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Modern Data Community

Public • 568 • Free

4 contributions to Modern Data Community
Metric Layer in dbt Core.
Hey team! One of my companies goal the following quarter will be to define an aggregated metric layer for rapid insight of business important metrics. I've done something similar previous but not with dbt. I'd like to know if anyone has done this with dbt core and how would be the best way to approach it. Thanks!
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New comment 7d ago
Public Data Tooling
Hey! In my company we're on our way to release some public data to our users. I'd like to step up this and not only release the data via a public s3 but offer our users a tool to explore and aggregate this datasets easily. ¿Do you know if something like this exists? I've been looking but haven't found anything useful yet. Update: I'm looking for something like Dune Analytics but for general data (not scoped to blockchain as this project is.) Thanks!
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New comment 26d ago
1 like • 29d
Thanks Tomas! This is actually a simple idea I've not thought of. Mainly because we use metabase for our internal users. But I think I could leverage Metabase's public dashboards & questions feature to do this :)
Migrate Metabase Question dependencies.
Hey team! I'm working in building a new dbt project on our snowflake datawarehouse. The idea is to improve how models are built, and the data architecture overall. One of the things I believe will take us some time is re-arranging all the existing metabase questions and migrating them from old models to the new ones. Anyone has faced this challenge before? If not, what do you thing would be the best way to do it?
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New comment Apr 3
0 likes • Apr 1
excellent! Sounds good!
What's your Data Stack?
It's one thing to read articles or watch videos about perfectly crafted data architectures and think you're way behind. But back here in reality, things get messy & nothing is ever perfect or 100% done. Most of us are usually working on architectures that are: - Old & outdated - Hacked together - Mid-migration to new tools - Non-existent Or perhaps you're one of the lucky ones that recently started from scratch and things are running smoothly. Regardless, the best way to learn what's working (and not working) is from others. I believe this could be one of the best insights this community can collectively offer each other. So let's hear it. What does your data stack look like for the following components? 1. Database/Storage 2. Ingestion 3. Transformation 4. Version Control 5. Automation Feel free to add other items as well outside of these 5, but we can focus on these to keep it organized.
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New comment 7d ago
2 likes • Mar 14
Hey team! Nice to be part of this community. Sharing my current data stack: Core: - Snowflake as DW. - Airflow for scheduling. - dbt for our transformations. Data extraction: - meltano for on-demand data extraction - aws kinesis firehose + snowpipe for a few real-time integrations. - segment for user tracking. - fivetran for intercomm. Data Viz: - Metabase
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Manuel Ponsa
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14points to level up
@manuel-ponsa-8575
Data Engineer at Decentraland :)

Active 24d ago
Joined Feb 21, 2024
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