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Sport analytics leverage AI and ML to improve the game

CIO Business Intelligence

Nearly 10 years ago, Bill James, a pioneer in sports analytics methodology, said if there’s one thing he wished more people understood about sabermetrics, pertaining to baseball, it’s that the data is not the point. The point is to use the data like a razor to cut through false convictions to find the truth.

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What is vegetation management? 

IBM Big Data Hub

Vegetation management aims to mitigate these risks. The 2003 blackout mentioned earlier wasn’t an isolated case; in some regions, vegetation causes up to half of the power outages, and in the US, this figure reaches as high as 92% , as reported by the Federal Energy Commission. But what exactly does vegetation management mean?

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Per Scholas redefines IT hiring by diversifying the IT talent pipeline

CIO Business Intelligence

When CEO Plinio Ayala joined Per Scholas in 2003, he noticed there weren’t enough skilled technicians to fix the hardware the organization collected. Per Scholas leadership calls the approach “market-driven training,” because it is informed by the current hiring demands and needs of the technology industry.

IT 100
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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. But looking through the blogosphere, some go further and posit that “platformization” of forecasting and “forecasting as a service” can turn anyone into a data scientist at the push of a button.

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Data Modeling 201 for the cloud: designing databases for data warehouses

erwin

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Data modeling for the cloud: good database design means “right size” and savings.

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What Will Drive Innovation in this Great Reset

Andrew White

In this second phase executive leaders will need to make critical business decisions with even less data and with more uncertainty. AI and machine learning will help, along with other data and analytics capabilities. New processes focused on data visibility and business resiliency will emerge. Data, analytics and AI.