QlikSense Class 9 - Tips and Tricks when developing | Paul Scotchford | Skillshare

QlikSense Class 9 - Tips and Tricks when developing

Paul Scotchford, Business Intelligence and Analytics developer

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15 Videos (2h 39m)
    • Lecture 59 Creating bookmarks to remember where part of a story is

    • Lecture 60 How to create a story

    • Lecture 61 Share your story with others

    • Lecture 62 Export data from your App

    • Lecture 63 Connect to a SQL Server database to extract data

    • Lecture 64 Extract data from a web page

    • Lecture 65 Use the Peek() function to look inside the data model

    • Lecture 66 Create a raw data calendar via scripting

    • Lecture 67 Integrating d3 visualisations

    • Lecture 68 Add a word cloud to your App sheet

    • Lecture 69 Linking to other sheets and URL references

    • Lecture 70 Introduction to data governance

    • Lecture 71 Implementing data governance

    • Lecture 72 Solution to the Inventory data problem

    • Lecture 73 How to create a mashup


About This Class

I recommend that you complete QlikSense Class 8 - Analyse Profit and Loss before taking this class.

Our start-up demands more value by enhancing the data visualizations and allow us to share our Apps with others.

These lectures will teach you more ways to enhance the value of your data visualisations and the user experience, you will learn how to ...

  1. Create bookmarks
  2. Create stories
  3. Share your apps with others (e.g via the Cloud)
  4. Export data 
  5. Connect to other data sources and scrape web sites for data
  6. d3 and Word Cloud integration
  7. And lots more...






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Paul Scotchford

Business Intelligence and Analytics developer

I have over 12 years experience as a Business Intelligence and Analytics developer specialising in both the Microsoft and Qlik technology environment.

Since 2012 I have been developing QlikView and in late 2014 I discovered QlikSense, my QlikView skills were immediately transferable to QlikSense too.

I have also been developing with SQL since the late 90's and have extensive experience in data extraction, modelling and analytics directly from ERP and Data Warehouse structures.

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