April 2019

Governing Self-Service BI

A few weeks ago, I wrote the first of three posts on my key takeaways from the Gartner Analytics conference. The first message focused on Organizing the Chaos. It’s taken me a bit longer than anticipated to write post no 2 on governing self-service BI. However, hopefully it was worth the wait because I will tie back to a post I wrote on Spotfire Skills – Historically Speaking. In this week’s post, I will explain more about the skills users will need to have in the immediate future. Read on to find out what you can do to put a guard rail around self-service analytics.

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Pro Tip No 4 How to Change Multiple Column Names At Once

In Spotfire, there are two ways to change column names. You can modify the column names in Column Properties, or you can change them with Transformations. There are ramifications for which method you use, which I explained in this Data Shop Talk post. Now, speaking to Transformations….For years, I’ve been under the impression that you could only ever change one column name at a time. However, I recently found out that is not the case. It is possible to formulaically change multiple column names in one fell swoop (or expression…as it were). Let me show you how!

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Part 7 – Data Limiting with Rules

Welcome to part 7 of my Spotfire Data Limiting Series. The first post in the covered data limiting with the filter and data panels. The second post talked about data limiting in the web player. The third post discussed limiting using filtering schemes. Then, I covered limiting with marking, limiting with expressions, and limiting with subsets. This is the final post in the series discussing data limiting with rules.

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5 Ways to Increase Speed of Delivery

One of the most common problems I run into in while building Spotfire projects is requests that are too large. They begin simply with a request for data or a modification to an existing project. However, it quickly balloons into more and more until we’ve created a monstrously huge project. One of these monsters jumped on my desk last August, and I’ve been working on it since then with a few stops and starts. Last night, I wrapped up a week of work in Midland. I was about to shut down my machine when I realized I wanted to write up what I’ve learned about how to increase the speed of delivery in these monster project situations.

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Part 6 – Data Limiting with Subsets

Welcome to part 6 of my Spotfire Data Limiting Series. The first post in the covered data limiting with the filter and data panels. The second post talked about data limiting in the web player. The third post discussed limiting using filtering schemes. Then, I covered limiting with marking. Last week touched on limiting with expressions. This week, we talk about data limiting with subsets.

Very few users know about limiting with subsets. When I took TIBCO’s Spotfire Essentials course, subsets were covered. I subsequently eliminated them from my own Essentials training as there was just too much to learn. I don’t use them very often, so this post was a great opportunity for me to revisit and rethink when they are most useful.

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Why use Python?

I always enjoy writing Python code. It’s fun, expressive, and my go to language when starting a new project. Python has exploded the past few years becoming the language of choice in many areas. No area has been affected more than data science and analytics.

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Part 5 – Data Limiting With Expressions

Welcome to part 5 of my Spotfire Data Limiting Series. The first post in the series covered data limiting with the filter and data panels. The second post talked about data limiting in the web player. The third post discussed limiting using filtering schemes. Last week, I covered limiting with marking. Now, we are on to limiting with expressions. As a new Spotfire user, I was enamored with filtering schemes, but as my skills developed, limiting with marking became my go-to method.

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