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Building Better Data Teams

Posted Aug 04
# Data Teams
# Data Tooling
# RN Production
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SPEAKER
Leanne Fitzpatrick
Leanne Fitzpatrick
Leanne Fitzpatrick
Director of Data Science @ Financial Times

Leanne is Director of Data Science at the Financial Times and is a passionate data leader with experience building and developing empowered data science and analytics teams in a variety of businesses. Leanne is in her element when developing and implementing strategic, technical, and cultural solutions to getting machine learning and data science into the operational ecosystem.

Leanne is an active part of the data and technology community, sharing innovation and insights to encourage best practices, from Manchester, UK to Austin, TX, and is an Advisory Panel Board Member. Outside of all things data you can ask Leanne about her golf swing (it’s not good - yet), her passion for American Football (specifically the Cincinnati Bengals), her latest sewing project, and her love for good music, food, and whisky.

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Leanne is Director of Data Science at the Financial Times and is a passionate data leader with experience building and developing empowered data science and analytics teams in a variety of businesses. Leanne is in her element when developing and implementing strategic, technical, and cultural solutions to getting machine learning and data science into the operational ecosystem.

Leanne is an active part of the data and technology community, sharing innovation and insights to encourage best practices, from Manchester, UK to Austin, TX, and is an Advisory Panel Board Member. Outside of all things data you can ask Leanne about her golf swing (it’s not good - yet), her passion for American Football (specifically the Cincinnati Bengals), her latest sewing project, and her love for good music, food, and whisky.

+ Read More
SUMMARY

We spent a lot of time talking about data tooling but we maybe spent not as much time talking about data organizations and efficiently running and organizing data teams.

What about starting with limitations instead of aspirations? Right constraints instead of the north star? In this session, let's learn more about a realistic take on the state of data organizations of today.

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