Thursday, 10 November 2016

Data16 - Keep it simple stupid by Chris Love

Keep it simple stupid


“Our world is unbounded by complexity”. Tolomy was living at a time of rapid development and built up an enourmous amount of data. He looked at the data and he mapped planetary movements. But he had the earth at the centre of the movement. It made sense.


The helio-centric model made more sense but faced more significant challenges due to the challenges to the culture this theory made.


Sankeys
Made originally but an engineer captain Sankey to look at steam power and energy loss throughout the process of a steam engine.
Minard’s Napolean’s march into Russia is probably the first that is largely used and most infamous


Sankeys are tough to build in Tableau. There are a lot of steps and a lot of techniques. Chris uses the example of Pablo’s Spanish migration and how a basic set of small multiple histogram show up the trends a lot more clearly


It's not just Pablo. A lot of people have used and built a lot of sankeys. It's not wrong but is it the best way to achieve what you are trying to achieve.


Chris highlights Joe Radburn as he is looking at complex subjects but is visualising them simply. This is arguable just a challenging skill to master.


Kuhn - new discoveries are only made when you don't have a preconception as to what the answer is and the best tool to achieve that preconception. Only exploration will lead to discovery.


Data sources should allow people to explore for themselves, or dashboards to let them answer their curiosity, story points are heavily guided.


Design for mobile is making us think more simply about the message we are trying to convey.


Wednesday, 9 November 2016

Pimp my Viz: Tokyo Drift - Jewel Loree

Jewel Loree


Taking crazy tips on how to create cool dashboards


Viz 1: Jewel’s Pokemon Go viz
For device designer, text doesn't resize but images do so take images of your titles
Helper buttons are great and useful - create a basic view of just a shape and the customise the tooltip
Jewel’s way to build unit charts is great - she's going to post the calcs on her blog and I will add a photo later [add photo here - remind me if I don’t]
Bring custom shapes in in the same order as the dimension so you can just click assign palette to save having to allocate them all individually
Mapbox used to create a similar map style to match Pokemon Go’s maps
To have different vizzes on your device specific dashboards, then just have the floating element just catching the edge of the dash (please make this easier tableau)


Viz 2: Data Breaches by Marc Schonwadt
There is a lot of custom formatting that you can do with text.
Check out the layout tab to see how someone has built their viz
Hiding index menus using layout containers (set up the hidden element as sitting at negative whatever the width of the layout container.
Jewel just copied across the dashboard which pulled in Robert Rouse’s technique dash to take his helper data with it. Make sure you don’t fit the width as it no longer collapse.


Everyday Pimping
Use custom colours
Do more with the Marks Card
Create custom headers
Always fix your tooltips
Thoughtful interactions


Putting a label on the bar and take away the header. Put the rows on the label and align the text to the left. Then fatten your bars.
Sort your bubble charts but sorting your dimension and sort on what is setting the size
Create custom header called Canva




Data16 - Developers on Stage

Analytics
Automatic drill - level of detail goes deeper as you zoom in
Map scaling added in to the maps
Spatial file connector coming in 10.2 beta
Python integration - using python scripts in calculated fields
Tooltip selection - click on the categorical fields in the tooltip to highlight by that selections
Date filters - filter to latest date rather than being stuck on what you originally published as.
Step and Jump lines - squarer trend lines
Advanced conditional formatting


Dashboards and Stories
Distribute evenly to space out your objects on a dashboard
Can add margin around all objects on your dashboard. No more blanks to separate your charts
Expressive text editor - add images and URLs in to text objects (including tooltips)
Web authoring has more right click functionality than before
Story points on the web
Full screen viz on the web


Mobile
Direct linking from subscription emails and condition warnings
Smooth tooltips for mobile. Also easier selection of small marks in a movie cuz. Like selecting where to enter text on a phone when holding down your finger.
Commenting on the go (not just in Desktop and Server)
Offline interactivity


Data
Joins on calculated fields
Database unions
New data connectors: pdfs, JSON


Extensibility
Server client library makes it easier to write simple scripts
RET API: JSON and CORS support
GetData() 3rd Party Charting libraries
Mobile App bootstrap - on GitHub now




