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Bringing Automation To Data Labeling For Machine Learning With Watchful

Data Engineering Podcast

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?

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Data News — Week 23.14

Christophe Blefari

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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Data News — Week 13.14

Christophe Blefari

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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Modern Data Management Essentials: Exploring Data Fabric

Precisely

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?

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?Data Engineer vs Machine Learning Engineer: What to Choose?

Knowledge Hut

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.

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Azure Synapse vs Databricks: 2023 Comparison Guide

Knowledge Hut

It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads.

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Building a Scalable Search Architecture

Confluent

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.