veritas3241

7 ms·

1. 31.▲
   by veritas3241 7y ago

   Oh that's good! Didn't realize it. Doesn't quite solve the spam problem, but seems like a step in the right direction.
2. 32.▲
   by veritas3241 7y ago

   I don't understand why they won't put the money in escrow instead of just shunting it to the claimant. Presumably because it would require people to make a determination. Seems irresponsible.
3. 33.▲
   by veritas3241 7y ago

   I have 12 small whiteboards (14x14 in) mounted on my wall that I add stickers to now. The only stickers on my laptop are ones I have duplicates of. It's a nice collection and it's scaled more than the back of my laptop has.
4. 34.▲
   by veritas3241 7y ago

   Seconded! We're implementing it at GitLab and while the documentation could use some work, it's been pretty great. Coupled with some off the shelf modeling packages[0] you can get good analytics pretty quick. We even started on Cl
5. 35.▲
   by veritas3241 7y ago

   I feel this too. It's perverse and it makes it feel like nothing is worthwhile unless it scales and earns a profit. I get that it's all in my head, but it's a real undercurrent in the west, particularly in tech. I'm not
6. 36.▲
   by veritas3241 8y ago

   I played with Arango a few years ago to prototype some graph stuff. Super fun to play with and it was awesome being able to traverse the graph so easily. We were playing with data to make it easy to go from a specific analyte that was gener
7. 37.▲
   by veritas3241 8y ago

   I didn't add indexes mainly b/c for analytic warehouses that are columnar, indexes are less important / meaningless. Partitions though, that's important!
8. 38.▲
   by veritas3241 8y ago

   You've intrigued me with this comment mainly because I know SQL quite well but IP not at all. Is wikipedia[0] for IP a good reference to dive in a bit? Would you recommend something else to grok why IP is so fundamental? [0] https:&#x
9. 39.▲
   by veritas3241 8y ago

   Agreed that SQL is amazing at processing data! I would argue that a lot of people are trying to both process their data _and_ ask a question of it in the same statement. Separating those out is really important to make analytics more scalab
10. 40.▲
    by veritas3241 8y ago

    Are you asking for examples of advanced SQL skills? In my experience, if you can grok lateral joins (aka cross apply), recursive CTEs, window functions, and fully understand all the join types, that's a gold star for understanding SQL!
11. 41.▲
    by veritas3241 8y ago

    You might be interested in this project then https://www.getdbt.com/ it's a SQL compiler and executor which has many features like you're talking about (macros to generate SQL and so on). It makes it pretty easy t
12. 42.▲
    by veritas3241 8y ago

    I fell in love again with SQL while working in my current position. What _really_ made me fall in love was the project dbt[0] which is a SQL compiler and executor. You can build a DAG of transformations all the way from your raw data to tab
13. 43.▲
    by veritas3241 8y ago

    And also you sometimes don't have capacity to do all the analyses you want at the start. Throw all the computational power you want at it, but if you don't have enough humans down stream to make decisions from it, then storing tha
14. 44.▲
    by veritas3241 8y ago

    We used them for a single data source at GitLab (Zendesk). Worked pretty well! But we quickly hit a road block where what you could get via the UI wasn't all the tables available. We wound up forking it and adding to the tap. Basically
15. 45.▲
    by veritas3241 8y ago

    It wasn't for optics reasons; that was entirely coincidental. It was announced well before the GitHub acquisition that we were moving to GCP, primarily for better Kubernetes integration [0]. [0] https://about.gitlab.com&#x2F
16. 46.▲
    by veritas3241 8y ago

    We're a big fan of dbt and the new docs feature at GitLab. We're working on implementing them on our end and they should all be publicly available as soon as we get it stood up (see https://gitlab.com/meltano/
17. 47.▲
    by veritas3241 8y ago

    Having just done a close to 20 hour flight (sort of - 6 hours CPT to ADD, just enough time to go to another plane, 14 hours ADD to IAD via a technical stop in Dublin), I've got to say just how absolutely miserable it is to fly for a lo
18. 48.▲
    by veritas3241 8y ago

    Thanks for the shout-out on Meltano! And we love dbt! Great project and great people behind the code. Their next release is going to be awesome - the new docs feature is beautiful.
19. 49.▲
    by veritas3241 8y ago

    I cannot recommend this book enough! I thoroughly enjoyed it and really appreciated the clear definitions and strong opinions.
20. 50.▲
    by veritas3241 8y ago

    Another commenter mentioned it as well, but "Designing Data-Intensive Applications" by Martin Kleppmann https://dataintensive.net/ is a _fantastic_ overview of the field and, I think, more approachable and enjoyab
21. 51.▲
    by veritas3241 8y ago

    Not sure if you're talking about the Chemical Engineer part, but I've met a lot of people trained as ChemE's that have nothing to do with that profession. But maybe that's true of a lot of professions and I'm just b
22. 52.▲
    by veritas3241 8y ago

    This is the _exact_ reason I went to grad school. I didn't believe I was a "good enough" chemical engineer so I went to grad school. About 2-3 years I was miserable but stuck with it to get the letters after my name. Thankful
23. 53.▲
    by veritas3241 8y ago

    There's a persistent bug with my Pi-Hole where every time it's active it causes my wife complains that several of the websites she wants to visit are unusable. :-D
24. 54.▲
    by veritas3241 8y ago

    Thanks for the positive comment! We're generally taking the same approach that was taken with GitLab the product: do it out in the open, iterate constantly, and work with the community. Especially doing it out in the open enables these
25. 55.▲
    by veritas3241 8y ago

    You're talking about more debugging tools within the transformation steps of a pipeline, right? dbt is helping with that via data tests (see https://gitlab.com/meltano/analytics/tree/master/elt/
26. 56.▲
    by veritas3241 8y ago

    The scope of Meltano isn't limited to just data pipelines, though that is the first major part of it. One thing that gets me really excited about it is the way we want to build version control in from the start. To give you an example
27. 57.▲
    by veritas3241 8y ago

    This could potentially become part of the Meltano stack. At GitLab, we're not at the phase yet where we're in need of data versioning. But I could imagine a data registry that's integrated with the workflow of data analysts&#
28. 58.▲
    by veritas3241 8y ago

    Personally, I quite like the approach FloydHub has for deep learning projects. At GitLab, we currently don't have any deep learning projects happening - we're still further down the AI hierarchy of needs - i.e. focusing on solid d
29. 59.▲
    by veritas3241 8y ago

    This look very interesting! I haven't heard of it before, but you've definitely piqued my interest. Thank you for the links.
30. 60.▲
    by veritas3241 8y ago

    Thanks so much!