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Online – Thursday Trainings at Three
17 september 2020 : 16:00 - 18:00 CEST
Want to learn how to harness the power of your data, but are short on time? If you’re new to Tableau and Alteryx then our speedy 2-hour hands-on sessions are for you (1.5 hour training, and up to 30 mins at the end for questions!).
We are running weekly introductory sessions where we will help you get to grips with data in Tableau Desktop, Tableau Prep, Tableau Server and Web Edit, and Alteryx Designer. These sessions will run concurrently, so come along to a different session each week to supercharge your data skills!
Our sessions are hands-on, so make sure you are ready-to-go by downloading a copy of the software for the session on your laptop (you can download trial versions of Tableau Desktop, Tableau Prep and Alteryx Designer. We will show you our Demo Tableau Server through the browser for our Server and Web Edit, and Explorer Licence trainings).
> Tableau Prep Builder (Beginner) – In this session you’ll get acquainted with the general interface of Tableau Prep Builder, how you can perform joins, data cleansing activities, and simple transformation tasks.
> Tableau Advanced Charts (Advanced) – In this session we’ll show you how to build a handful of specific charts that go far and beyond the ones available in the ‘Show Me’ menu. Examples of the charts we may cover are dual axis combination charts, small multiple charts, and dynamically updating charts using features like set and parameter actions.
> Tableau Table Calculations (Advanced) – Need a little more oomph to answer tougher analytical questions like ‘Percent of total within branches’ or ‘Year-to-date running sum of growth’? Then you need Table Calculations! This session will cover the basics of what table calculations are, their syntax, and ways that you can use them to do more with your data (such as year over year growth and window calculations).
> Alteryx Designer (Beginner) – In this session we will show you an overview of Alteryx Designer’s capabilities – how you can drag and drop your way through data cleansing, aggregation and preparation processes that are repeatable and shareable with your colleagues.
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