We relaunched our product, we revamped our brand. But why did this happen?
Our CEO Hung shares why a #ModernDataOpsCloud was necessary to solve the challenges in the data space.
Learn more about Y42's changes here: https://t.co/kVftBd1UnQ
https://t.co/VCWLdQrgcD
๐๐'๐ซ๐ ๐๐ฑ๐๐ข๐ญ๐๐ ๐ญ๐จ ๐ฎ๐ง๐ฏ๐๐ข๐ฅ "๐๐ฒ๐ญ๐ก๐จ๐ง ๐๐ง๐ ๐๐ฌ๐ญโ, ๐จ๐ฎ๐ซ ๐ฅ๐๐ญ๐๐ฌ๐ญ ๐ข๐ง๐ง๐จ๐ฏ๐๐ญ๐ข๐จ๐ง ๐๐๐ฌ๐ข๐ ๐ง๐๐ ๐ญ๐จ ๐๐ง๐ก๐๐ง๐๐ ๐๐๐ญ๐ ๐ข๐ง๐ ๐๐ฌ๐ญ๐ข๐จ๐ง ๐ฉ๐ซ๐จ๐๐๐ฌ๐ฌ๐๐ฌ.
With Python Ingest, you can:
๐ implement custom ingestion logic,
๐ remove boilerplate code to load data into your data warehouse, and
๐ get standardized metadata, lineage, and documentation out of the box.
Read on in our announcement post: https://t.co/2m1qJfdDWx
As we embrace the challenges and opportunities of 2024, it's crucial to stay ahead in the data world. We sat together with Madison Schott to discuss key industry trends and make 5 data predictions for 2024. ๐ฎ
Read on in our blog post: https://t.co/mVB7nEjPEV
We're introducing a new stateful, declarative approach for data pipelines. Ensuring auditable, simple, standardized code with full traceability and zero compute cost for changes. Read on here: https://t.co/uJEMnyZI5p
Sharing some best practices for working with dbt and BigQuery. Hands-on insights from a data practitioner. Discussing relevant BigQuery functions, table partitioning, and materialization strategies.
Check it out: https://t.co/tdjNK0zUnF
Calling all data enthusiasts! ๐งโ๐ป Say hello to Virtual Data Builds by Y42! Unify logical changes via Git, materialize code changes, and handle operational changes in a single structure - environment management for Data simplified! ๐ Detailed announcement in the comments.
Data teams keep making the same mistakes over and over again. Why is that? ๐ค
Hereโs our guess:
โ Lack of reflection and learning
โ Ineffective collaboration
โ Inadequate documentation
โ Failure to adapt to change
Learn more here: https://t.co/XDFDFE6JyB
#Readoftheweek ๐ค๐๐ผ
Poor data quality undermines all the time and effort you put into your work.
โ Your systems don't matter
โ How robust your pipelines are doesn't matter
Learn more about the importance of #dataquality for #dataengineers here: https://t.co/ud9IEDJ3TG
Want to improve your company's #datagovernance program this year?
๐๐ผ Check out our #readoftheweek to learn how you can implement data governance best practices into your day-to-day work:
https://t.co/6i6acmjXfc
Thank you to everyone who joined our #webinar with @redsift and @googlecloud on the benefits of automating your data pipelines.
๐๐ผ If you missed out on the webinar, you can watch the recording here: https://t.co/SGAHm8IbwI
Part of a data team's responsibility is improving a company's overall #dataliteracy.
Start sharing #datacontent with business users, beginner data analysts, or anyone in between.
Here's our pick for their perfect #readoftheweek: https://t.co/UtU84v7z0E
Have we already mentioned that we have a #webinar coming up? ๐
โ Learn how to manage increasing data needs and requests.
โ Learn how to automate your data infrastructure as your company grows.
๐๐ผ Sign up here:ย https://t.co/bCn7N4d3Er
Do you know the difference between #datamanagement and #datagovernance?
๐๐ผ Check out our #readoftheday to learn the differences, similarities, and use cases of data management and data governance:
https://t.co/ZvmTWgenLM
Looking for an insightful read to wrap up the week? ๐ค
How about discovering the power of #Git workflows and branching strategies to #versioncontrol your #dataproducts?
Check out our recommended #readoftheweek here: ๐๐ผ
https://t.co/LrnEooI9dp
Discover the power of automated #datapipelines!
Join Eliott Sacau (@redsift ), Jelena Mijuskovic (@Google ) and Ba Khai Tran (@y42dotcom ) in our upcoming #webinar!
๐๐ผ Sign up here: https://t.co/NuTkwfZ20U
Here are 3 steps to follow if you want to implement #dataownership within your organization.๐๐ผ
1๏ธโฃ Get an overview of all your data assets by making an inventory
2๏ธโฃ Determine domain experts per data asset
3๏ธโฃ Implement a data catalog for better traceability
๐๐ผ This is what you need to do to avoid not knowing when a data model failed. ๐๐ผ
Test intermediate and core models too! ๐ก
If you don't, you let errors pass onto your final model and have to check all previous models to identify the culprit. ๐ซ
#datatesting#datamodeling
Types of #datagovernance frameworks:
โ Command and control framework
โ Traditional frameworkย
โ Non-invasive frameworkย
Which one should you choose? That will depend on your company goals and team structure.
Here are the 6 key benefits of #datamonitoring.๐๐ผ
1๏ธโฃ Faster debugging and minimized inconsistencies
2๏ธโฃ Increased business efficiency
3๏ธโฃ Stable and standardized data pipeline
4๏ธโฃ Faster retrieval of actionable data
5๏ธโฃ Reduced data preparation time
6๏ธโฃ Cost-effectiveness