Datakin

The news of our acquisition of Datakin broke in #TechCrunch. Hours later, at @DataCouncilAI in Austin, @J_ (Julien Le Dem) announced it from the stage! Watch the announcement during the talk on #DataLineage with #Airflow using @OpenLineage. youtube.com/watch?v=lqz12s…

2/2 To see @rossturk himself dive deeper into OpenLineage (the OSS tool for data lineage), along with Staff Software Engineer @PeladoCollado, join them on Tuesday at 2 PM (ET) for our next webinar. hubs.ly/Q016N5Tq0

1/2 To operate in today’s distributed #data ecosystems, you need a complete and up-to-date picture of your data. And you can’t have one without #DataLineage. Learn why it matters, expertly explained by @rossturk, our Senior Director of Community. #blog hubs.ly/Q0177vcx0

The 80th edition of @data_weekly featuring 📚 @astronomerio ready for its next mission after @DatakinHQ acquisition, $213M Series C 📚 @jonloyens How Should We Be Thinking about Data Lineage? dataengineeringweekly.com/p/data-enginee…

The contributions we make to @OpenLineage and @MarquezProject will continue. In fact, we will be able to dedicate more resources to this important work.

Datakin is excited to announce that we have been acquired by @astronomerio, the commercial developer of Apache Airflow. datakin.com/joining-astron…

When we started Datakin, we had an ambitious goal: to bring data lineage to the modern data stack. This goal has not changed; our new friends at Astronomer share it with us!

“Our job duration tab enables a more detailed inspection of how a given job fits into the overall pipeline. You can evaluate the execution times of all the upstream jobs in the most recent run cycle.” datak.in/3n8VocI

Without a real time #datalineage graph “not only is it hard to identify duration issues, it’s costly and time-consuming to diagnose their cause.” datak.in/30kpNfj

Collecting #datalineage from @ApacheSpark is easy, and can help you keep your pipeline running smoothly. Read more on the @openlineage blog: datak.in/3wHiV7H

Sometimes a long-running data pipeline job is more than just an inconvenience, it is the sign of a more complex problem. In this post, Peter Hicks shows how to identify data pipeline bottlenecks with #datalineage and Datakin: datak.in/3D6PVbU

🚨🔥 new @dbt_labs Analytics Engineering Podcast episode is LIVE! @jthandy and I sit down with @J_ from @DatakinHQ / @OpenLineage to talk about open source data standards, data lineage, and tool connectivity. Give it a listen👇 open.spotify.com/episode/1Tjni9…

The team at Northwestern Mutual has begun to capture and trace the lineage of key datasets, creating a real-time map of their pipelines. Over on the OpenLineage blog, Kevin Mellott explains how real-time #datalineage helps them stay ahead. datak.in/3Cip0JY

I'll be chatting today at 1:50pm PT with Kevin Mellott from @NM_Financial about lineage and metadata. @MarquezProject @OpenLineage

- @AashViswanathan, Senior Data Scientist @Atlassian - Julien Le Dem (@J_) CTO and Co-Founder @DatakinHQ - @SriniKadamati, Senior Data Scientist @preset_data - Rohit Choudhary (@rconline), Founder and CEO @acceldataio And many more! Check here👇 #speakers" target="_blank" rel="nofollow noopener">dataagility.io/#speakers

"If you use Datakin to observe @getdbt models as they run, you can always know exactly where your datasets came from and how they were created." datak.in/3vgLZlQ

Using @OpenLineage, the team at Northwestern Mutual has begun to capture and trace the #datalineage of key datasets, creating a real-time map of their pipelines. Register now for the session on Oct 21 at datak.in/3lJZBTz and learn how it helps them stay ahead of the game.

In this tutorial, we show how to use Datakin to observe @getdbt jobs. Learn how to trace #datalineage, observe changes across the pipeline, and troubleshoot performance bottlenecks: datak.in/3BL0XTB

"Increasingly, we will find data science at the edges, decentralized and largely ungoverned. We think that data lineage is the key. It can establish a 'chain of custody' for key datasets, contextualize fragmented work, and build organzational trust." datak.in/3Bfigfg

#DataLineage tip: “Be sure to use the `{{ ref() }}` and `{{ source() }}` jinja functions when referring to data sources if you want to accurately capture @getdbt data lineage with @MarquezProject.” datak.in/3FkfbNe