François Nguyen

MARCH 22, 2021

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.

Architecture 130

Architecture Technology Google Cloud Metadata 130

Knowledge Hut

MARCH 28, 2024

Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. GDPR, HIPAA), and industry standards.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

NOVEMBER 2, 2023

Azure Data Ingestion Pipeline Create an Azure Data Factory data ingestion pipeline to extract data from a source (e.g., Azure SQL Database, Azure Data Lake Storage). Data Aggregation Working with a sample of big data allows you to investigate real-time data processing, big data project design, and data flow.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Data Engineering Podcast

FEBRUARY 18, 2024

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

Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

FEBRUARY 4, 2024

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. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

SQL 173

SQL Data Lake High Quality Data Data Pipeline 173

Monte Carlo

MAY 14, 2024

Delta Lake : Released by Databricks in 2019, Delta Lake was created to bring reliability and robustness to data lakes, incorporating ACID (Atomicity, Consistency, Isolation, Durability) transactions into Apache Spark to maintain data integrity across complex transformations and updates.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Engineering Podcast

JANUARY 21, 2024

In this episode Tasso Argyros, CEO of ActionIQ, gives a summary of the major epochs in database technologies and how he is applying the capabilities of cloud data warehouses to the challenge of building more comprehensive experiences for end-users through a modern customer data platform (CDP).

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147