.

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King County enlists AI to reduce drug overdose deaths

CIO Business Intelligence

The ML models include classic ML and deep learning to predict category labels from the narrative text in reports. The IT department also used the Hugging Face online AI service and PyTorch, a Python framework for building deep learning models. Azure Databricks is also employed for data analytics as part of the solution.