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External Data Supports More Accurate Planning

David Menninger's Analyst Perspectives

One of the points that I look at is whether and to what extent the software provider offers out-of-the-box external data useful for forecasting, planning, analysis and evaluation. Robust datasets that hold a large and diverse set of data from which to glean inferences create more useful and accurate forecasts.

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Predictive Models Are Nothing Without Trust

Cloudera

Ryan Garnett, Senior Manager Business Solutions of Halifax International Airport Authority, joined The AI Forecast to share how the airport revamped its approach to data, creating a predictions engine that drives operational efficiency and improved customer experience. Here are some highlights from Paul and Ryans conversation.

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Predictive Analytics Supports Citizen Data Scientists!

Smarten

In order to do this, the team must have a dependable plan and be able to forecast results and create reasonable objectives, goals and competitive strategies. Forecasting and planning cannot be based on opinions or guesswork. According to CIO publications, the predictive analytics market was estimated at $12.5

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The key to operational AI: Modern data architecture

CIO Business Intelligence

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

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KDnuggets™ News 22:n01, Jan 5: 3 Tools to Track and Visualize the Execution of Your Python Code; 6 Predictive Models Every Beginner Data Scientist Should Master

KDnuggets

3 Tools to Track and Visualize the Execution of Your Python Code; 6 Predictive Models Every Beginner Data Scientist Should Master; What Makes Python An Ideal Programming Language For Startups; Alternative Feature Selection Methods in Machine Learning; Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor (..)

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective. Our team does a lot of forecasting. It also owns Google’s internal time series forecasting platform described in an earlier blog post.

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Data Insights for Everyone — The Semantic Layer to the Rescue

Rocket-Powered Data Science

The BI (business intelligence) analysts need to find the right data for their visualization packages, business questions, and decision support tools — they also need the outputs from the data scientists’ models, such as forecasts, alerts, classifications, and more.