Datafold Blog

Always keen on exploring the ever-changing world of data

14 April, 2021

Good Data: How Spotify, Shopify & Lyft approach data quality

We are thrilled to announce we are finally on Clubhouse! Our latest conversation of data, engineering, and data quality featured co-host George Xing [https://www.linkedin.com/in/georgexing/], Zeeshan Qureshi [https://www.linkedin.com/in/zeeshanq/], and Josh Temple [https://www.linkedin.com/in/joshtemple/]. They joined us from Lyft, Shopify, and Spotify, respectively. Below is a lightly edited transcript of our interview. This is the first in a series of interviews about unlocking different app

07 April, 2021

Data Quality Meetup #3

Why implement regression testing for ETL code changes, how to align data producers and consumers, and what Data teams at Carta, Thumbtack, Shopify & Clari do to solve data quality.

05 February, 2021

Datafold + dbt: The Perfect Stack for Reliable Data Pipelines

Take your ETL workflow to the next level with Datafold and dbt integration that automates data testing and provides column-level data lineage

30 November, 2020

The Data Quality Flywheel

The more people that are looking at the data, and the more apps that are using the data, the faster data quality issues will be identified and resolved.

26 November, 2020

Digest of Data Quality Meetup #2

On the second Data Quality Meetup, we discussed three types of data testing and when to apply them, new-generation ETL frameworks and ROI of open-source data catalogs.

19 November, 2020

Datafold raises a $2.1M Seed round led by NEA

Over the past 10 years, we've seen a great advancement in technologies and tools for analytics and machine learning: with today’s modern analytics stack, we have fast and scalable data warehouses, dirt-cheap data storage, capable ETL orchestrators, and powerful BI tools.