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Robust Experimentation and Testing | Reasons for Failure!

Occam's Razor

Since you're reading a blog on advanced analytics, I'm going to assume that you have been exposed to the magical and amazing awesomeness of experimentation and testing. And yet, chances are you really don’t know anyone directly who uses experimentation as a part of their regular business practice. Wah wah wah waaah.

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Do You Need a DataOps Dojo?

DataKitchen

Centralizing analytics helps the organization standardize enterprise-wide measurements and metrics. A centralized team can publish a set of software services that support the rollout of Agile/DataOps. Central DataOps process measurement function with reports. They also can provide education and training enterprise-wide.

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A New Era of Value-Driven AI

DataRobot Blog

Today, DataRobot unveiled a new AI platform designed to help businesses derive measurable value from AI – something that too many organizations today have been unable to achieve. We are offering customers rapid experimentation and value identification, with both code-first and no-code approaches. And we’re just getting started.

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What you need to know about product management for AI

O'Reilly on Data

You might establish a baseline by replicating collaborative filtering models published by teams that built recommenders for MovieLens, Netflix, and Amazon. It may even be faster to launch this new recommender system, because the Disney data team has access to published research describing what worked for other teams.

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Methods of Study Design – Experiments

Data Science 101

Some pitfalls of this type of experimentation include: Suppose an experiment is performed to observe the relationship between the snack habit of a person while watching TV. Reliability: It means measurements should have repeatable results. For eg: you measure the blood pressure of a person.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Instead, we focus on the case where an experimenter has decided to run a full traffic ramp-up experiment and wants to use the data from all of the epochs in the analysis. Companies like Google [2], Amazon [3], and Microsoft [4] have all published scholarly articles on this topic.

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eCommerce Brands Use Data Analytics for Conversion Rate Optimization

Smart Data Collective

Several organizations and research firms publish e-commerce conversion rate benchmarks based on industry data and trends. Experimentation is the key to finding the highest-yielding version of your website elements. You can find comprehensive E-commerce conversion rate benchmarks here.