Hacker Noon

Learn SQL techniques for data warehousing, including handling incremental tables, using MERGE statements, and converting tables to JSON objects.

16 SQL Techniques Every Beginner Needs to Know

ByteByteGo

This week’s system design refresher: OAuth 2 explained in simple terms. The diagram below shows a comparison of URL, URI, and URN. Do you know the differences? Do you use a data warehouse or a data lake to retrieve data? Twitter 1.0 Tech Stack is the biggest technology newsletter on Substack.

EP66: Comparison of URL, URI, and URN

Medium

This post discusses a data engineer project that involves transforming data from a PostgreSQL database to an S3 datalake and then to a PostgreSQL data warehouse. The author shares their experience and methodology, as well as the tools used. They also highlight the problems they faced during the project.

Data Engineer Project: Postgres (Database) to S3 (DataLake) to Postgres (Data Warehouse) | Prep Coffee Inventory Management

Decube

ETL and ELT are two approaches to data integration. ETL involves extracting data from source systems, transforming it into an analysis-ready format, and loading it into a data warehouse. ELT involves loading data into the target system first and transforming it as needed.

What is ETL? Difference between ETL and ELT

A data warehouse is a centralized repository for storing and analyzing structured and historical data from multiple sources to support business intelligence and analytics. It enables organizations to consolidate data for reporting, analysis, and decision-making. Readers can explore how data warehouses enable organizations to perform complex queries, generate reports, and gain insights into business performance by integrating data from disparate sources and transforming it into actionable information.

Best of Data Warehouse — 2023