## Metadata - Author: [[matt-arderne|Matt Arderne]] - Full Title:: The Way of Ways - Category:: #🗞️Articles - Document Tags:: [[Data culture|Data culture]], [[Data culture|Data culture]], - URL:: https://groupby1.substack.com/p/the-way-of-ways - Finished date:: [[2023-08-22]] ## Highlights >  ([View Highlight](https://read.readwise.io/read/01h8bkrp3xffyfh1jp61q1xs66)) > ELT, synonymous with MDS, came under cost pressure. People realised that the work was pretty predictable and so cheaper, better, faster options became abundant. ([View Highlight](https://read.readwise.io/read/01h8bkxdvh7yx3j6gtv0ddn6k3)) > dbt [democratised that](https://roundup.getdbt.com/p/complexity-the-new-analytics-frontier): > > Did we achieve more collaboration on an analytics code base? ✅ > > > > Did we achieve more leverage through reusable and modular code? ✅ > > > > Did we also buy more complexity, resulting in longer maintenance and debugging cycles? Unfortunately, also ✅ 🤓 > > > > Turns out the price of enabling people to build a more complex code base is… **a more complex codebase**, and everything that comes with that. ([View Highlight](https://read.readwise.io/read/01h8bkyfvx8e763f8rnma4edjn)) > the following “MDS categories”. ([View Highlight](https://read.readwise.io/read/01h8bm015wjm95tafy19h0p0t5)) >  ([View Highlight](https://read.readwise.io/read/01h8bm058am8k0h4be9kq7sy1h)) >  ([View Highlight](https://read.readwise.io/read/01h8bm078zx2z1r5p7t9tc2xwn)) > Business Intelligence tools continued to underwhelm, primarily because of the split between traditional reporting and exploratory analytics. ([View Highlight](https://read.readwise.io/read/01h8bm2pvjf5hcx6c08jw621f7)) > Traditional BI just don’t move the needle in the same way that newer tools like Hex do. (Hex described this paradigm in [deleted article](https://web.archive.org/web/20211113014204/https://hex.tech/blog/bi-tools-hex/), they now position themselves as a data tool that does [reporting too](https://hex.tech/blog/data-driven-decisions-with-kpi-dashboards/#:~:text=They%20can%20be%20simple%20or%20complex%20depending%20on%20need%2C%20and%20as%20beautiful%20or%20sparse%20as%20you%20can%20make%20it.%20But%20the%20data%20always%20takes%20center%20stage.%20Your%20focus%20when%20building%20one%20should%20always%20be%20%E2%80%9Cdoes%20this%20help%20drive%20the%20organization%20forward%3F%E2%80%9D)). I use Hex daily. It is relatively cheap, it works very well and has sufficient depth to replace a [fair chunk of MDS and technology infrastructure](https://twitter.com/mattarderne/status/1656361016983265280) too. ([View Highlight](https://read.readwise.io/read/01h8bm3eyg8p0ktynqakv6pn1z)) > The **data systems are largely** ***good enough*** and so the bottleneck becomes what to do with the data. Data engineering ***was*** the bottleneck. In January 2022 I gave the opinion that Data Engineering was [no longer the primary bottleneck](https://groupby1.substack.com/p/data-engineering) to delivering insights/value/whatever. ([View Highlight](https://read.readwise.io/read/01h8bmcjb9hj3yjagvqv5ky1gf)) This is weird because I would say this is still Data Engineering > The challenges are now more subtle: > 8 > Track 1: “[All I want is to know what's different](https://benn.substack.com/p/all-i-want-is-to-know-whats-different)” > Track 2: “[The emotionally informed company](https://benn.substack.com/p/the-emotionally-informed-company)” > Track 3: “[The truth is out there The only thing stopping us from finding it is us](https://benn.substack.com/p/the-truth-is-out-there)” > Track 4: “[Will we ever have clean data? Probably not, but maybe we can work with messy data](https://benn.substack.com/p/will-we-ever-have-clean-data)” ([View Highlight](https://read.readwise.io/read/01h8bmcwdwyczrn0hjww7ezzk7))