I am knee deep in a 7 part series on decomposing Spotfire projects. In case you missed it, here are the links to the previous posts. This week, I am covering decomposing data wrangling. Next, with an understanding of data sources, we’ll look at how they come together and how much data manipulation happens.
Week 2 — Decomposing Data Functions
Now, each post in the series will be broken down into four sections.
- Quick and Dirty (Q&D)
- The Extended Version
- Room for Improvement
Quick and Dirty
- How do the tables fit together?
- Did the project developer choose to merge tables or keep data in separate tables?
- Are all transformations intact?
- For insert columns, do the joins make sense? For insert rows, are columns mapped correctly?
In the first two posts, it was easy to explain the answers with captions on screenshots. Here, the answers are a bit more complicated and require more explanation.
How: Open the Data Panel > Select a data table from the drop-down > Click on the Cog > Click on Source View.
- Are there any tables that aren’t used?
- Are all transformations necessary?
- Does the flow of data make sense?
- Are any data tables created by data functions?
- The developer found a better/different data source.
- The project began with QA and the swapped to PROD and didn’t delete QA.
- They started with a spreadsheet and switched to a SQL table.
- The user was testing out something that didn’t work. When it didn’t work, they moved on.
- Is there any way to make the table build/project load more efficient?
- Is Spotfire the best place to perform the data wrangling?
- Would it be possible to speed up the project with a different architecture?
- Where are bottlenecks?
Guest Spotfire blogger residing in Whitefish, MT. Working for SM Energy’s Advanced Analytics and Emerging Technology team!