Tuesday, 8 November 2016

Cross Database Joins - Bethany Lyons and Alex Ross

Bethany Lyons and Alex Ross


The unexpected solution to many tough analytics problems


Bethany has looked forward to delivering this session for a long time as CDJ (Cross Database Joins) can be used to solve so much


Often most analysts have read only access so don't have the chance to create data
Identify (create vs deriving)
Understand (complexity and volume vs performance)
Use - focus on CDJs as the solution


Example 1
Taking a 12 month subscription from just one row and spreading it across the 12 months (on a monthly basis) to show the monthly revenue. Use a simple excel scaffold of month number and a key of 1 to create the product join.


To create the filter of finding when the contracts will earn revenue up to, Bethany used a Boolean filter calf but then added it to the data source filters to cut down on the processing done locally on your machine.


V10.2 adding joins based on calcs


Example 2


Counting staff employed at any single point in time - use missing values to fill the gaps on the table calcs


A scaffold of all dates is needed though and the just return those that are after hire and pre-termination date.


What if the scaffold creates huge amounts of rows?
I.e. If you have seconds a tool is active, you can scaffold on a day level and the create a calc that then counts a full day’s worth of seconds (86,400) but if a partial day then use a datediff() calc


#data16 Visual Design Decisions by Andy Cotgreave

Visual Design Tricks for Dashboarding by Andy at
tabsoft.co/designmonth for the resources


Dashboarding styles and sophistication develops over time. This is true for Andy (and all of us)


Iraq’s bloody toll dashboard is easy to change to change the feel of the dashboard. Here’s the original: http://gravyanecdote.com/tag/iraqs-bloody-toll/
Orientation, colour and title can completely transform the meaning of the dashboard


‘Great designers produce pleasurable experiences’ Don Norman, The Design of Everyday things


User design decisions have some large impacts but it becomes lower level of improvement as you get closer towards over engineering something


Get rid of shading on titles as it adds cognitive load. Remove borders to allow the data to stand out.


Use fewer colours and make it relevant to your data theme. Try building your dashboard in black and white to see if it stills work as a dash and is clear


We have to question the data in multiple ways and through different charts to find the stories in the data


So many ways to interact with a dashboard and the level of tableau awareness will change what people normally do


There are lots of changes that have high impact but some are more time consuming that others. Choose wisely!


Use custom dates to prevent people from accidentally drilling down through the date hierarchy.














Data16 Keynote

9th annual customer conference.


8,947 people at their first conference.


Tableau marking a difference for companies at huge scale all the way through to individuals.


Maps give huge amounts of data in simple form and allow for multi-faceted visualisations. VizQL allows any dataset to be accessible to anyone.


Tableau looking to bring in:
viz in tooltips
Multi layers of visualisations


Tableau are conscious that databases are not necessary fast enough. In-memory data work is important. HyPer is the next step for this.


Five key areas moving forward:
Visual analytics
Data engine
Data management
Cloud
Collaboration


Visual Analytics
Instant analytics
Time and space
Natural language


Instant analytics
Reference lines with key numbers
Select time and the call out labels will show change (taken from Vizable)
Instant multiple visualisations to push you to explore new angles
Summary of the clusters when you hover over the cluster to show the key attributes about that cluster
Time & Space analytics
Add geographic elements just based on the long / lat of the data. You won't need the data fields there. Tableau will do that for you.
Long / lat to join data sets
Drag and drop indexing of time based data


Natural Language support
Lets you type the question you want to know and Tableau will add elements that allow you to filter by the ambiguous terms. Called Eviza.


Data Engine
Hyper
From next year we will have access to this - faster data analysis, data ingestion and enterprise scalability
HyPer can load and analyse data at the same time. Real time ingestion.


Data Management
Balance between governance and freedom
Certified data sources by key server users so the users know that data source is correct and accurate
Icons to show when users have added calculations to the data source. Quick way to recommend new data field be added to the certified data source
Data fields measured by how often they are used
Seeing which workbooks are created from the data source and which fields are used where. Can add data fields with just drag and drop.


