QlikSense Class 6 - Analyzing On-Line Customer Sales Performance | Paul Scotchford | Skillshare

QlikSense Class 6 - Analyzing On-Line Customer Sales Performance

Paul Scotchford, Business Intelligence and Analytics developer

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10 Videos (1h 59m)
    • Lecture 34 Understanding the new data for the App

      7:49
    • Lecture 35 Create a new Model and merge data files

      17:15
    • Lecture 36 Discretize (Band) data for analysis

      8:07
    • Lecture 37 Resident loads

      11:28
    • Lecture 38 How to do a Lookup()

      11:51
    • Lecture 39 Visualize our discretized (Banded) data

      15:46
    • Lecture 40 Advanced counting using Sum,Aggr() and TOTAL

      14:56
    • Lecture 41 Testing the advanced counting results

      8:02
    • Lecture 42 Lets put all this stuff on a data visualization (Dashboard)

      11:04
    • Lecture 43 Finally we can add maps to our visualization

      12:14

About This Class

I recommend that you complete QlikSense Class 5 - Analyzing Stock Position before taking this class.

Our start-up has online based sales.

These lectures will teach you how to build a On-line customer sales performance analysis App and as we build the app you will also learn how to ...

  1. Work with This Year / Last Year data calculations
  2. Merge data in the model
  3. Create discretised data using the Class() and Flag methods
  4. Create a data island (Disassociated data tables)
  5. Use the Lookup() function to query data
  6. How to count customer registrations using advanced counting functions Aggr(), TOTAL

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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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