This was yesterday’s contribution to a Tableau forums discussion on data extracts, I thought it deserved a separate post that I could keep updated. There are some subtle behaviors and idiosyncracies in working with data connections, Tableau data extracts, and Tableau Server that aren’t fully fleshed out in the documentation, here’s my attempt! I start out with a review of the common file types and .twb vs. .twbx, and then get into some details on different types of connections and what happens based on different orders of operations, and toss in a gratuitous Buffy reference.
Southern Maine Health Care has an opening for a data analyst in Quality Management. Or, to put it another way, you’d get to be in the office sitting next to me, see lots of arts & crafts from my daughter and hear me brag about her gymnastics exploits, eat amazing desserts, learn all of my Tableau tricks, and hopefully teach me some new ones.
Seriously, though (well, I am serious about teaching and learning and my officemates are fantastic bakers), what we’re up to is improving patient safety and quality of care. On a daily basis I get to help people who save lives, and I work with an awesome team of doctors and nurses who are passionate, dedicated, smart, and really appreciative of the assistance I give them in analyzing and understanding data. Being a non-profit system in a changing environment, you’re not going to get a big Silicon Valley or Wall Street salary here, so there’s a tradeoff. That said, Maine doesn’t have Silicon Valley’s cost of living either, and there are a whole lot of plusses besides to tempt you to work in this northeast corner of the US. Here are some of my favorites:
- We’re on the coast, yet there are mountains, lakes, and a lot of woods close by. We get all four seasons (gorgeous falls, snow in winter, mud in spring, and hot muggy summers), and as long as you subscribe to the adage “There’s no such thing as bad weather, only the wrong clothing.” you can have a great time swimming, sailing, skiing, hiking, biking, etc.
- Pace of life. Compared to big cities and their ‘burbs life runs a bit more slowly here, which suits me.
- Architecture. The old mill towns have amazing construction and details, and the old farmhouses with their “Big House, Little House, Back House, Barn” design (I live in one) are a fascinating mix of form and function. (As well as many opportunities for learning home repair & improvement skills).
- Food. Portland and the surrounding towns have become a foodie mecca, including Biddeford where I work. Bon Appetit just named the Palace Diner to its best new restaurants list, and Business Insider named Elements: Books Coffee Beer to its best coffee shops list.
The set of tasks is pretty varied: You would be working to integrate new data sources and new metrics (we have over 110 active data sources tracking over 1000 metrics), find ways to improve efficiencies in quality management and beyond, and be responsible for a set of regularly-updated dashboards and reports, and have opportunities to redesign them to improve communication. A key goal in the next year is to find & develop ways to get more information out sooner throughout the organization.
Organizationally, SMHC is the largest employer in York County and a local institution. This is a different model from a start-up environment, here we get the job done, work our hours, and get to go home. Overall, Maine hospitals are the best in the country at quality and patient safety; we’re part of that, and the goal is to get even better. As an integrated healthcare system including two hospitals and over a dozen outpatient physician offices we’re big enough to have a variety of interesting problems, yet small enough that one person can have influence. Within weeks of starting you’d be presenting analytics to front line clinicians and/or senior management. A core challenge we are dealing with is working out how we can transition healthcare in our area from an ultimately unsustainable payor and delivery model to something more sustainable while increasing patient safety, quality of care, and improving how we do our jobs, and that’s part of why I’m here.
If you’re interested in this job, feel free to contact me at jonathan (dot) drummey (at) gmail or directly apply.
I’m going to plug some sessions for the 2014 Tableau Conference, if you want to promote yourself please add a comment below!
Getting your blend on has never been easier
At the 2014 Tableau Conference there’s a whole track worth of sessions on data blending by some fabulous folks, with my comments in italics.
- Mix It Up: Data Blending Basics by Alex Woodcock of Tableau. Beginner, Wednesday 10:45am-1:00pm and Thursday, 10:45am-1:00pm. If you’ve never blended before, this is the class for you.
- What’s In Your Blender by Charles Schaefer and Kelly Hotta of Tableau. Advanced, Tuesday, 11:15am-12:15pm. Tips and tricks for data blending.
- Jedi Calculation Techniques by Bethany Lyons and Alan Eldridge of Tableau. Jedi, Tuesday, 11:15am-1:30pm Room also Wednesday 3:30-6pm. Covers when blending might be used among lots of other non-blending topics in the 2hr session.
- Become a Mix Master with Data Blending by Bethany Lyons of Tableau. Jedi, Tuesday, 2:30-3:30pm and Wednesday, 10:45-11:45am. Bethany gave this presentation at the London conference, it covers how blending works in more detail.
- Mix and Match Your Data: Advanced Data Blending by Alex Woodcock of Tableau, Advanced,Tuesday, 2:30pm-5:00pm and Wednesday, 3:30-6pm. 2hr training to bootstrap yourself from basic to more advanced knowledge of data blending.
- Flowing with Tableau by Joe Mako (Tableau guru to the gurus), Jedi, Wednesday, 12-1pm. See how Joe approaches Tableau and conceives of the solutions that he does, he gave a similar talk in California this summer.
- Extreme Data Blending by Jonathan Drummey (yours truly), Jedi, Wednesday, 3:30-4:30pm. See below.
I’m energized about all of these sessions, especially Joe Mako’s. It’s not so much tips and tricks, but instead how to “think Tableau” and work with the software. I’ve used the metaphor of a structured poem before, in that when writing something like a sonnet we have certain conventions to follow, and as long as we do we can have lovely results, the same goes with Tableau in how we structure the data and use the different features and functions in the software.