Data preparation
Project Maestro - new product for data prep and integration
Drag and drop joins within reference tables
Maestro available later next year


Cloud
Three aims: connectivity, simplicity, anywhere
Live query agent - a secure tunnel through to on premise data sources
Prebuilt templates of dashboards as datasets are consistent with cloud applications
Aim by end of next year to have everything in browser editing that is in Desktop
Save once, see everywhere - save offline and then published when next on the web
Server has recommendations on how to manage capacity and the a couple of clicks to update
Tableau server on Linux - ready for release next year


Collaboration
Drive a culture of analytics
Machine learning on server to serve up individual preferences
Discussion chat in the server browser and desktop
Data driven alerting is coming soon - simple click on the metric to set up
Metrics - save metrics from different dashboards to pull the key elements of your business together
Safe and secure discovery - personal sand boxing and team sand boxes too






Sunday, 18 September 2016

Iron Viz III - Device Specific Dashboards

If you scroll back through my blog you will notice one missing item. Iron Viz Qualifier II. It was all about politics during a pretty dramatic time. The Presidential candidates were getting chosen in the US and the UK was in the midst of voting themselves out of the EU. Visualising data on politics was the last thing I wanted to do.

So why this enter this time? Quite simply, why do I enter any of the Iron Viz competitions?
Well it isn’t to get up on stage and viz my little heart out. It’s to actually investigate subjects and techniques I am interested in. But this time was different. I actually could develop an app that was useful for me and improve my chance of getting better at something I do a lot; namely Cycling.
I have been sitting on a data set of all my rides for the last two years but I didn’t just want to visualise them for a vanity project of “oh look how much I ride”. I wanted to save the data set for a time that it would actually teach me something and aid my improvement. Tableau’s release of device-specific dashboarding gave me exactly that opportunity.

The data set shows that I already capture the data from each ride manually, but now I can just add it to a google sheet and get instant feedback on whether I am riding as much this year than last, whether I visited some cool places and I shouldn’t forget, or whether I ride more if the weather is better etc.
Keeping a running total of the distance I do, whether it is inside on the turbo trainer or Spin Class or on training rides or tours, can give me an idea of whether I am improving and riding more distance with more confidence. The mobile dashboard can be easily checked to see this.

But what about my friends who don’t keep up with every ride? Well they can check out the normal dashboard that will give them a view on the foreign adventures and how I am getting on with my overall distance for the year (a little peer pressure goes along when it’s raining outside and the last thing you want to do is hit the roads).



Tableau techniques
I don’t often build individual callout numbers but in this dashboard they certainly had their places. I didn’t want to create multiple graphs with similar trend lines for different metrics. Time on the saddle and overall distance would always follow the same pattern so calling these overview numbers out was an easy design choice to make. To do this, just drop the value you want to show in to the middle of the visualisation (or on to the text part of the marks card). You can then edit the text (click on the text part of the marks card) to put the value in to a description to help position the number.

Running Total - In The Information Lab we obviously use Tableau to visualise our sales numbers and seeing them evolve overtime is useful. Comparing similar time periods against each other is a great way to show your progress so I decided to take a monthly look at the distance I rode and how it adds up. Giving myself lots of monthly targets rather than always trying to make a new personal best can be a lot more motivational and helps to break big targets down. The way Tableau handles dates is perfect for this so splitting out the months in to individual running totals is really easy as you can use separate date parts (day on ‘Columns’, months on ‘Detail’).


Shapes as filter – Rather than using a quick filter, Tableau actually performs better using a sheet with a dashboard action filter affecting the other sheets. This means that users need to be guided to interact with the worksheet that you want to act as the filter. A fun way to do this is to use custom shapes to make these filter sheets more interesting. You can load images and your own shapes in to Tableau by adding them to the ‘Shapes’ folder in your ‘My Tableau Repository’ (you’ll probably find it in your ‘My Documents’ folder if you are a Windows user). Rather than just having four icons for the seasons – I thought four different images of me cycling during the different seasons would illustrate this differently.