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5 Things to Know about the Tableau 9.1 Web Data Connector

Posted by on Jul 27, 2015

5 Things to Know about the Tableau 9.1 Web Data Connector

If there’s anything the Tableau community is known for it’s adopting new versions fast (even betas) and making the most of new features. Here’s all you need to know about the new Tableau 9.1 Web Data Connector

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Alteryx For Sport – “Find Nearest” (Organising your scouts)

Posted by on Jul 27, 2015

Alteryx For Sport – “Find Nearest” (Organising your scouts)

A lot of focus in the use of data in sport is centred on talent identification, team/player performance or human performance/sport science. However, calling on my 9 years’ experience working within elite football, I can certainly state that this is just a small part of the work that goes on behind the scenes at a football club. This is because researching, planning, implementation and reviewing of strategies and processes takes up a huge amount of time. One aspect of this planning is the arranging of which players to scout, establishing when they are playing and identifying the nearest scout...

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Creating a timetable / Gantt using the DATEDIFF function

Posted by on Jul 23, 2015

It is easy to represent where a project starts or where it ends using Tableau’s Gantt chart. However, when we want to look at the duration of a project it can be quite difficult to create the visualisation. For example, imagine you are creating a timetable for lessons. There will be multiple different lessons within a day, so there will be multiple start times and end times for each lesson. You may be familiar with the DATEDIFF function which calculates the difference, at a given time level, between two time periods. E.g. DATEDIFF(‘minute’,[Start],[Finish]) If we use this...

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Using Alteryx to get data from APIs – Part 2: JSON Parse Tool Output

Posted by on Jul 21, 2015

In a previous blog we went through the process of downloading some data from the website Quandl. Again, if you aren’t aware of this website, do check it out! Previously, the JSON Parse Tool was set up so that the data output values into a single string which gives four columns: Field Name, DownloadHeaders, JSON_Name and JSON_ValueString. If you select “Output values into data type specific fields” the JSON Parse Tool output will have seven columns: Field Name, DownloadHeaders, JSON_Name, JSON_ValueString, JSON_ValueInt, JSON_ValueFloat and JSON_ValueBool. It’s always worth...

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Aggregate Measures = Tableau Hot Sauce

Posted by on Jul 21, 2015

Aggregate Measures = Tableau Hot Sauce

This blog post snowballed in my head from a conversation last night with my colleague Carl Allchin (or to give him his full title: Carl Allchin Data Ninja) based on some work we did yesterday at our Data School, so thanks to Carl and the Data School gang for seeding the idea for something that really needed putting out on the blog. Let’s start with a test, please tell me what Level of Detail (i.e. what each mark represents) in the visualisations below:     Now try again, what does each mark represent: (incidentally this visualisation shows what the UK would look like if we...

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Alteryx For Sport – Reshaping Your Excel Worksheets

Posted by on Jul 20, 2015

Alteryx For Sport – Reshaping Your Excel Worksheets

In the first blog in this series (Joining Excel Worksheets) I touched upon the required structure of a CSV or Excel file to be able to maximize the potential of the data, to analyse the data at its most granular level and for us to visualize our data using Tableau (more information on this here). So what if our data isn’t in the required format, what if we have workbooks upon workbooks that contain cross-tabs? When cross-tab meets Alteryx Reshaping our Excel data is a breeze when using Alteryx, no opening of multiple workbooks, no vlookups and no copy and pasting, just a few drag-and-drop...

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