Remove Data Collection Remove Experimentation Remove Information Remove ROI
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What you need to know about product management for AI

O'Reilly on Data

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. These companies eventually moved beyond using data to inform product design decisions.

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Themes and Conferences per Pacoid, Episode 6

Domino Data Lab

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. Of course, some questions in business cannot be answered with historical data.

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Product Management for AI

Domino Data Lab

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. And then you’ll do a lot of work to get it out and then there’ll be no ROI at the end.

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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Information can get quite distorted after being abstracted that many times.

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Dear Avinash: Attribution Modeling, Org Culture, Deeper Analysis

Occam's Razor

Bjoern Sjut3: My main issue at the moment: How will multi-channel funnels and ROI calculations work in a multi device world? If your wish in the second part is to track effectiveness of advertising ( how to determine ROI ) then please see this post: Measuring Incrementality: Controlled Experiments to the Rescue! That is the solution.

Modeling 124
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10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big

Occam's Razor

Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. It is possible that you'll be the exception and build the first clickstream data warehouse where you'll deliver positive ROI (against the Total Cost of Ownership ). Likely not.

Analytics 118
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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions.