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Toward a Data Mesh (part 2) : Architecture & Technologies

François Nguyen

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ? As you can see, this is in the code part where you are building your data pipelines, a misnomer because this is an over simplification.

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Top 10 Azure Data Engineer Job Opportunities in 2024 [Career Options]

Knowledge Hut

Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. Education & Skills Required Proficiency in SQL, Python, or other programming languages. Develop data models, data governance policies, and data integration strategies.

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Top 20 Azure Data Engineering Projects in 2023 [Source Code]

Knowledge Hut

Azure Data Ingestion Pipeline Create an Azure Data Factory data ingestion pipeline to extract data from a source (e.g., CSV, SQL Server), transform it, and load it into a target storage (e.g., Azure SQL Database, Azure Data Lake Storage). A strong understanding of data sourcing with SQL.

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Build A Data Lake For Your Security Logs With Scanner

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data.

Data Lake 147
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Tackling Real Time Streaming Data With SQL Using RisingWave

Data Engineering Podcast

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable. Starburst : ![Starburst

SQL 173
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Using Trino And Iceberg As The Foundation Of Your Data Lakehouse

Data Engineering Podcast

Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Data lakes are notoriously complex. Go to dataengineeringpodcast.com/dagster today to get started. Your first 30 days are free!

Data Lake 262
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Designing A Non-Relational Database Engine

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is brought to you by Datafold – a testing automation platform for data engineers that prevents data quality issues from entering every part of your data workflow, from migration to dbt deployment.