Pearson's Director: Learn How to Create and Use Data Models
Skills:
Data Literacy60%
Michael Hernandez had a vision for his team at Pearson Education: “Ensure a customer's success with our products to earn brand loyalty". It's relational first, then we align their needs to our solutions based on what is learned, not just what we sell." With limited resources, he needed to prove the value of adding the right tools to focus on specific customers who needed the most assistance.
To combine the customer narrative with usage and support patterns for signs of risks, he turned to Data Science Dojo. Having led customer-facing teams for many years, he knew there were patterns in the customer narrative, but needed to prove which actions would have the most impact on senior leadership. In September 2017 he attended our Data Science & Data Engineering Bootcamp in Austin with self-proclaimed “outdated programming knowledge”, but an eye for what to do with the data models once he could learn how to create them.
After returning to Pearson, the impact was almost immediate. By aligning his vision of “ensuring success first”, he began to create data models outlining risk and opportunity indication campaigns. The collaboration of this data with various teams helped increase the speed and accuracy at which they could provide the right guidance at the right time for the customer’s success. They tried various implementations using tools such as R, Python, and even Power BI to unleash a proactive support model instead of a historically reactive one.
This new practice brought dramatic growth in customer success for this product line, resulting in a giant leap in customer retention, growth, and revenue. The impact was felt across the division, leading to a promotion, and putting his team at the front line for expanding this across other digital products.
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At Data Science Dojo, we believe data science is for everyone. Our data science trainings have been attended by more than 10,000 employees from over 2,500 companies globally, including many leaders in tech like
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Reading External Data Sources | Beginning Azure ML | Part 2
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Scrub Missing Values & Project Columns | Beginning Azure ML | Part 5
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Feature Engineering & R Script | Beginning Azure ML | Part 6
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Building Your First Model | Beginning Azure ML | Part 7
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Run and Fine-Tune Multiple Models | Beginning Azure ML | Part 8
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Deploying Your First Predictive Model As a Web Service | Beginning Azure ML | Part 9
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Using R API to Obtain Predictions From Your Web Service Beginning Azure ML | Part 10
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Software Engineer at Microsoft Reveals About His Experience with Data Science Bootcamp
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Wade Wimer on the Impact of Data Science Bootcamp
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Analyzing Data with Data Science Bootcamp: Hannah Richta's Revelation
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Applying Data Science Skills to The Current Role with Bootcamp: Marcos Lacayo's Revelation
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Lance Milner on the Impact of Data Science Bootcamp
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Deloitte's Data Scientist Revelation: Learning Predictive Analytics with Data Science Bootcamp
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Rajesh Patil's Experience at Data Science Bootcamp As an Enterprise Architect
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Michael Atlin on the Impact of Data Science Bootcamp
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Ceo's Revelation about Data Science Bootcamp
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Kevin Hillaker on the Impact of Data Science Bootcamp
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Unisys Manager's Revelation: Visualizing Real Time Data with Data Science Bootcamp
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Learn Data Mining with Data Science Bootcamp: Ryan LaBrie's Revelation
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Vang Xiong on the Impact of Data Science Bootcamp
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Data Scientist's Experience at Our Data Science Bootcamp
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Alejandro Wolf Yadlin on the Impact of Data Science Bootcamp
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Introduction To Titanic Kaggle Competition | Part 1
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Learning How to Code in R with Data Science Bootcamp: Priscilla Mannuel's Revelation
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Andrew Berman On Why Data Science Bootcamp Is Better Fit for Him
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How To Do Titanic Kaggle Competition in R | Part 3.1
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Missing & Duplicated Data | Introduction to Data Mining | Part 8
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Graph and Ordered Data | Introduction to Data Mining | Part 5
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