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At a loss for data project ROI? Evaluate it like a product

CIO Business Intelligence

In 2006, British mathematician Clive Humby proclaimed, “Data is the new oil.”. Today, Doug Laney, innovation fellow of data and analytics strategy at West Monroe, disputes Humby’s assertion on a technicality: “When you use a drop of oil, you can only use it one way at a time,” Laney says. Humby had bona fides to make that claim.

ROI 114
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The Complete Digital Analytics Ecosystem: How To Win Big

Occam's Razor

Helpful post: Best Metrics For Digital Marketing: Rock Your Own And Rent Strategies.]. While there are no such things as blessed KPIs everyone must follow – because everyone is not executing the exact same strategy -, some metrics can never be KPIs. Your digital analytics tools are full of metrics. Averages this. Total that.

Analytics 150
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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

Selection and aggregation of forecasts from an ensemble of models to produce a final forecast. Calendaring was therefore an explicit feature of models within our framework, and we made considerable investment in maintaining detailed regional calendars. Adjustments for effects: holiday, seasonality, and day-of-week effects.

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SAP Industry Insights Podcast Highlights of 2021 with Host Tom Raftery

Timo Elliott

Most people rent skis rather than buying, because it’s easier and cheaper and more convenient — so why not apply that model to more things? I also loved the episode The Race to Zero: Regenerative Business Models for a Sustainable Future. The logic of the argument was very convincing. with the CTO of SAP Fieldglass.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. As the story goes, the general history of DG is punctuated by four eras: “Application Era” (1960–1990) – some data modeling, ?though Those days are long gone if they ever existed.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

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A Big Data Imperative: Driving Big Action

Occam's Razor

It is not my hope to encourage you to copy/paste the strategy outlined, or to use the tools shown. I've championed the need to leverage frameworks like the Digital Marketing & Measurement Model , in the web context, to ensure that the analysis we do is deeply and powerfully grounded in what's important to the business.

Big Data 127