AgileData Newsletter #7
Agile Anti Patterns
When we think about patterns we also think about anti-patterns.
An anti-pattern can describe a set of context where a pattern is unlikely to work well.
An anti-pattern can also describe things we see people doing often that don't seem to work, and then we can focus on what pattern might solve that problem.
Have a listen or read to this podcast where Shane Gibson And Murray Robinson talk to Todd Lankford who has a great set of agile anti-patterns to watch out for.
Listen to the No Nonsense Podcast or read the transcript @agiledata.io
AgileData Lineage - Mapping your Way to Magic
Simply put, data lineage shows how your data has traveled from start to finish.
It's a core user feature of any data platform, but one that often gets missed.
Read a quick blog post on what data lineage is:
https://agiledata.io/blog/data-and-analytics/what-is-data-lineage/
Or have a listen, or read the transcript, from the AgileData podcast where Nigel and Shane discuss Data Lineage in more detail.
Listen to the AgileData podcast or read the transcript @ AgileData.io
Data Map
When we change data to make it useful to consume, we end up with lots of steps and code to make these changes.
So when somebody who is consuming the information asks "where did that data come from?" we need to trace those steps or that code.
Luckily we have a feature we call Data Map, which uses a data lineage pattern to show the journey data is going on.
We think it as the London Underground Tube Map for data.
Watch @ YouTube
Catalog & Cocktails Podcast - Agile in the Data Domain
Earlier in 2022 Shane Gibson was lucky enough to chat to the awesome hosts of Catalog & Cocktails about agile in the data domain.
And it was recorded live!
Watch or listen to the recording at your pleasure.
Read more @ AgileData.io
The Concept of an Information Product
An Information Product is an approach to describe a subset of data, analytical and visualisation requirements, in a way that the business stakeholders can agree what they will get and the team can understand and deliver it in small iterations.