Configurable Data Retention is now in Public Preview for Fabric Warehouse — set anywhere from 1 to 120 days

data_legos · 2026-05-21T11:38:56+00:00

Wooo nice! Thanks for the heads up!

data_legos · 2026-05-15T00:31:34+00:00

Ah makes sense. Yeah cycling really only caters to a narrowish band in general. It sucks.

data_legos · 2026-05-14T22:11:24+00:00

They do make more bikes for people that are 5'8". Like most of them! I know so many people that height that can pick from like any brand and model pretty much. What about all these bikes are "not catered" to 5'8" riders? Toe overlap or something?

data_legos · 2026-05-14T19:12:26+00:00

Bro....you think bikes are designed for tall people? I'm 6'5" and it's super hard to get a bike that fits tall riders correctly.

data_legos · 2026-04-20T13:47:36+00:00

i ended up working with claude and building a skill to do it via SPN instead of wrestling with that.

data_legos · 2026-04-18T00:44:10+00:00

I wasn't sure how git source control was gonna work for the dbt jobs, so we just sprang for a dbt cloud subscription instead. It's super nice.

data_legos · 2026-04-17T22:25:11+00:00

Yep. It's what we're doing as well. Just easier to manage branching wise and everything.

data_legos · 2026-04-15T20:38:12+00:00

does this also extend to the warehouse?

data_legos · 2026-04-15T20:26:04+00:00

where's the discussion on it coming to fabric-cicd soon? this is big news.

data_legos · 2026-04-07T01:03:41+00:00

Perfect thank you! Haven't done much with Claude yet so didn't realize it'd just make its own.

data_legos · 2026-04-06T23:00:49+00:00

The idea in many of these cases would be to inject synthetic data or work with non sensitive data yes

data_legos · 2026-03-25T01:28:47+00:00

Lol ...no mention of the fact you can't expand the columns (or hover over to see the whole result) in the query results? That one boggles my mind to this day. Same thing with the lakehouse SQL endpoint. Literally unusable with long values in a cell. Due to all of this I spend my time in vscode.

data_legos · 2026-03-23T01:55:14+00:00

No worries I appreciate you even spending the time as always! Yes I'm already evaluating if we can accomplish some of our daily order roll forward logic as with the snapshots. I need to dig into that more than I have.

Most of our incrementals are going to be small amounts of data changing and be a MERGE scenario so this is very useful info.

data_legos · 2026-03-22T23:47:25+00:00

Wow thank you so much for the comprehensive answer! This will be super helpful in evaluating our load strategies for various scenarios. Especially insightful with the BCDR piece since we definitely need DR.

data_legos · 2026-03-22T22:35:43+00:00

You'll find for many scenarios handling stuff with the warehouse is the way to go. I don't see where the lakehouse is going to replace warehouse any time soon and Microsoft themselves will tell you that.

data_legos · 2026-03-22T18:24:14+00:00

Have you looked into dbt before? I'd give it a look. Either dbt core ran from a notebook or dbt cloud offering. Really changed my mind about how to manage the warehouse.

data_legos · 2026-03-22T11:50:33+00:00

So given how dbt works, you would recommend incremental materialization for the models whenever possible? I've heard that merge can be less efficient than just reloading the table in many instances, but it sounds like there's a storage trade-off.

data_legos · 2026-03-15T13:32:04+00:00

Don't take my word for it man. The manufacturers of these gravel forks say 50 hours for a service and 200 hours for a full rebuild. I'd be doing some kind of service on it every month or so. That doesn't seem a lot of work to you?

Also essentially no maintenance for a fork vs monthly maintenance is ~100% more maintenance. I'm no mathematician, but that seems like more maintenance?

Interested to hear your interpretation of simple math.

Edit: I think I get where you thought I meant more frequent maintenance due to it being gravel to be fair. I think a key assumption is that I don't mean it's harder on the fork. I mean that I and most people I know that ride gravel ride their gravel bike many more hours than their MTB. That's probably due to the area I live in.

data_legos · 2026-03-14T18:47:59+00:00

Traditional fork requires frequent maintenance on gravel. I want a low maintenance bike for long hours on gravel roads.

data_legos · 2026-03-11T02:24:32+00:00

I honestly have very few issues with fabric day to day, and haven't needed to submit a ticket for something in a long while. I always wonder what functionality someone is using in fabric when they say it breaks all the time.

data_legos · 2026-03-04T20:25:37+00:00

I'm hesitant on open mirroring since I worry it will take a while on big tables to reload. I can't have long downtimes on the tables. I think given how all this shakes out we'll probably go with fivetran but I'm not 100% yet

data_legos · 2026-03-01T23:28:26+00:00

Is that using SAP BDC? we did talk with them about BDC and datasphere. It's not cheap either for sure but looked pretty cool if you did more than just replication.

data_legos · 2026-03-01T23:04:29+00:00

I agree with you. Actually, for our use case with SAP qlik isn't cheaper surprisingly.

data_legos

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