My own session on Extreme Data Blending mashes up South Park and Frozen in a deep dive into how data blending works. I’m excited to share what I’ve learned, especially how that every single odd, strange, or seemingly broken result of data blending actually has a logic and reasoning behind it that can be understood, explained, and even made use of. If you’re new to data blending and want to attend my session, I suggest you go to one of the other sessions to get grounded in blending behaviors. If you’ve been using blending already, I promise you you’ll learn something new, though if you’ve read all of my posts on data blending then some of the use cases will be familiar. If you’re already a Tableau Jedi, you’ll like this session because I’ve purposely created it to start out with a review of known territory, then we’re going Jedi++.
A few other sessions and meetups that I’d like to plug are:
- First timers and conference newbies – Emily Kund and Matt Francis (they host the one and only Tableau Wannabe Podcast, totally worth a listen) are hosting a conference orientation session Monday at 4pm, before the welcome reception. They then repeat that First Timers’ Field Guide session Tuesday at 11:15am
- Tableau Community Meetup – Wednesday, 12:30-2pm in Community Alley. Here’s your chance to meet in real life Tracy, Patrick, and Jordan who run the Tableau forums along with assorted other forum helpers.
- Meet the Tableau Zen Masters – Besides my session, the one place you can definitely find me (ok, besides stalking Neale Degrasse Tyson and Hans Rosling for selfies) is here on Wednesday at 6pm, though I’m not sure yet where “here” will be.
- Women in Data Meetup – Jenn Day and Anya A’Hearn are hosting this meetup on Tuesday at 12:45pm in the University Room at the Sheraton. I think it’s fantastic Jenn & Anya are hosting this and that Tableau is supporting the meetup, see #womenindata for more on the topic. We all need to find our tribes, maybe this is yours!
See you in Seattle!
In all the hype about big data, we have to acknowledge that some of us have “wee” data. Not every organization has a fully-built out Information Systems department or Business Intelligence team with access to petabytes of data and the latest tools like Hadoop and Alteryx. Some of us are still running on legacy hardware and software, have tiny budgets, part-time staff, and thousands or tens of thousands of records that we want to analyze vs. billions.
My day job is in the latter camp. For all that US healthcare includes the latest treatments and technology, healthcare IT has historically been behind the times. My desktop is running Windows XP SP3, Office 2007 is our productivity tool, Microsoft Access is our most commonly used database, and Tableau is our go-to choice for data visualization (so there’s at least one area where we’re we’ve got current technology).
Every couple-few months I get a question about Microsoft Access and Tableau, I thought I’d take a few minutes to combine my answers into one post, so read on for what I know about integrating Access and Tableau.
Here’s a quick lunchtime post on working with durations in Tableau. By duration, I mean having a result that is showing the number of seconds, minutes, hours, and/or days in the form of dd:hh:mm:ss. This isn’t quite a built-in option, there are a several ways to go about this:
- Use any duration formatting that is supported in your data source, for example by pre-computing values or using a RAWSQL function.
- Do a bunch of calculations and string manipulations to get the date to set up. I prefer to avoid these mainly because they can be over 1000x slower than numeric manipulations. If you want to see how to do this, there’s a good example on this Idea for Additional Date Time Number Formats. (If that idea is implemented and marked as Released, then you can ignore this post!)
- If the duration is less than 24 hours (86400 seconds), then you can use Tableau’s built-in date formatting. I’ll show how to do this here.
- Do some calculations and then use Tableau’s built-in number formatting. This is the brand-new solution and involves a bit of indirection.
If you’re not off on some sunny beach somewhere (or even if you are), here are some (free!) opportunities coming up for you to sharpen your Tableau skills and get previews of material that will be in my book. I’ve got 3 presentations in the next month, two are in New England, the other is a webinar:
- June 24th at the Boston Tableau User Group: Making Tableau More Predictable: Understanding the Multiple Levels of Granularity. This is a reschedule of the session I was going to give back in April, it’ll be a combination of presentation and hands-on practice on how to “think Tableau” so your calculated fields, top & conditional filters, table calcs, etc. are more likely to come out the way you expect. Alteryx is demoing their software, and Zach Leber is also presenting.
- July 10th for a Think Data Thursday webinar: Setting up for Table Calculation Success. This will also review some of the granularity material, and go through how you can set up views and table calculations so that a) they work, and b) if they don’t work how to diagnose what is going on so you can get back to a working calc or be able to submit a really detailed support request.
- July 22nd at the (inaugural) Maine Tableau User Group: Getting Good at Tableau. Hosted by Abilis Solutions in Portland, I’m helping to kick off the MaineTUG with a talk on how to set up your data and build your Tableau skills (including how to avoid getting distracted by all the gee-whiz features of the Tableau interface) and I’ll do some intro of Tableau 8.2. Grant Hogan of Abilis will be presenting, as well as someone from Tableau.
I’ll update this post as the links for registering appear, I hope to see you (virtually or in person) at one of these events! And if not then, I’ll be a the Tableau Conference in September.
There was a Tableau forums thread on At the Level awhile back where Matthew Lutton asked for an alternative explanation of this somewhat puzzling table calculation configuration option, and I’d promised I’d take a swing at it. Plus, I’ve been deep into book writing about shaping data for Tableau, and a taking a break to write about obscure table calc options sounds like fun! (Yes, I’m wired differently.)
Read on for a refresher on addressing and partitioning and my current understanding of uses of At the Level for ordinal table calculations such as INDEX() and SIZE(). Part 2 will cover LOOKUP(), and Part 3 will cover WINDOW_SUM(), RUNNING_SUM(), and R scripts. If you’re new to table calcs, read through at least the Beginning set of links in Want to Learn Table Calculations. Thanks to Alex Kerin, Richard Leeke, Dimitri Blyumin, Joe Mako, and Ross Bunker for their Tableau forum posts that have informed what you’re about to read.