Have you ever looked at a part of your code or dataset and wondered what you are looking at? I have for sure! Analytics engineering plays a key element in the data-driven decision-making process today. Besides the complexity of the analytics workflow, the crucial role of documentation significantly impacts the efficiency, transparency, and sustainability of analytics engineering processes.
What is data documentation?
Very simply put, data documentation is the process of creating and maintaining detailed information about datasets. Documentation helps users to understand, interpret, and effectively use data. Some key components for data documentation are:
- Variable names
- Data types
- Variable descriptions
- Data structure (primary keys, foreign keys)
- Relationship between tables
Why is documentation important?
External knowledge transfer
As an analytics engineer consultant you collaborate with diverse clients. To do so, it is best practice to write a comprehensive documentation that can serve as a knowledge transfer mechanism. Why? Good documentation facilitates communication and ensures that clients comprehend the intricacies of the analytical processes. This transparency fosters trust and supports clients to actively participate in decision-making processes. Besides, documentation ensures that the value you bring to a project endures beyond the immediate project scope.
Internal Knowledge transfer
Knowledge transfer is also important internally within a company. For example, if new knowledge is instantly documented and shared amongst company members, the business can use this to strengthen it’s position on the market. Moreover, when internal projects are properly documented it becomes easier for other company members to jump on a project without having to run around the office first to gather all the information they need. Not to mention, that most of the time you do not get the information that you are looking for anyways. Documentation of internal projects therefore leads to a more efficient workflow, which results in a higher productivity rate.
Team member integration and departure
A well written documentation helps to facilitate the integration process of new team members because it minimizes the time required for the new team members to understand the existing dataset. To the contrary, a comprehensive documentation prevents the business from relying on specific individuals. For example: if a key member departures or is temporarily unavailable, a comprehensive documentation prevents the loss of critical information. Moreover, the remaining team members would have to make assumptions about the dataset if critical information is lost, which could challenge the continuation of the project.
Documentation is a must!
Data documentation serves key purposes such as enhancing collaboration with clients, fostering transparency in analytical processes and ensures enduring project value. Moreover, it strengthens a companies position by promptly sharing new knowledge, streamlining project transitions, which contribute to a more efficient workflow. Finally, it facilitates the integration of new team members and prevents reliance on specific individuals which ensures project continuity.
