Tableau Server resource is a valuable commodity and one of the activities which use this, like no other, is the rebuilding/refreshing of Data Extracts (TDEs). At Atheon, our data (usually) refreshes each day, with many hundreds of extracts to refresh. This uses a huge Continue reading TDE Rebuild using up all your Tableau Server Resource?…Try using the SDK
I recently wrote a 3 part series on my 2 favourite subjects…Data Visualisation and Grocery Retail. As the Data Animators are all about Data Visualisation and the Retail Sector, this seems the perfect place to share it… Continue reading Why Visual Analytics Should Become the ‘New Normal’ in Grocery Retail
So (what now seems an age ago) I took my annual holiday, and went back (for the 5th time) to my favorite country…India.
While digging out the back-pack from the back of the wardrobe, I came across our stash of photo’s…about 5 albums of old holidays, and a huge box of photos in the pending/holding-queue! (this will mean nothing to anyone under 30, who may never have owned a physical photograph 😀 ). I also have copious amounts of pen-drives, hard-drives and clouds of other holiday photos, which rarely get an outing. So while we were away…travelling about, having a wicked time, taking snaps I was trying to think of a better way to create a holiday album Continue reading My Indian Advizture
I’m out in Berlin at the Exasol Xperience 2016 customer/partner event – good fun, interesting people, great product announcements from Exasol on version 6 and beyond… but since they announced us (Atheon Analytics) as winners of their Smartest Solution partner award, everyone wants to know what the Exasol in my Pocket device is. So let me explain…
As analysts our job is to analyse and compare data. Our visualisations need be aesthetically pleasing, easy to gain insight, and inviting for discovery. ‘Brushing’ is a great technique for comparisons and meets those needs.
It cropped up again last week; the dreaded statement from a BI professional
We must have a single version of the truth…
Anyone working in IT / BI / decision support / enterprise reporting / analytics etc. for more than a couple of months will have heard this, and for those of us working in the field for 20+ years we may wince slightly and wish that we had a pound for every time…
Continue reading Chasing rainbows
The ‘Granularity’ (or ‘Grain’) of the data is the most important thing I consider for any data analysis. When I get a new data-set, my first question What is the Granularity? When designing a new (Tableau) visual model, my first consideration What Granularity do I need? When calculating a measure (or KPI), my first questions: What is the Granularity? and What Granularity do I need?
I’d go as far as saying “Understanding the Grain of your data is 99% of the solution”… Continue reading The Importance of Granularity (…to Blend or not to Blend?)
One of the most common requests from my clients is for Actionable Insight; a desire to receive simple, understandable output from analytical activity which provides a clear indication for what they should do. As a request it’s entirely understandable, reasonable and a great focus for the majority of analysis; after all, analysis is most valuable when it directs action and results in improvement. There are, however, two clear cases when the desire for Actionable Insight oversteps the mark and misses the point:
Continue reading In praise of *unactionable* insight
Much of my visual analysis is performed to help large companies – usually retailers and their suppliers – to better understand a perplexing problem or opportunity in their organisation. How can we reduce waste in our stores? Which promotions drive the desired behaviour in customers and why? What effect does non-delivery at depot have on availability in store? What’s the optimum product range for our biscuits category? etc.
As the title suggests, this nifty trick has the dual purpose of allowing you to trigger sheet swaps using Dashboard Actions and, when two data sources contain different levels of Granularity, it lets you analyse at both levels (the Granularity of the Primary and Secondary data source). This is the ‘illusion of a Full Outer Join’…All seems a little cryptic and techie. Let’s run through an example…
The Data Animators 