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Rising Tide Rents and Robber Baron Rents

O'Reilly on Data

Google and Amazon were still atop their respective hills of web search and ecommerce in 2010, and Meta’s growth was still accelerating, but it was hard to miss that internet growth had begun to slow. Now a typical page of Amazon product search results consists of 16 ads and only four organic results. The market was maturing. I think not.

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How to make the most of global talent opportunities

CIO Business Intelligence

The early 2010’s practice of co-locating talent supercharged collaboration, but also limited organizations’ ability to scale with a workforce based in high-density, cost-prohibitive metros. Each of these companies above has also invested in technologies to streamline internal processes and reduce the operational risks of distributed teams.

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Estimating the prevalence of rare events — theory and practice

The Unofficial Google Data Science Blog

Of course, any mistakes by the reviewers would propagate to the accuracy of the metrics, and the metrics calculation should take into account human errors. If we could separate bad videos from good videos perfectly, we could simply calculate the metrics directly without sampling. The missing verdicts create two problems.

Metrics 98
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10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big

Occam's Razor

Because every tool uses its own sweet metrics definitions, cookie rules, session start and end rules and so much more. Yet case studies in some sense reduced risk, even if they were simply over blown marketing fluff written by the vendor. There is such little risk to actually trying. Why do I need a case study? Neither do you.

Analytics 118
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A CDO’s Guide to the Data Catalog

Alation

Between 2010 and 2018 the number of CDOs present in Fortune 1500 companies increased nearly 8-fold. On the other, a data free-for-all creates risk—not only of data leaks with regulatory penalties, but also of inefficiency, as the same work and assets may be duplicated across the organization. Protecting Sensitive Data.

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Unintentional data

The Unofficial Google Data Science Blog

With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. Looking at metrics of interest computed over subpopulations of large data sets, then trying to make sense of those differences, is an often recommended practice (even on this very blog).

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Where Programming, Ops, AI, and the Cloud are Headed in 2021

O'Reilly on Data

Observability” risks becoming the new name for monitoring. We don’t see that in our data, though there are certainly some metrics to say that artificial intelligence has stalled. It’s tempting to think of Flask and Vue as “new” platforms, but they were released in 2010 and 2014, respectively; they’ve had time to establish themselves.