Remove 2017 Remove Data mining Remove Interactive Remove Visualization
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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2) Data Discovery/Visualization. We all gained access to the cloud.

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Make Your Investment in Analytic Technology Pay Off With Decision Requirements Modeling

Decision Management Solutions

Like many enterprises, you’ve likely made a hefty investment in analytic technology—from interactive dashboards and advanced visualization tools to data mining, predictive analytics, machine learning (ML), and artificial intelligence (AI). 1 MIT Sloan Management Review September 06, 2017.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. Skater provides a wide range of algorithms that can be used for visual interpretation (e.g. Partial Dependence Plots (PDPs).

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

However, if we experiment with both parameters at the same time we will learn something about interactions between these system parameters. Figure 4: Visualization of a central composite design. Central composite designs are made of three parts. The center part is one or more experiments in which parameters take their control (i.e.,

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What Is Data Intelligence?

Alation

Data catalogs then integrate compliance at the point of consumption, so people are alerted to sensitive data where it lives. Source: “What’s Your Data Strategy?” HBR Review May/June 2017. Data Intelligence and Metadata. Data intelligence is fueled by metadata. Data Intelligence and Active Metadata.