Data Preparation Database Database-centric 
Data Engineering Podcast
AUGUST 13, 2022
In this episode founder Shayan Mohanty explains how he and his team are bringing software best practices and automation to the world of machine learning data preparation and how it allows data engineers to be involved in the process. Can you describe what Watchful is and the story behind it?
Christophe Blefari
APRIL 8, 2023
At the same time Maxime Beauchemin wrote a post about Entity-Centric data modeling. Microsoft data integration new capabilities — Few months ago I've entered the Azure world. Today, Microsoft announces new low-code capabilities for Power Query in order to do "data preparation" from multiple sources.
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Christophe Blefari
APRIL 8, 2023
At the same time Maxime Beauchemin wrote a post about Entity-Centric data modeling. Microsoft data integration new capabilities — Few months ago I've entered the Azure world. Today, Microsoft announces new low-code capabilities for Power Query in order to do "data preparation" from multiple sources.
Precisely
JULY 18, 2024
This satisfies the needs of data owners, who require a simple way to make data products available to users and keep them up to date, and data users who demand user-friendly, self-service methods for finding and accessing trusted data. Can a data fabric architecture help you achieve your business goals?
Knowledge Hut
JUNE 20, 2023
The generalist position would suit a data scientist looking for a transition into a data engineer. Pipeline-Centric Engineer: These data engineers prefer to serve in distributed systems and more challenging projects of data science with a midsize data analytics team.
Knowledge Hut
JANUARY 30, 2024
Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? Patterns, trends, relationships, and knowledge discovered from the data.
Confluent
JUNE 18, 2019
As the databases professor at my university used to say, it depends. Using SQL to run your search might be enough for your use case, but as your project requirements grow and more advanced features are needed—for example, enabling synonyms, multilingual search, or even machine learning—your relational database might not be enough.
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