ETL was actually a new acronym for me: Extract, Transform, Load. https://en.m.wikipedia.org/wiki/Extract,_transform,_load
Please be aware there is also a newer concept, which is ELT. Extract Load Transform. This is the data lake principle: you firstly dump all data verbatim into one coherent data storage. (data ingestion phase) The transform will eventually be done by the data scientists (data curation phase). The data curation is really difficult as it requires in-depth knowledge of the data, removing of slack, creation and lookup of r…
Using an ETL framework vs. writing yet another ETL script
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Re: Using an ETL framework vs. writing yet another ETL script
#62Re: Using an ETL framework vs. writing yet another ETL script
#63We currently are using Airflow for ELTs/ETLs to ingest from different Postgres databases to BigQuery/Google Cloud Storage. Airbyte looks sweet for the same task and would free us from a big effort burden, but its Postgres source only supports SELECT * statements (i.e. you can't deselect columns). That's kind of a dealbreaker for us, because for security reasons our Postgres users permissions are granularly configured…
Re: Using an ETL framework vs. writing yet another ETL script
#64There's a despair that overcame me when the data we were processing changed date/time format in the middle of a file. It was a file for one day's data! Data on 5 minute intervals for 3 thousand data sources. Received in an email, no less. (Long story). But date/time format changed. The initial load was garbage. As many know, some countries use mm/dd/yy and others dd/mm/yy. I just wanted to cry when I dug in and saw t…
This means investing timebin learning a workflow orchestrator, but your new hires will be glad they did.
Re: Using an ETL framework vs. writing yet another ETL script
#65I gave up on all these frameworks and just use Cron and Make and Python
Re: Using an ETL framework vs. writing yet another ETL script
#66Earlier quoted context omitted.
Please be aware there is also a newer concept, which is ELT. Extract Load Transform. This is the data lake principle: you firstly dump all data verbatim into one coherent data storage. (data ingestion phase) The transform will eventually be done by the data scientists (data curation phase). The data curation is really difficult as it requires in-depth knowledge of the data, removing of slack, creation and lookup of r…
1. Great explanation of ELT, for a long time ETL monkey this broke through for me. 2. GDPR/COPPA means you really have to think about your data lake before dumping verbatim into long term storage.
Re: Using an ETL framework vs. writing yet another ETL script
#67Airbyte Engineer here. I think some of the points made here about ETL scripts being just 'ETL scripts' are very relevant. Definitely been on the other side of the table arguing for a quick 3-hour script. Having written plenty of ETL scripts - in Java with Hadoop/Spark, Python with Airflow and pure Bash - that later morphed into tech debt monsters, I think many people underestimate how quickly these can quickly snowba…
Re: Using an ETL framework vs. writing yet another ETL script
#68Re: Using an ETL framework vs. writing yet another ETL script
#69I am tasked with standardizing ETL in a small org, airbyte is on my list to evaluate. As I write this there are 64 comments in the thread and only a single comment mentions actual experience using airbyte. Any other actual insights using the tool? What about Airflow downsides mentioned in the article? Thx!
Re: Using an ETL framework vs. writing yet another ETL script
#70I am tasked with standardizing ETL in a small org, airbyte is on my list to evaluate. As I write this there are 64 comments in the thread and only a single comment mentions actual experience using airbyte. Any other actual insights using the tool? What about Airflow downsides mentioned in the article? Thx!
YT has usually good tutorials and concept explanations. Maybe a good point to start.