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Two Downs Make Two Ups: The Only Success Metrics That Matter For Your Data & Analytics Team

DataKitchen

So it’s Monday, and you lead a data analytics team of perhaps 30 people. But wait, she asks you for your team metrics. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. Where is your metrics report? What should be in that report about your data team?

Metrics 130
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30 Best Manufacturing KPIs and Metric Examples for 2021 Reporting

Jet Global

An Operations Key Performance Indicator (KPI) or metric is a discrete measurement that a company uses to monitor and evaluate the efficiency of its day-to-day operations. These operations KPIs help management identify which operational strategies are effective, and those that inhibit the company.

Metrics 131
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What you need to know about product management for AI

O'Reilly on Data

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools.

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25 Best Healthcare KPIs and Metric Examples for 2021 Reporting

Jet Global

A healthcare Key Performance Indicator (KPI) or metric is a well-defined performance measure that is used to observe, analyze, optimize, and transform a healthcare process to increase satisfaction for both patients and healthcare providers alike. While this metric is very useful, it is also very general. What is a Healthcare KPI?

Metrics 98
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Bringing an AI Product to Market

O'Reilly on Data

The Core Responsibilities of the AI Product Manager. Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle.

Marketing 363
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Managing risk in machine learning

O'Reilly on Data

At the recent Strata Data conference we had a series of talks on relevant cultural, organizational, and engineering topics. Here's a list of a few clusters of relevant sessions from the recent conference: Data Integration and Data Pipelines. Data Platforms. Model lifecycle management. Culture and organization.

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Automation for all—managing and scaling networks has never been easier

CIO Business Intelligence

By leveraging one common networking architecture and multiple cloud-based devices, users can view and manage a network from end-to-end through any number of interfaces (e.g., It also provides an easier way to implement and manage automation tools throughout a network. web UI, APIs, mobile).