"New to data stuff—what is elt and how’s it different from etl?"
Hey everyone! So I’ve been diving into data integration lately, and keep hearing about *what is elt*. From what I gather, it’s like ETL but flipped?
ETL extracts, transforms, then loads data. But elt extracts, loads *first*, then transforms it later in the target system (like a data warehouse).
Why’s this a big deal? Seems like elt is faster for huge datasets since you’re not transforming before loading. But also… when would you *not* use it?
Kinda confused about the pros/cons vs ETL. Anyone got real-world examples or just dumb it down for me?
Thanks! 🙌
(Also, sorry if this has been asked a million times—I did search but some answers got way too technical.)
Great question! So, what is elt? It’s basically ETL but with the T and L swapped. Instead of transforming data *before* loading, you dump it raw into your warehouse and transform it there.
Biggest perk? Speed. No waiting for transformations to finish before loading. Tools like Snowflake or BigQuery handle the heavy lifting.
Downside? If your target system sucks at transforming, you’re stuck. Also, messy raw data can be a headache later.
For tools, check out Fivetran or Stitch for ELT, and Talend for ETL.
Yo, ELT is a game-changer for big data. ETL’s like cooking before serving—ELT’s like serving first, then cooking.
Why? Cloud warehouses (Redshift, BigQuery) are beasts at transforming data *after* it’s loaded. Saves time and $$$.
But… if you’ve got strict compliance (like GDPR), ETL might be safer since you clean data *before* it lands.
Try dbt for transformations in ELT—it’s magic.
what is elt? Think of it as the lazy (but smart) way to handle data. Load first, ask questions later.
ETL’s old-school for smaller, structured data. ELT shines when you’ve got TBs of messy stuff.
Tools? Airbyte for extraction, Snowflake for storage, dbt for transforms.
Cons? You gotta trust your warehouse. If it’s slow, ELT becomes a pain.
ELT vs ETL is like… do you wanna clean your groceries before putting them in the fridge (ETL) or just shove ‘em in and deal with it later (ELT)?
ELT’s faster for sure, but if your data’s garbage going in, it’s garbage staying in.
For tools, Matillion’s great for ELT, especially with Snowflake.
When *not* to use ELT? When you need super clean data upfront (like for reporting).
what is elt? It’s the “load now, worry later” approach. Perfect for cloud setups.
ETL’s more predictable but slower. ELT’s flexible but can get messy.
Try Snowflake + dbt for ELT. Old-school ETL? SSIS still works.
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Wow, thanks everyone! This makes way more sense now. Didn’t realize how much the choice depends on your warehouse’s power.
Gonna try Fivetran + dbt with BigQuery like some of you suggested.
Quick follow-up: Anyone got horror stories with ELT? Like, when did it totally backfire? Just wanna avoid landmines lol.
what is elt? It’s ETL’s cooler younger sibling. Load raw data, then transform it *inside* the warehouse.
Pros: Scales like crazy. Cons: You need a solid warehouse (BigQuery, Redshift).
ETL’s better if you’re stuck with on-prem systems.
Tool recs: Fivetran for ELT, Informatica for ETL.
ELT is like stuffing your closet first and organizing later. Works great if you’ve got space (aka a powerful warehouse).
ETL’s like folding clothes before putting them away—slower but neater.
Use ELT for speed, ETL for control.
Tools: Stitch for ELT, Talend for ETL.
