ETL

ELT for the Data Consumer

You’ve likely heard about ELT — Extract Load and Transform… the Modern Data Stack’s evolution on ETL. This is a game changer by nature in that it enables organizations to ingest raw data into the data warehouse and transform it later. ELT gives end-users access to the entirety of the datasets they need by circumventing downstream issues of missing data that could prevent a specific business question from being answered.

jared parker8 min read

Survival of the Fittest: ETL vs. ELT

As data became more and more available to companies, data integration became one of the most crucial challenges for organizations. In the past decades, ETL (extract, transform, load) and later ELT (extract, load, transform) emerged as data integration methods that transfer data from a source to a data warehouse.

benedetta cittadin10 min read

What is Reverse ETL? The Definitive Guide

The data ecosystem has changed drastically over the last six years and we've witnessed the rise and fall of several different technologies. However, there’s one constant that’s remained the same, the cloud data warehouse.

Hightouch18 min read

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5 Helpful Extract & Load Practices for High-Quality Raw Data

ELT is becoming the default choice for data architectures and yet, many best practices focus primarily on “T”: the transformations.

Sven Balnojan8 min read

ETL

ELT for the Data Consumer

Survival of the Fittest: ETL vs. ELT

What is Reverse ETL? The Definitive Guide

5 Helpful Extract & Load Practices for High-Quality Raw Data

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