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
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?)
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 