Launching a self-service analytics programme (part 2)
My first post on launching an self service analytics programme was all about why I decided to do it.
This post will go into the detail about what my particular programme covers and why.
So, after deciding on what your programme aims to achieve, who your target audience is and agreement from your business sponsor, it's time to start planning a curriculum.
My goal was to take general users of Tableau Server and people who tended to interact with our analysts frequently and enable them to limit these interactions and answer their own questions via the data published in Tableau Server.
Generally they had never used Tableau Desktop before.
For my particular programme we had identified (after trial and error) what an ideal participant represented.
- Familiar with data in some format — Microsoft Excel, Google Sheets, Salesforce.com
- Not too junior and not too senior — Positions in the company that gave them a time to dedicate to developing a new skill, but also the experience and authority to use their time effectively and not just follow instructions from a manager
- Employed by the business for at least 9–12 months — This was so that the participants had the knowledge and understanding of how the business works, how their team fits in and what the challenges and questions are
These three points helped me recruit enthusiastic participants who were eager to develop some new skills and support their teams.
Based on the beginner level experience with Tableau, I set up the sessions to progress from almost an introductory level all the way through to a fairly proficient Tableau Desktop user.
Ground rules
Before we even open up Tableau Desktop, I like to do a bit of general housekeeping and set the expectations to the group. I believe this is important as it indicates that
- I am the instructor
- You are here to learn
- We are all working towards the objective to use data to inform our teams/areas more effectively
So what are my ground rules?
- No phones during the session
This is rude and distracting to me and the other participants. You have agreed to spend two hours on learning and development per week. If you can’t commit to not checking a phone in that time then there are other issues at hand.
2. Be punctual
The training sessions are created based on a fairly strict timeline. There is a set amount of content to get through in a short amount of time. Waiting for people to turn up causes the session to be disrupted and not as effective.
I ask for people to advise if they are unable to make sessions or running late earlier so I am aware of who is attending (from the confirmed invites) and we do not delay the start of the session. This includes arriving with teas, coffee or water.
3. Respect other participants
This should be a no brainer, but people learn at different speeds. People have a different level of understanding. We are all here to learn so support the people around you and if people have to ask questions, please listen and give them a chance to speak and learn.
So, after I lay down the ground rules. I quickly move into an ice breaker exercise. The main reason is that there are eight participants from all over our business who most likely don’t know me or each other.
I give them a bit of a story about myself, what I do at the company, my data viz creds and then share a story about my weirdest job as an ice breaker.
We go around the group saying who they are, what department they work in, what they hope to achieve from the course and their weirdest job.
After a few laughs, a few “yep, been there” moment we are ready to start talking about data visualisation.
Session 1: Why we visualise data
I spend ten minutes discussing what DataChefs is all about. It's a way of learning, supporting others (via data), its best practise and understanding data.
I then talk about what is data visualisation.
For me, the definition that I like to use is one that was delivered to me by Andy Kirk while attending his data visualisation training course.
To represent and present data to facilitate understanding
When working with Joanna Hemingway she proposed adding to this definition with:
That can be used to drive better decision making
I then like to use the exercise from Ryan Sleeper showing the value of visualisation. You can read about this in Ryan’s blog post on his PlayfairData website.
Leading on from this, I like to then show 3 minutes from the TED talk by the late Hans Rosling from 2006 to get the group excited about data visualisation. The passion he has for this topic is infectious and I like to think that part of this passion and enthusiasm passes to the participants.
Finally, we are ready to open up Tableau Desktop.
This session covers a lot of the basics in Tableau Desktop. Connecting to data, going over the types of connections we would expect to use. How to check for things like the data source owner (published data source), when it was last updated etc.
I then go over the data pane and explain the dimensions and measures areas. We play around with dragging some dimensions and measures into the data pane and seeing what happens when you change the order of the dimension pills.
We click on “show me” and explain the marks card.
We look at all the shortcut icons and explain what each item does and why they are useful.
Finally we create a few basic charts, mainly bar chart, line chart using date dimensions and use the marks card to alter their appearance.
Two hours normally flies by.
Session 2: Chart types, attributes and cognitive load
This session is all about creating charts. We begin by understanding what a chart is and how they are constructed. There is a lot of theory incorporated into the training especially around themes like cognitive load and psychological schemas.
I explain marks and attributes and how they are used to represent the information in the form of a chart. We go over the different classification of charts and then we start “speed charting”. Making 11 different charts in the session. I try to make it a bit of fun and light hearted with the time pressure to get all 11 completed, as well as getting participants to share what chart they thought was worthy of a second date.
Session 3: Calculations and data types
One for the finance people. Lots of calculations both table calculations and creating calculated fields. We create examples of calculations for a range of functions: aggregate, number, string, date and logic. I try to make this as realistic as possible and try to frame exercises in which participants are asked a question which requires a calculated field to be created to get the answer.
Session 4: Interactivity (filtering, sets, parameters etc)
This session focuses on how we can use the functions in Tableau to really engage an audience. Partly to try and answer secondary questions and avoiding re-work. Why interactivity is useful. We cover several examples of interactivity — what the benefits and limitations are, and then create a working example.
Session 5: Design and formatting
One of my favourite sessions. It is really hard to compress all the information and content out there about designing for visualisations in 2 hours.
I have made an attempt at this by spending time on colours, fonts, layout and other functions (layout containers).
For the last part of the session I invite a guest speaker in, one of my lead analysts in the team who talks about the process of designing. We then do a bit of inspiration, showing what is possible.
Session 6: Data Storytelling and dashboards
The last technical hands on session is used to talk about dashboarding or stories in Tableau. The different ways you can bring the charts together and build a story with titles, text and annotation. Making sure that the business question is being answered and that end users can interpret the information and take an action.
Finally publishing and adding all the housekeeping to the final dashboard which establishes the best practise principles we
The Showcase
The culmination of the 6 weeks of training.
After week 2, I give a task to all participants to find a business question from their area. The goal is by the end of the course to demonstrate an understanding of the theoretical concepts of data visualisation as well as the technical elements of Tableau Desktop.
I also want to make sure that the participants are comfortable talking about data and Tableau in front of a small audience.
So week 7 of the DataChef programme we all gather to see the final projects from each person on the course. They have 10 minutes in which they present their business question, demonstrate the dashboard they created and we discuss ideas, feedback and other comments about it.
I felt it was important to have a session to give the programme a sense of finality. Lots of applause and I also invite special guests and line managers to give them a real view of the achievement from the group.
Phew.
Seven sessions of training over nine weeks. It’s a long programme and I do feel mentally drained after it. As well as preparing all the training content and organising all the sessions, there are lots of 1–2–1 meetings with the participants to discuss data requirements for showcase projects.
That being said, I wouldn't change it. For me the best part is when each person has that lightbulb moment. The instant they realise what is possible for them in the context of their role and team and the value they can add.
Straight from a Mastercard advert.
Priceless.
The final part of my “Launching a self-service analytics programme” blog post series will be about my reflections and iterations I’ve made over the duration I’ve been running it.
Good luck if you are planning or looking to launch a programme of your own.
