Thursday, 5 July 2018

TC18 London - Practical Tableau Tips

Ryan Sleeper

Fundamentals = Success
Ryan’s two most popular posts out of 200 is one on bars and one on lines

Bar chart tips
  1. Give your headers space
  2. But don’t make your bars too fat
  3. For only a few bars - use a direct label and hide the axis
  4. Heavy axis ruler bar to give the base a firmer zero line

Line chart tips
  1. Maximise Data Ink ratio (Tufte concept) To do this minimise the non-data elements
  2. Remove redundant data ink
  3. Make increments on the axis larger
  4. Remove obvious axis labels
  5. Highlight the key element you want to analyse

Psychological Schemas - we learn by patterns so if we disrupt the pattern, we struggle. Ie if green didn’t equal good and red wasn’t bad
  1. Don’t break these within your visualisation or you will confuse your users

Spatial Context
  1. Adding any spatial element to a view helps add additional context and spot weird outliers as we have preconceptions about how the pattern should be

Describe
CTRL+E - in Tableau this can tell us a lot
You can also click on a calc in a Calculation window and click ‘describe’ on the dialogue box and you can copy and paste your calculation

Filter in Use
Create a calculation If sum(num of red) <> attr({fixed: sum (num of records)}) then ‘Filter in use’ else “” end
Add to the dashboard to show when someone is filtering

Strategy
Descriptive analytics (basic dashboarding)
Prescritptive analytics - explain why something has happened and describe what to do about it
Add your own commentary by using a string parameter on another sheet and a three choice option as to whether it is positive, neutral or negative and then show the resulting values in the main dashboard.

TC18 London How Tableau solved a life crisis - Bethany Lyons

Bethany Lyons

Don’t try to be good at Tableau - try to be good at solving (and generalising) problems in Tableau

Meta Points
  1. Optimising performance
  2. Progressing your career
  3. Building teams
  4. Making software recommendations

The crisis
Spending 180 days in the UK to warrant the Permanent Residency status in the UK
From passport stamp data, you can work out days in the UK
Level of detail calcs can give you the days in then UK by trip ID
Bethany had 189 days abroad in 2014 (building the partner ecosystem in France)
Data captured on 7th Jan 2018 but showed 11 days for 2018. This showed the days abroad had been allocated twice

Bethany tried to work out how to split and allocate the years
Step 1. Identify the years
Step 2. Allocate the right number of days to the year (chunky IF statement to work out Start date to end of year, and end date from start of year)
Step 3. There is double counting as trips can have multiple legs
Step 4. Use a sequence value and only bring back max sequence value
...but there are easier ways to solve this

Don’t hard count your calcs for the data you have, think about the use cases which will break your hard coding

Issue - immigration years were rolling year based on your application date

Types of temporal data tables
  1. Event - a record represents a state change at a moment in time
  2. State - each record represents state during a period of time
  3. Calendar - dense time range bounded by event time domain
  4. Time - each record represents a state in a moment in time

Event table was what Bethany used for the original data
State table had a value for a property
Calendar - is a dense time range
Time table - for a dense range of time, a property of an entity has a value (ie for each day, there is a specific value)

Time tables are created by joining calendar date to state table (ie scaffolding as it is more commonly known)

Bethany needed to create a state as to whether she is in the UK or not. To do this she needed a start and end date - you can use aggregation in Prep to do this
Calendar date - use the idea that calendar is <= end date and >= start date (to not bring in any unnecessary date

By adding an appointment date parameter, Bethany could then create a rolling year bin. Take the integer of the date / 365 (minus 1) to work out which year it is

Bethany was fine but then she wants to release were there dates when she would have hit the 180 day limit?

If you want to have a record for everyday, you can join the calendar date to the Data source by using a calc join (1 = 1...see Bethany’s session from last year) to create the rolling year calc

Like all Bethany sessions - watching the recording to get all the value from the techniques but it will hopefully capture some concepts to go away and learn (or Google)!

