Datakin

Real-time, operational data lineage tracing that helps data engineers and data scientists find, fix, and prevent operational issues.

[Astronomer @astronomerio]

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.
https://t.co/fhHouuhrbI

[Astronomer @astronomerio]

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.
https://t.co/hdQVxobVKU

[Astronomer @astronomerio]

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
https://t.co/DLMsAJfdpo

[Data Engineering Weekly @data_weekly]

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?
https://t.co/driZQVM69Q

[Datakin @DatakinHQ]

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 @DatakinHQ]

Datakin is excited to announce that we have been acquired by @astronomerio, the commercial developer of Apache Airflow.

https://t.co/QsnLQ5FUiT

[Datakin @DatakinHQ]

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!

[Datakin @DatakinHQ]

“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.” https://t.co/VCQZxvNIM7

[Datakin @DatakinHQ]

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.” https://t.co/VrKZUBKtYK

[Datakin @DatakinHQ]

Collecting #datalineage from @ApacheSpark is easy, and can help you keep your pipeline running smoothly. Read more on the @openlineage blog: https://t.co/chOJL1iANK

[Datakin @DatakinHQ]

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: https://t.co/NzLe8gbVBt

[Julia Schottenstein @j_schottenstein]

🚨🔥 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👇
https://t.co/Etu0YaGFSG

[Datakin @DatakinHQ]

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.
https://t.co/o8sVlt0SYk

[Julien Le Dem @J_]

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

[Modern Data Stack @moderndatastack]

- @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👇
https://t.co/UfFyPIIlr9

[Datakin @DatakinHQ]

"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."
https://t.co/NKU6hiocsk

[Datakin @DatakinHQ]

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 https://t.co/VOwwOCPRWl and learn how it helps them stay ahead of the game.

[Datakin @DatakinHQ]

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:
https://t.co/W2Q5NlxtS2

[Datakin @DatakinHQ]

"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."
https://t.co/SXgtx5XHKV

[Datakin @DatakinHQ]

#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.”
https://t.co/yv2lTGQOg3