1st Alteryx User Group Meeting

Last Thursday evening the first Milwaukee Alteryx User Group (MAUG) meeting was held at the Baird offices. Starting with pizza and soda at 4:45pm provided by AE Business Solutions the meeting transitioned to a welcome and introductions. The group is being lead by Robert Farley of Health Payment Systems, John Heisler of Health Payment Systems, Matt Christen of Baird, Mark Hohensee of Baird, Alex Christensen of AE Business Solutions, Tessa Jahnke of AE Business Solutions, and Sam Lachterman of AE Business Solutions. Outside of those individuals there was representation from Northwestern Mutual and Johnson Controls who aren’t currently using Alteryx, IMS Health who is using the tool for its geocoding capabilities, and Artisan Partners among others.

John Heisler began the presentations with an overview of HPS’s implementation and use of Alteryx which was over my head as they are using it as a replacement to a data warehouse. It is certainly an interesting use case and I’m sure pushes the boundaries of the purpose of the tool. 

Matt Christen did a quick-fire demo showing us how he used Alteryx to find cabins within a certain range of a vacation spot. From the Minocqua website he manually copied cabin locations into Excel, then used the public Alteryx gallery tool to geocoding them. His next step was to put the data into Alteryx to essentially only show locations within a 6 mile radius of the center of town. It was a very interesting demonstration and something I would definitely consider doing as well. My pain point would be manually copying the data into Excel. I would much prefer to automate that process using some sort of web scraping ability.

Alex Christensen provided another example using the in-database tools which puts the processing power on the database and not the machine that runs the Alteryx workflow.

Next up was John Fomby of Alteryx who showed the group the road map for the next year. Some cool things are definitely on their way in Q2, but I’m more excited about the second half of the year. 

Overall it was a great first meeting. The presentations provided wonderful examples of what is possible. I liked the breakout discussions at the end and I might use that same idea in a Tableau User Group meeting but I would assigned high-level topics so members could get the most out of the discussion.

1st Data+Women Meeting

On Wednesday, March 23rd I held the first Milwaukee Data+Women Meetup at Anodyne Coffee. Seven people attended (including myself) and we discussed a variety of things. I began the conversation explaining why I wanted to start the group but that I was struggling with the group’s purpose. I posed a question to the group to get an idea of why they chose to attend.

Purpose
Most people wanted to network with like-minded individuals and learn about what others are doing with data and the tools they use. Additionally, having a place where women felt comfortable speaking up was an important attribute. Reflecting on the meeting, I believe we accomplished the objective.

Mentoring
Our conversation began with mentoring. It was a topic that stuck with me when I read Lean In by Sheryl Sandberg. Starting with an anecdote about a human resource intern who approached me to get involved with analytics, we discussed how we can support other women or get younger women interested in data science. A good point was made about keeping women in the field of data as some of the participants had experienced women leaving their departments.

Tools
The idea of the meeting came from a Tableau leaders webinar. At the last Tableau Conference a Data+Women panel was held and more recently the San Francisco TUG held their own meeting. So obviously when I began organizing the meeting I shared the information with the Milwaukee Tableau User Group. While Tableau brought us together, the conversation was applicable to all. Actually two of the attendees aren't Tableau users (yet).

We discussed some of the data science tools available, one of which was Tableau. Since most of us were familiar with Tableau we spent more time discussing Alteryx, R, and Hadoop. Alteryx is a data preparation tool and one other user had experience with it. R is a statistical programming language and Hadoop is a database for unstructured data.

Learning
This topic lead us to talking about how to learn new things. It can be difficult to know what you need to learn, but even more difficult to take the initiative to learn it. You have to make time, focus on the subject, and then try to translate what you learn into actual implementation. We discussed the best websites to facilitate learning and how we each learn on the job.

I found an interesting image the other day that I shared with the group. It's called the Imposter Syndrome and it seemed to apply to other participants.


Tableau 9.3 Has Been Released

Like everyone else, I received an email notifying me of the release of the newest release of Tableau (9.3). As always I took a look at the new features and there is some pretty cool stuff!

Self-Service at Scale

  • SEARCH – Like it sounds, similar to the filter search bar
  • CONTENT ANALYTICS – Sorting by most popular workbooks, trend chart in tooltip for interactors to find dashboards they might not typically look at
  • VERSIONING – This is one of the most exciting additions for me as I’ve been tasked to put our workbooks into SVN, rolling back changes made easy!
  • CONTENT MANAGEMENT – Now more users can refresh data extracts, which will help me out since we have many data sources that I want to give our users access to run as needed
  • TABLEAU SERVER MANAGEMENT – While there are many fun things here, my favorite is disk-space monitoring so we can avoid any issues

Flow

  • PUBLISH DATA SOURCE – The interface has changed, the biggest impact here is the swapping the local data source with the published one
  • MOBILE SIGN-IN – Stay signed in to the mobile app
  • ALWAYS CONNECTED – Desktop will remember your connection, the downside here is for admins who may frequently switch sites
  • TABLEAU ONLINE SYNC – Notifications if your data source needs additional information, love this!

Data

  • UNION – I’ve been using this for a while now from the beta directly to our Tableau 9.2 server because it’s a frequent request, no more writing weird queries using the “legacy connection”
  • SNOWFLAKE – I don’t know much (or anything) about Snowflake other than they were at the Gartner BI & Analytics Summit
  • DATA GRID – Additional preview abilities
  • GROUPS AND BINS – More data prep capabilities in the data source window
  • JOIN – The ability to pivot your data and then join, this just takes even more of those basic data prep needs and embeds them directly in the tool
  • DATA CONNECTIONS – Row level security capabilities among many other items regarding Teradata, PostgreSQL, Oracle, Pivotal Greenplum, Microsoft SQL Server, and Salesforce
  • PERFORMANCE – Better caching and only connecting to necessary data sources to create the selected view

Fast and Easy

  • MAPS – Even more geographic detail for Europe and India, more demographic information for the United States, and updates to postal codes
  • FORECASTING – Automatic seasonal selection to help with odd patterns
  • HIGH DPI – This speaks for itself
  • TOTALS – You can now exclude totals from coloring, which will help many of our users significantly
  • SHEET COLORS – Color in the sheet sorter and filmstrip views
  • PERFORMANCE – Various performance enhancements, I’ll have to test this on some of our more complex workbooks


I’d love to hear your thoughts on the newest Tableau features so please comment below! If you want to check out the details yourself, you can find them here: http://www.tableau.com/new-features/9.3