Table of Contents for
Using the Concat() function to display a string of field values as a dimension
Using the Concat() function to display a string of field values as a dimension
by Ferran Garcia Pagans, Neeraj Kharpate, Philip Hand, James Richardson, Dr. Henric
Qlik Sense: Advanced Data Visualization for Your Organization
- Qlik Sense: Advanced Data Visualization for Your Organization
- Table of Contents
- Qlik Sense: Advanced Data Visualization for Your Organization
- Credits
- Preface
- 1. Module 1
- 1. Qlik Sense® and Data Discovery
- 2. Overview of a Qlik Sense® Application's Life Cycle
- 3. Empowering Next Generation Data Discovery Consumers
- 4. Contributing to Data Discovery
- 5. Authoring Engaging Applications
- 6. Building Qlik Sense® Data Models
- 7. Qlik Sense® Apps in the Cloud
- 8. Extending the Qlik® Analytic Platform
- 9. Administering Qlik Sense®
- 10. Sales Discovery
- 11. Human Resource Discovery
- 12. Travel Expense Discovery
- 13. Demographic Data Discovery
- 2. Module 2
- 1. Getting Started with the Data
- Introduction
- Extracting data from databases and data files
- Extracting data from Web Files
- Activating the Legacy Mode in Qlik Sense® desktop
- Extracting data from custom databases
- Invoking help while in the data load editor or the expression editor
- Previewing data in the Data model viewer
- Creating a Master Library from the Data model viewer
- Using a Master Library in the Edit mode
- 2. Visualizations
- Introduction
- Creating Snapshots
- Creating and adding content to a story
- Adding embedded sheets to the story
- Highlighting the performance measure in a bar chart
- Associating persistent colors to field values
- Using the ColorMix1 function
- Composition
- Relationships
- Comparison
- Distribution
- Structuring visualizations
- 3. Scripting
- Introduction
- Structuring the script
- Efficiently debugging the script
- Packaging the code in script files
- How to use sub routines in Qlik Sense®
- Optimizing the UI calculation speed
- Optimizing the reload time of the application
- Using a For Each loop to load data from multiple files
- Using the Concat function to store multiple field values in a single cell
- 4. Managing Apps and User Interface
- Introduction
- Publishing a Qlik Sense® application created in Qlik Sense® desktop
- Creating private, approved, and community sheets
- Publishing a Qlik Sense® application to Qlik Sense® cloud
- Creating geo maps in Qlik Sense®
- Reference lines in Sales versus Target gauge chart
- Effectively using the KPI object in Qlik Sense®
- Creating Tree Maps
- Creating dimensionless bar charts in Qlik Sense®
- Adding Reference Lines to trendline charts
- Creating text and images
- Applying limitations to charts
- Adding thumbnails – a clear environment
- Navigating many data points in a scatter chart
- 5. Useful Functions
- Introduction
- Using an extended interval match to handle Slowly Changing Dimensions
- Using the Previous() function to identify the latest record for a dimensional value
- Using the NetworkDays() function to calculate the working days in a calendar month
- Using the Concat() function to display a string of field values as a dimension
- Using the Minstring() function to calculate the age of the oldest case in a queue
- Using the Rangesum() function to plot cumulative figures in trendline charts
- Using the Fractile() function to generate quartiles
- Using the FirstSortedValue() function to identify the median in a quartile range
- Using the Declare and Derive functions to generate Calendar fields
- Setting up a moving annual total figure
- Using the For Each loop to extract files from a folder
- Using the Peek() function to create a currency Exchange Rate Calendar
- Using the Peek() function to create a Trial Balance sheet
- 6. Set Analysis
- Introduction
- Cracking the syntax for Set Analysis
- Using flags in Set Analysis
- Using the = sign with variables in Set Analysis
- Point in time using Set Analysis
- Using comparison sets in Set Analysis
- Using embedded functions in Set Analysis
- Creating a multi-measure expression in Set Analysis
- Using search strings inside a set modifier
- Capturing a list of field values using a concat() function in Set Analysis
- Using the element functions P() and E() in Set Analysis
- 7. Extensions in Qlik Sense®
- 8. What's New in Version 2.1.1?
- Introduction
- Using the visual exploration capability in Qlik Sense® 2.1.1
- Defining variables in Qlik Sense®
- Exporting stories to MS PowerPoint
- Using the Qlik Dev Hub in Qlik Sense® 2.1.1
- Using Extension editor in Qlik Dev Hub
- Using Qlik Dev Hub to generate mashups
- Embedding Qlik Sense® application on a website using a single configurator
- Using the Qlik DataMarket
- Creating dynamic charts in Qlik Sense®
- Using Smart Search
- Using smart data load profiling
- Conclusion
- A. Appendix
- 1. Getting Started with the Data
- 3. Module 3
- 1. Getting Ready with Predictive Analytics
- 2. Preparing Your Data
- 3. Exploring and Understanding Your Data
- 4. Creating Your First Qlik Sense Application
- 5. Clustering and Other Unsupervised Learning Methods
- 6. Decision Trees and Other Supervised Learning Methods
- 7. Model Evaluation
- 8. Visualizations, Data Applications, Dashboards, and Data Storytelling
- 9. Developing a Complete Application
- A. Bibliography
- Index
A line-level table is normally the most granular data in a Data model. For example, consider an Order Line table. The orders for each customer are stored one row per product line, and we have corresponding costs for each product on each line. When we generate a Table report for such data, we will have a separate line for each product which in itself is not wrong. But recently a customer asked me to initiate an export for the Table report in such a way that all the products for a particular order are contained in a single cell and the sales column should show the aggregated figure for all the products under OrderID. To tackle this requirement, I created a calculated dimension using the Concat function. The process is explained in the following recipe.
- Create a new Qlik Sense application.
- Add the following
INLINEtable that contains theOrder Linetable details:Orders: LOAD * INLINE [ Customer,OrderID,Product,Cost 1,201,Chain,20 1,201,Seat,40 1,201,Mudguard,50 2,202,Gloves,15 2,202,Basket,60 3,203,Helmet,70 ]; - Load the data and save the file. Open App overview by clicking on the Navigation dropdown
in the top-left corner.
- Create a new sheet.
- Drag the Table object from the left-hand side Assets panel on to the sheet. Name it
Sales by Order. - Add OrderID and Customer as dimensions.
- Add the following as a third, calculated dimension and label it
Products:=AGGR(Concat(DISTINCT Product,','),OrderID)
- Add the following expression as the measure. Label it
Total Sales:Sum(Cost)
- Click on Save and click on
. - The resulting table on the screen will look like this:
- As you can see, all the products for a particular
OrderIDvalue are stringed together in a single cell and the sales figures are the aggregated figures for eachOrderIDvalue.
The Concat() function gives us the aggregated string concatenation of all the product values separated by the , delimiter. The Concat() function is an aggregation function and hence needs to be used with AGGR in order to be used as a dimension. For the sake of our dimension, the products are grouped by the OrderID.
The same functionality could have been achieved by defining products within a calculation in a measure as follows:
Concat(DISTINCT Product,',')
But by doing so, we won't be able to select the products for a particular OrderID value inside the table.
When we use the calculated dimension, we get the advantage of selecting all the products for the OrderID value in a single go by selecting a cell in the products column.
-
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click here login for view all page.