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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. What delivers the greatest ROI? How do you select what to work on?

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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. Ultimately, business intelligence and analytics are about much more than the technology used to gather and analyze data.

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Advanced Data Discovery and Augmented Analytics: Simple, Sophisticated Tools for Business Users

Smarten

Business users can quickly and easily prepare and analyze data and visualize and explore data, notate and highlight data and share data with others to identify the important ‘nuggets’, buried in traditional data, and to connect the dots, find exceptions, identify patterns and trends and better predict results.

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Knowledge

Occam's Razor

Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. Seven Steps to Creating a Data Driven Decision Making Culture. Customer Lifetime Value ROI, Buzz Monitoring, Click Fraud. Data Quality Sucks, Let's Just Get Over It.

KPI 124
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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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Dear Avinash: Attribution Modeling, Org Culture, Deeper Analysis

Occam's Razor

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Bjoern Sjut3: My main issue at the moment: How will multi-channel funnels and ROI calculations work in a multi device world? They also reveal things that starting to become scary (Privacy!

Modeling 124
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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. That body of work has much to offer the practice of leading data science teams.