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Can developer productivity be measured? Better than you think

CIO Business Intelligence

Measuring developer productivity has long been a Holy Grail of business. In 2020, McKinsey surveyed 440 large companies about their “ developer velocity” — meaning the practices that best tap the full potential of development talent. In addition, system, team, and individual productivity all need to be measured.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

The trends we presented last year will continue to play out through 2020. In 2020, BI tools and strategies will become increasingly customized. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

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Getinge’s digital transformation shows scaling and adapting in equal measure

CIO Business Intelligence

There is measurable progress, however, as data from the company’s connected products are collected in its own platform, where customers have access to information via a portal. “In In the long run, we envisage new services such as being able to handle predictive maintenance based on what we know about the products,” he says.

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The 10 Essential SaaS Trends You Should Watch Out For In 2020

datapine

billion by 2022—a level of growth that will shape SaaS trends in 2020. With a new year on the horizon, in this article, we’ll explore 10 essential SaaS trends that will stand out in 2020. Before we dig any deeper into our top ten SaaS industry trends for 2020, let’s dispel some common myths surrounding the industry.

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TCO Considerations of Using a Cloud Data Warehouse for BI and Analytics

Enterprises are pouring money into data management software – to the tune of $73 billion in 2020 – but are seeing very little return on their data investments.

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Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. Researchers and practitioners have been using human-labeled data for many years, trying to understand all sorts of abstract concepts that we could not measure otherwise. That’s the focus of this blog post.

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Some highlights from 2020

Data Science and Beyond

My track record of posting here has been pretty poor in 2020, partly because of a bunch of content I’ve contributed elsewhere. Well, no one has compiled a meta-post of my public work from 2020 (that I know of), so it’s finally time to publish it myself. Technical work.