Remove 2023 Remove Apache Kafka Remove Data Lakes
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Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and…

ODSC - Open Data Science

Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and Google’s PaLM 2 Building a Pizza Delivery Service with a Real-Time Analytics Stack The best businesses react quickly and with informed decisions. Final ODSC Europe 2023 Schedule Released! Here’s what you can expect from ODSC Europe.

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Pictures and Highlights from ODSC Europe 2023

ODSC - Open Data Science

We’re a few weeks removed from ODSC Europe 2023 and we couldn’t have left on a better note. The week was filled with engaging sessions on top topics in data science, innovation in AI, and smiling faces that we haven’t seen in a while. That’s it for our ODSC Europe 2023 highlights! What’s next?

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All of the Free Virtual Sessions Coming to ODSC Europe 2023

ODSC - Open Data Science

Wednesday, June 14th Me, my health, and AI: applications in medical diagnostics and prognostics: Sara Khalid | Associate Professor, Senior Research Fellow, Biomedical Data Science and Health Informatics | University of Oxford Iterated and Exponentially Weighted Moving Principal Component Analysis : Dr. Paul A.

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Watch the Top ODSC Europe 2023 Virtual Sessions Here

ODSC - Open Data Science

Below you’ll find just a few of the many expert-led sessions at ODSC Europe 2023 that attendees loved — and you can view them for yourself here ! And don’t miss the chance to join us for our upcoming free virtual Generative AI Summit on July 20th and ODSC West 2023 in San Francisco (October 31st-November 3rd). What’s next?

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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

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The Evolution of Customer Data Modeling: From Static Profiles to Dynamic Customer 360

phData

In transitional modeling, we’d add new atoms: Subject: Customer#1234 Predicate: hasEmailAddress Object: "john.new@example.com" Timestamp: 2023-07-24T10:00:00Z The old email address atoms are still there, giving us a complete history of how to contact John. Both persistent staging and data lakes involve storing large amounts of raw data.