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5 key areas for tech leaders to watch in 2020

O'Reilly on Data

Up until 2017, the ML+AI topic had been amongst the fastest growing topics on the platform. After several years of steady climbing—and after outstripping Java in 2017—Python-related interactions now comprise almost 10% of all usage. Not necessarily: Java-related searches increased by 5% between 2017 and 2018. Coincidence?

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Infor’s Velocity Summit Highlights Multiple Advances and Enhancements

David Menninger's Analyst Perspectives

Also center stage were Infor’s advances in artificial intelligence and process mining as well as its environmental, social and governance application and supply chain optimization enhancements. Optimize workflows by redesigning processes based on data-driven insights. It also offered a chatbot that utilized Amazon Lex.

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Oracle Wants to Be the Database for AI

David Menninger's Analyst Perspectives

In addition to various deployment options, Oracle offers several database services, including Oracle Exadata optimized infrastructure, Oracle Autonomous Database, Oracle Autonomous Data Warehouse and Heatwave MySQL service. Oracle was an early leader in using machine learning to provide autonomous capabilities, introducing them in 2017.

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Data Analytics Play Huge Role In Optimizing Organization Management

Smart Data Collective

In 2017, 53% of companies reported using data analytics as part of their strategy. The post Data Analytics Play Huge Role In Optimizing Organization Management appeared first on SmartData Collective. The number of companies utilizing data analytics has skyrocketed in recent years. This marks a 200% increase over a two-year period.

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TBM helps CIOs translate tech spending to business outcomes

CIO Business Intelligence

The goal is to give such leaders widespread visibility into planning, benchmarking, and optimization of their IT investments, according to the TBM Council. The US Office of Management and Budget has also pushed agencies to use TBM practices since 2017. While many organizations swear by TBM, the practice also has its detractors.

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What are model governance and model operations?

O'Reilly on Data

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. An overview from a 2017 paper from Google lets us gauge how much tooling is still needed for model operations and testing.

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The cloud infrastructure that’s redefining management at Guzmán Minerals

CIO Business Intelligence

The company is nowin the process of improving digitalization in the factory, which includes automation processes and adoption of technologies to optimize operations. for Business Central, the project is in its early stages and represents a major transition from its current Dynamics NAV 2017 ERP solution.