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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. Which means that OpenAI owns Samsung data. But is it really different than what we already have with Gmail or AWS? Microsoft data integration new capabilities — Few months ago I've entered the Azure world. seed round.

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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. Which means that OpenAI owns Samsung data. But is it really different than what we already have with Gmail or AWS? Microsoft data integration new capabilities — Few months ago I've entered the Azure world. seed round.

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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. Go to dataengineeringpodcast.com/ascend and sign up for a free trial.

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Cloud Business Intelligence: A Comparative Analysis of Power BI, QuickSight, and Tableau by Mike Morgan

Scott Logic

There is a preferred workflow to guide a user through the steps of data preparation, analysis and visualisation but this workflow is not mandatory. This really is a platform intentionally designed so that non-technical users can create reports, manipulate data, and perform in-depth data analysis operations.

BI 52
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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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Machine Learning Engineer vs Data Scientist - The Differences

ProjectPro

If you look at the machine learning project lifecycle , the initial data preparation is done by a Data Scientist and becomes the input for machine learning engineers. Later in the lifecycle of a machine learning project, it may come back to the Data Scientist to troubleshoot or suggest some improvements if needed.