Remove Data Engineering Remove Data Ingestion Remove Data Lake
article thumbnail

How to learn data engineering

Christophe Blefari

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. Who are the data engineers?

article thumbnail

Data Engineering Weekly #179

Data Engineering Weekly

Learn More → Notion: Building and scaling Notion’s data lake Notion writes about scaling the data lake by bringing critical data ingestion operations in-house. Hudi seems to be a de facto choice for CDC data lake features.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

The No-Panic Guide to Building a Data Engineering Pipeline That Actually Scales

Monte Carlo

Your data engineering pipeline started simple: a few CSV exports, some Python scripts, and manual updates every week. You’re left wondering if there’s a breaking point where your DIY data solution won’t cut it anymore—and honestly, you might be there already. It means you’re scaling!

article thumbnail

Data Engineering Zoomcamp – Data Ingestion (Week 2)

Hepta Analytics

DE Zoomcamp 2.2.1 – Introduction to Workflow Orchestration Following last weeks blog , we move to data ingestion. We already had a script that downloaded a csv file, processed the data and pushed the data to postgres database. This week, we got to think about our data ingestion design.

article thumbnail

Data Engineering Weekly #168

Data Engineering Weekly

link] RevenueCat: How we solved RevenueCat’s biggest challenges on data ingestion into Snowflake A common design feature of modern data lakes and warehouses is that Inserts and deletes are fast, but the cost of scattered updates grows linearly with the table size. Counting is the hardest problem in data engineering.

article thumbnail

Data Ingestion: 7 Challenges and 4 Best Practices

Monte Carlo

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

article thumbnail

What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData: Data Engineering

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.