Complexity arises from incrementally and reactively solving a problem (walk away from the desk before solving the question)
Get a clear understanding of what is, work out the semantics of your question and then it’s over to you as the analyst

Meta summary
Performance problems arise from complexity -Holistic thinking is the best solution. Iterate but then don’t be afraid to rebuild.
Progressing your career - visual design and data design is very different. There is a massive shortage of data designers.
Building teams - get both visual and data designers
Software recommendations - all principles discussed are unique to Tableau. Most companies look at features and price, this leads to examples in the first convoluted feature. Great software helps you escape these elongated builds as it will have features that compose well (VizQL is a language and you can communicate in many different ways)

Wednesday, 4 July 2018

TC18 - Advanced Mark Types

Going beyond Bars and Lines

How many chart types are there in Tableau?
There is no answer as really it’s unlimited depending on the techniques you use
1967 - Jacques Bertans wrote the ‘Semiology of Graphics’
Jock McKinley’s research
2003 - Chris Stolte creates VizQL
Tableau writes all of these elements together into one product

Heatmap Calendar
This isn’t a chart type - it’s taking date parts and placing on to shelves
Weekday on Columns, Week on Rows etc

Pareto chart
Is a line chart and a bar chart in combination

Donut Pie Chart
A dual axis pie chart with the pie in front, whited out. Mrunal used min(1) where as I use avg([Number of Records])

Hex tile map
Using a scaffold of the states and their X Y co-ordinates

Does this mean I should be using all different chart types?
Stop and think - challenge stakeholder requirements - ask why? Need vs Want
Discuss the analytical value
Build vs Analyse mentality - rather than just build the report, if you are asking questions of the data then you will create a better product

If you want the challenge to test your skills then there are lots of blogposts to help you work through the charts

Best way to learn is deconstruct and recreating it
This is what Tableau Public hugely helps with

TC18 - Questioning your marks

Neil Richards - HESA

Zen doesn’t mean technical impossibility

What constitutes a Viz?
Tableau means a picture of a scene - a nice way to look at the overview of a Viz
A framework, one or more visual encodings, annotations

What are the Marks?
The actual representations of your data - ie the Visual Vocabulary from the Financial Times
Removing annotations and axis titles makes most data visualisation useless

What is data Viz consumption?
Does the Viz need to be consumed in 2 seconds?
Really, the fast element is important but don’t ignore the ‘longer term learnings’ that your consumer should be able to be deduced from your work

How important are titles?
Remove them and find out!
Be careful with screenshots as people will often chop titles
Not just titles but also add short descriptions to add more depth or detail for new consumers

What is White Space?
Defined as the bit that isn’t showing data (it doesn’t have to be white)
Data to Ink ratio - what you are using to show the information vs all ink showed on the page. Ie remove any unnecessary elements

Is white space always your friend?
Remove obvious axis titles (years) and just leave the scale
Use colour in your title to remove colour legends
Reduce the darkness of non-data elements to push the detail in to the background

What makes a visualisation memorable?
This is changing over time - style and tools change over time
Intrigue leads to insight (Beaumont) - make people curious
Chart junk can add to memory as it can create a more unique style

How can you make best use of annotations and labels?
Annotations can add to pinpointing insight but also adding more clarity
Empty space can make strong, clear messages with the absence of data

How important is self review and feedback?
Very - especially when you are challenging the normal conventions

TC18 London - Getting out of your Dataviz Comfort Zome

Dataviz Comfort Zone (DCZ) - being ok with what you produce but ultimately something that is containing information and not insight
Strava is used a lot by Eva but their data Viz doesn’t allow Eva to ask the questions she wants answers to. Is it distance per week or distance per day?
Garmin doesn’t do much better- their dashboard doesn’t lead to intrigue, it leads to ‘ok’ but no further chances to ask more questions. Also shows lots of info that is not useful for the specific questions Eva wants to ask.
‘Iterate or Die’ - culture change happens continually so do your dashboards

