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Do You Need a DataOps Dojo?

DataKitchen

We’ll also discuss building DataOps expertise around the data organization, in a decentralized fashion, using DataOps centers of excellence (COE) or DataOps Dojos. Centralizing analytics helps the organization standardize enterprise-wide measurements and metrics. Test data management and other functions provided ‘as a service’ .

Metrics 243
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10 Technical Blogs for Data Scientists to Advance AI/ML Skills

DataRobot Blog

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

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eCommerce Brands Use Data Analytics for Conversion Rate Optimization

Smart Data Collective

E-commerce businesses around the world are focusing more heavily on data analytics. There are many ways that data analytics can help e-commerce companies succeed. Understanding E-commerce Conversion Rates There are a number of metrics that data-driven e-commerce companies need to focus on.

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What you need to know about product management for AI

O'Reilly on Data

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade.

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12 Marketing Reports Examples You Can Use For Annual, Monthly, Weekly And Daily Reporting Practice

datapine

Today’s digital data has given the power to an average Internet user a massive amount of information that helps him or her to choose between brands, products or offers, making the market a highly competitive arena for the best ones to survive. First things first – organizing and prioritizing your marketing data.

Reporting 280
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When models are everywhere

O'Reilly on Data

Infinite Jest was published in 1996, just as the modern Web was coming into being. It predates recommendation engines, social media, engagement metrics, and the recent explosion of AI, but not by much. The Entertainment” is not the result of algorithms, business incentives and product managers optimizing for engagement metrics.

Modeling 195