Despite all of the current chaos, we are getting ready to upgrade our Spotfire installation. I’m a bit sad we are only going from 10.2 to 10.3, but 10.3 is the last LTS version. In performing testing in our dev environment, we ran into errors with data functions using packages. This post will explain how to resolve the error — ‘xyx package’ was built by an R engine with different internals. Read on to learn how to resolve data function errors when upgrading Spotfire.
Errors & Troubleshooting
I can’t tell you how many times my manager has asked me — “How many projects connect to the <insert name> information link? While this might seem like a difficult question to answer, the information is just a few clicks away in the Library Administrator. The key is knowing how to search for it. If you don’t know how to search for it, maybe you have relied on the terrifying-yet-effective method of clicking delete in the Information Designer and waiting for Spotfire to tell you what the info link is connected to. Rather than be afraid you are about to break something, let me show you how to use the Library Administrator to search for DXP dependencies. Read on to learn more.
It’s a fact. If you have manual data entry, there will be errors. I found this out the hard way when working with our completions team on a Spotfire KPI project. We built the Spotfire KPIs and were attempting to tie out to spreadsheets. The numbers didn’t match. Discrepancies consistently traced back to bad data entry. We would fix the bad data, but without proper controls to keep it out, we were chasing our tails. So, we addressed bad data with a QAQC or error report. The first version was all Spotfire, but it had flaws. Version 2 performed error reporting with Alteryx. Ultimately, I wound up with a combination of Alteryx and Spotfire. To see what it looks like and how it was implemented, read on.
- Have you noticed key columns for linked data in Data Table Properties and just want to know more?
- Have you tried to use replace value transformations but found options grayed out (screenshot above)?
- Have you ever lost the marked data behind tags when opening or closing a file?
- Would you like to be able to edit values in a data table?
If any of these apply, read on to find how what key columns are and how to use them.
I’ve never found a great way to explain what I do. Analogies help right? The first analogous thing that pops into my head is a Rubix cube. My day to day work feels like trying to solve a Rubix cube over and over, and the cube is a big pile of dirty, messy data. Thus, much of my day to day is troubleshooting data wrangling problems.
Some days, it’s incredibly satisfying, as solving a Rubix cube is. Other days, I want to rip the stickers off and throw it out the window. When I drafted this post, I was in “rip the stickers off” mode. I was frustrated with how long it took to solve data wrangling problems. When I get in that mindset, I want to share what I learn so other people don’t suffer as much. Thus, this post discusses my top 5 ways to approach troubleshooting data problems. These methods will apply no matter what application you are working in or if the problem is related to data wrangling or logic problems. Read on for details.
I don’t work in a support role anymore, but…Occasionally, someone will reach out to me with a question that’s quick and easy to solve, so I help. This week, a user contacted me because he was missing options in lines and curves.