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Data Teams

Data Teams

July 15, 2020 1 minute read

How Five Data Leaders Are Leading Teams Through the Pandemic

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Jessica Schimm

Content Marketing Manager

Mode interviewed five data leaders during the COVID-19 pandemic to discuss their strategies for maneuvering through a crisis. Learn how they use data to make crucial decisions and lead their teams through uncertainty.

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Data Teams

May 5, 2020 3 minute read

You... May Enjoy These Recent Mode Product Enhancements

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Mike DeCarlo

Product Manager

Happy May! We’d like to spotlight some new analytics workflow enhancements and improvements to managing large organizations in Mode.

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Data Teams

September 19, 2019 1 minute read

3 Tips for Effective Data Science Processes

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Benn Stancil

Chief Analyst

Here are some quick notes on how to accelerate your data science efforts for a larger impact.

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Data Teams

May 2, 2019 3 minute read

4 Lessons to Keep Your Data Model Under Control

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Joel Carron

Data Scientist at Mode

A data model defines how an organization's various data sources are organized, related, and accessed. As data sources are added and complexity grows, the data model makes a big impact on the productivity and efficiency of anyone in the company that works with data.

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Data Teams

March 27, 2019 2 minute read

Get More Done With the New API Cookbook and Developer Docs

Leqi Long

Senior Customer Success Engineer

Today, we're announcing the newly-designed Mode developer site. The new site contains extensive documentation of commonly used API endpoints, plus a few new ones. We've also added an API cookbook give you templates for common tasks. These new resources make it easier than ever before to build with Mode.

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Data Teams

March 5, 2019 2 minute read

Empathy and the Art of Analytical Persuasion

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Benn Stancil

Chief Analyst

As analysts and data scientists, we have to make our work compelling and persuasive to change the way our organizations think. It can be easy to assume that our well-constructed graphs and tables are plenty convincing on their own. But this ignores a fundamental fact of analytics: it's still a human making the decision behind those numbers, and that person is rarely as quantitatively inclined as we are. Persuading this audience takes a skill that isn't discussed enough in the data science community: empathy.

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