Analysts
- Be Brave as you are the author and you are driving the improvements. Challenge the status quo, you’re the expert so don’t let those asking the questions tell you how to do it.
- Keep working on improving your skills; speak up - communicate confidently; keep an open mind; take feedback; share your knowledge and skills (teach and support others)
- Quick wins - land some benefits ASAP and keep iterating as you won’t land the perfect dashboard but sharing things early will mean better questions will be asked and you will be challenged to do more (and learn new techniques)
- Take inspiration from other people
- Research a new subject to allow you to explore the subject

Team Leaders
  • Let go! Let your analysts do all of the above for themselves. Your job is now to remove blockers to your team being able to do the above
  • Build a feedback culture - fostering training and create exciting roles
  • Attract great talent...then support their development through training and conferences. Make it part of their reward structure. Mentoring - pay it forward by getting the mentee to double the time they receive and give it to others
  • Inspire - share ideas and use related worlds to find differing approaches

Executives and Decision Makers
  • Be open to new ideas
  • Encourage Growth
  • Create a sharing Tableau Culture - The Tableau Community is open to sharing knowledge and learnings so invite them in.
  • Encourage people to play in their own environment (Tableau Public) so they can then bring those skills in to the workplace
  • Create live, in person events to get your analytical individuals together. A place to play will become a great place to learn. A great way to show off how your organisation and how you work with data

What happens after that?
  1. Connect, learn and have fun - share ideas with others
  2. Engage, challenge and enrich
  3. Empower your people

TC18 Opening Keynote

New Tableau functionality

For the Creators:
Connecting to Data in the browser through Server
Joins and connections in the browser so can form your own data set
Workbook formatting on the web
Quick number formatting to make the number formatting process less hidden
  • Able to see instant updates
Dashboard starters for Tableau Online (Salesforce, Marketo etc)

Viewers:
Able to comment on images and snapshots taken from dashboards. Can lasso the elements of interest and write custom comments over the top of free form lasso

Tuesday, 10 October 2017

Vegas Data17 - Opening Keynote Brief Notes

Adam Selipsky
61,000 customers in 100+ countries
Data Myths - created to replace the unknown and create reasons for what happens
#1 AI will replace the analyst. Actually AI is likely to assist the analyst. Tableau is smart software. Drag and drop of Clusters and Trend. Natural Language Processing will take out some of the technical barriers.
#2 Data is only for the analysts. More data programs in Higher Education. 800 million knowledge workers. Excel used to be taught in university, now school children use it. Tableau aiming for the same.
#3 Data governance means no. Data is valuable so needs to be protected. But that’s the old model - the bottleneck has been removed. Governance should means secure enablement.
Honeywell deals in human safety. It needs to have appropriate data ready at appropriate times. Giving multiple environments with clear transitions between them helps to manage creation at all levels. 20,000+ users within two years as the right mix of options gives governance and flexibility.
#4 There can be one, perfect source of truth. Innovation is so rapid that you can predict the different sources and combinations of these. We live in a world of many sources of truth. We have to embrace that. Tableau invests in all of the flexibility that you need. Go past the hype and try the tools. 

Francois Ajenstat
Myth - BI platforms take power away from the people. Often designed for specialist. Tableau focuses on people. 

100+ features added in Tableau over the last year. 50+ came from the community.

10.5 in beta today
Hyper
Linux
Viz in Tooltips 

Data Engine
Hyper is the new Data Engine. Tableau Data Engine was great. But time to scale up. Hyper instant compared to 25 second load where heavy calculations are used. Extract creation will also be massively improved (3 million rows live SQL) double the speed in Hyper. Hyper doesn’t sort the data like a TDE. 500 million rows isn’t possible with TDE, Hyper is possible. No migration necessary - just use 10.5 and it’s there.
Data prep
Still working with existing data prep partners but not everyone has this - introducing Maestro. Data profiles gives you a sense of your data. Filter outliers with normal exclude functionality that you find in Tableau. Grouping through Fuzzy Clustering to sort poorly entered data. Clear view of the changes made through the transformation. Drag and drop joins and unions. Very simple join and cleaning of joins. Maestro in beta this quarter
Extensions API
Makes additions in to Tableau rather than Tableau in to other applications. Dashboards becoming their own applications. Dashboard Extensions create two-way communication with the data source.