Remove teams
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How to build a data team

Christophe Blefari

My personal collection of the best resources to bootstrap a data team and get inspired from what others are doing.

Building 130
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The Data Discovery Team

Jesse Anderson

A Guest Post by Ole Olesen-Bagneux In this blog post I would like to describe a new data team, that I call ‘the data discovery team’. And that is what the data discovery team that I propose in this blog post should work on: searching for data. 1) The data discovery team must work on discovering the IT landscape.

Metadata 147
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Useful Project Management Tips for Agile Development Teams

Knowledge Hut

Before proceeding, it is important to know that management of the task and a lengthy project is imperative for every development team for the precision of task and quality output. Earlier, the software development team used to take the assistance of the waterfall project management for the completion of the project management task.

Project 98
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How To Set Up Your Data Analytics Team For Success – Centralized vs Decentralized vs Federated Data Teams

Seattle Data Guy

Success in the data world hinges on team setup. I’ve delved into onboarding and standards in previous articles, but never into the structure of data teams. Typically, there are three configurations: Centralized, Decentralized, and Federated. Most companies I’ve seen use a mix of these.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

Join us for an enlightening session to empower you to lead your team to greater heights. Takeaways: Uncover and navigate through common pitfalls that are plaguing product teams today. Explore proven solutions, laying the groundwork for triumphant product launches.

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How To Eliminate Burnout And Make Agile Teams More Productive

Knowledge Hut

Agile methodology helps developers find better ways to work in a team, adapt to change, and increase market speed. At such times, the IT team must deal with the project's tight deadlines, resulting in extreme work stress. It’s been religiously followed by a team which truly works in Agile methodology. It worked for our team.

Project 98
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Common Pitfalls in Deploying Airflow for Data Teams

Seattle Data Guy

This is what spurred me to write the article “Should You Use Airflow” because there are plenty of people who don’t enjoy Airflow or… Read more The post Common Pitfalls in Deploying Airflow for Data Teams appeared first on Seattle Data Guy.

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Entity Resolution Checklist: What to Consider When Evaluating Options

The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success!

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction. It emphasizes engineers’ efficiency and satisfaction during the product development process.

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The Data Metaverse: Unpacking the Roles, Use Cases, and Tech Trends in Data and AI

Speaker: Aindra Misra, Sr. Staff Product Manager of Data & AI at BILL (Previously PM Lead at Twitter/X)

Key objectives: Introduction to the structures and ownership dynamics of data platform, analytics and AI teams, along with an exploration of various roles in the data ecosystem. Join us for a forward-looking exploration of the future data landscape!

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New Study: 2018 State of Embedded Analytics Report

We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Why do some embedded analytics projects succeed while others fail? Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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5 Early Indicators Your Embedded Analytics Will Fail

Many application teams leave embedded analytics to languish until something—an unhappy customer, plummeting revenue, a spike in customer churn—demands change. But by then, it may be too late. In this White Paper, Logi Analytics has identified 5 tell-tale signs your project is moving from “nice to have” to “needed yesterday.".

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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics.

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The Essential Guide to Building Analytic Applications

Embedding analytics in software presents some unique opportunities—and poses unique challenges—to software teams. What should software teams know about implementing security that works with the rest of their products? What are best practices when designing the UI and UX of embedded dashboards, reports, and analytics?

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The Big Payoff of Application Analytics

And they won’t cut it for your end users, your development team, or your business. The value of embedding analytics to users, development teams, and the bottom line. Outdated or absent analytics won’t cut it in today's data-driven applications. That's what drove the five companies in this eBook to change their approach to analytics.