feat: 🚀 Added link to Makefile use-case and new resources across multiple documents

+1 -1

Automation.md

··· 11 11 - Drive standards through automation and building internal tools/scripts rather than through extensive [[documentation]]. 12 12 - Standards can help to reduce this friction but take time. Before jumping into standards processes, [consider other ways to encourage consistency](https://blog.ldodds.com/2023/09/18/consistency-before-standards/). 13 13 - If you jump into standards, [make them open, modular, interoperable, customizable and, extensible](https://voltrondata.com/codex/standards-over-silos#1-3-5-composable-systems-are-MICE). 14 - - Makefiles are a great way to document and consolidate different projects of a team. Each project should have a `make` that runs it, and perhaps a `make deploy` to deploy it. Language and tool independent! 14 + - Makefiles are a great way to document and consolidate different projects of a team. Each project should have a [`make` that runs it](https://gagor.pro/2024/02/how-i-stopped-worrying-and-loved-makefiles/), and perhaps a `make deploy` to deploy it. Language and tool independent!

+1

Data/Analytics Engineering.md

··· 46 46 - [MIT Open Learning](https://github.com/mitodl/ol-data-platform) 47 47 - [Our World in Data](https://github.com/owid/etl) 48 48 - [Catalyst Cooperative PUDL](https://github.com/catalyst-cooperative/pudl) 49 + - [Ecosyste.ms](https://github.com/ecosyste-ms) 49 50 - [Spellbook](https://github.com/duneanalytics/spellbook/) 50 51 - [Flipside Crypto](https://github.com/FlipsideCrypto/external-models) 51 52 - [MetricsDAO](https://github.com/MetricsDAO)

+1

Data/Data Culture.md

··· 25 25 - If data is the most precious asset in a company, does it make sense to have only one team responsible for it? 26 26 - [People talk about data as the new oil but for most companies it's a lot closer uranium](https://news.ycombinator.com/item?id=27781286). Hard to find people who can to handle or process it correctly, nontrivial security/liabilities if PII is involved, expensive to store and a generally underwhelming return on effort relative to the anticipated utility. 27 27 - The purpose of becoming data driven is to build a causal model of the business in your head. The purpose of doing all this work is that you want to understand how your business actually works and grows, not rely on superstitious beliefs about how your business works and grows. 28 + - You become data driven by looking at the data and not that much by hiring/expanding the data team. You can't outsource it. 28 29 - [The pain in data teams come from needing to influence PMs/peers with having little control of them. Data teams need to become really great internal marketers/persuaders](https://anchor.fm/census/episodes/The-evolution-of-the-data-industry--data-jobs-w-Avo-CEO-and-Co-founder-Stefania-Olafsdottir-e16hu1l). That said, it shouldn't be the data team job to convince the organization to be data driven. That's not an effective way of spending resources. 29 30 - Executives are expected to be data driven, even if they don't know what it means. 30 31 - Epistemology of the leadership team really really matters.

+1

Data/Metrics.md

··· 53 53 - Output metrics represent results and input metrics represent actions. 54 54 - When output metrics are given as goals, teams can often focus on the wrong inputs or thrash between inputs. 55 55 - Focus on usage first (not revenue first). This is the most common version of outputs vs inputs. Usage creates revenue, revenue does not create usage. As a result, the most important metrics in terms of creating growth are not your revenue metrics, they are your usage metrics. 56 + - On a similar note, there are leading and lagging indicators. Leading indicators are usually input metrics and are harder to measure. Lagging indicators are usually output metrics and easy to measure. 56 57 - Mixing Up Retention and Engagement. Retention and engagement are not the same things. Retention is binary. It answers the question, was this person active within my defined time period? Yes or no. Engagement is is depth. It answers the question, how active were they within the defined timed period? 0→N. Engagement is one of three major inputs into driving retention. 57 58 - Customers vs Users. A customer and a user is not the same thing in most business models. A customer is defined as the person/group that is paying you. A user is a person using the product. 58 59 - In subscription products, oftentimes there are multiple users associated with a single customer. Or people are users before they are a customer. You need to separate the definition and language between these two things for teams to clearly act on them.

+3

Teamwork.md

··· 7 7 - Define boundaries and limitations of each component. 8 8 - Work in the open and [[Documentation|document]] everything. Transparency increases understanding and reduces synchronization challenges. **[Emulate Open Source projects](https://tomayko.com/blog/2012/adopt-an-open-source-process-constraints) and [[Remote Jobs|remote companies]]**. 9 9 - [Write weekly updates](https://doingweeknotes.com/) and share them in a common place. 10 + - What is shipping (e.g. what is on the near horizon). 11 + - Why is it important / what is now possible as a result / why should people care? 12 + - How are things progressing. Any blockers? 10 13 - To make everyone more productive and happy: **Make feedback loops fast**. [Some best practices](https://simonwillison.net/2022/Oct/1/software-engineering-practices/): 11 14 - Tested, automated process for new development environments. 12 15 - Automated preview environments.

+6

Web Based Tools.md

··· 12 12 - [Birme](https://www.birme.net/) 13 13 - [Law Of UX](https://lawsofux.com/) and [Visual Design Safe Rules](https://anthonyhobday.com/sideprojects/saferules/) 14 14 15 + ### SVGs 16 + 17 + - [SVGViewer](https://www.svgviewer.dev/) 18 + - [SVG Crop](https://svgcrop.com/) 19 + - [SVGOMG](https://jakearchibald.github.io/svgomg/) 20 + 15 21 ## Teamwork 16 22 17 23 - [HackMD](https://hackmd.io/)

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