Writing data documentation belongs to the famous “important but not urgent” tasks.
There's always something more urgent to do … Or more exciting! You might also not know where to start or how to proceed.
This article launches a series on data documentation, with the goal of addressing 4 key questions about the subject:
🎯 Why?: Why is it vital to pay attention to data documentation? It prevents repeated questions from data consumers, allowing data producers to allocate their time towards more valuable pursuits.
📖 What?: What are the different forms of data documentation? Although data dictionary or business glossary may come to mind first, there are additional capabilities that are just as important.
✍🏼 How: How can you approach data documentation effectively? Documentation is not magic, just common sense. In this part, we will set up a framework for curating documentation.
🔍 Where: Where should data documentation live? Organization is one of the most critical aspects of documentation. True success in documentation is achieved when readers are able to independently access the information they need and are satisfied with what they find.
We’ll explore the significance of the first question, "Why?", in this first article, as well a few rules for effective documentation. Want to know more? Subscribe to receive the rest of the series directly to your inbox.
Let's dive in!
Technical documentation is an essential component of workplace productivity and collaboration. It serves several key purposes, including:
Properly executed data documentation can open many doors. However, to achieve this outcome, you must follow certain guidelines. To turn your data team into a powerhouse, make sure you utilize only reliable and up-to-date data, document in a manner that promotes dashboard reuse, and combat metric inconsistencies.
When starting on your data documentation project, avoid using data that is out of date, data that is known to be duplicated, work tables, and sandboxes. These types of data can be unreliable and mislead data users. Only document data that is reliable and up-to-date, to ensure everyone in your company is working with the right information.
Instead of creating a brand new dashboard from scratch, you can potentially take an existing one and modify it to suit your needs. Dashboard reuse can be a great way to save time, energy, and resources, as it leads to less maintenance work and a reduction in storage and processing costs.
For this reason, your documentation should promote dashboard reuse. Data documentation can support dashboard reuse by providing clear and comprehensive information about existing dashboards, including their purpose, data sources, calculations, and visualizations.
This information can be used to evaluate whether an existing dashboard can be adapted to meet new requirements, or if a new dashboard needs to be created from scratch. By having this information readily available, decision-makers can make informed choices about dashboard reuse and avoid duplicating effort.
It’s common to get different figures for the same metric from one table to another. Without a unified source of truth for metrics, different departments may adopt their own method of calculation, leading to conflicting metric interpretations across the various departments within the same company.
To avoid this, naming conventions and folder organization rules should be strictly followed. This is essential in order to maintain consistent data across the board and ensure that any discrepancies can be easily identified and fixed. It is also important to keep track of a timeline of all changes so any sudden shifts in figures can be quickly and accurately traced back to their source and addressed. These measures will help to promote accuracy and avoid any confusion or errors in the future.
Data documentation is vital to ensure data users can extract value from the data. It brings clarity to information, eliminates repetitive questions, keeps information organized, makes transitions smooth, and reduces the burden of knowledge.
This article emphasized why data documentation is important, and the crucial elements of effective data documentation including the prevention of inaccurate data, promotion of dashboard reuse, and avoidance of inconsistencies.
By keeping these principles in mind, data documentation can be a powerhouse practice that elevates productivity, streamlines processes, and fosters teamwork in the workplace.
We write about all the processes involved when leveraging data assets: from the modern data stack to data teams composition, to data governance. Our blog covers the technical and the less technical aspects of creating tangible value from data.
At Castor, we are building a data documentation tool for the Notion, Figma, Slack generation.
Or data-wise for the Fivetran, Looker, Snowflake, DBT aficionados. We designed our catalog software to be easy to use, delightful and friendly.
Want to check it out? Reach out to us and we will show you a demo.