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Data Engineers of Netflix?—?Interview with Kevin Wylie

Netflix Tech

Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. In his free time he enjoys gardening and playing sports with his 4 kids.

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The Right Stuff: The Role of MLOps in AI Success

CIO

Interestingly, many companies do just that, creating a disconnect between data science teams and IT/DevOps when it comes to AI development. Data scientists would really love to just build models and do real core data science. This gap is a significant reason why AI pilot projects fail. “AI

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Analytics Maturity Model: Levels, Technologies, and Applications

Altexsoft

We will describe each level from the following perspectives: differences on the operational level; analytics tools companies use to manage and analyze data; business intelligence applications in real life; challenges to overcome and key changes that lead to transition. the specialists, tools, and applications of Descriptive analytics.

Analytics 102
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9 Great Reasons to Join the DataRobot AI Experience Virtual Event Jun 7-8

DataRobot

Formula 1 is the fastest growing sport in America and has been popular around the world for decades. Supporting the technology ecosystems that top organizations use today, DataRobot aligns with the platforms, applications, and strategic services most in demand. Even more DataRobot customer stories will be unveiled at the virtual event.

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6 Frontiers for Data Virtualization in 2021

TIBCO - Connected Intelligence

Imagine you’re a data engineer at a Fortune 1000 company. You use data virtualization to create data views, configure security, and share data. One: Streaming Data Virtualization. All this data is in motion. But first-generation data virtualization tools are designed for data at rest.

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Win-Win: Everyone Benefits from Adding Data Virtualization to Your Data Integration Toolbox

TIBCO - Connected Intelligence

Sports are like that. That’s what I like about data virtualization. By adding data virtualization to your data integration toolbox, everyone can win across your organization—from data consumers to data engineers. . A Win for Data Engineers. Someone wins. Someone loses. . Win-win-win!

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Top Data Science experts you should know about

Apiumhub

Schloss’s areas of expertise include Big Data, analytics, BI, IoT, and data warehousing. With a combined experience in both startup and G500 environments, she has successfully launched numerous products, from business-focused analytic applications to data warehousing tools such as Business Objects Data Services.