Let's create the following variable:

If everything works correctly, then the detailed bullet graph will appear in front of a transparent, gray background. When we want to close the detail and go back to the general view of our customer fact sheet, we click on the grayed-out background. We could also create a Close button, but it is now common UX practice to close a pop-up window by clicking anywhere else on the screen.

As only one pop-up window will appear at any one time, we use one variable to determine which popup is displayed. One variable is obviously easier to maintain than having one for each corresponding popup. However, if we want to give the users the ability to open as many detailed charts as they like, then we would have to create a control variable for each popup.

Let's create the following variables:

1

=pick(match('|' & GetFieldSelections(_SortMetric,'|') & '|'
, '|Net Sales|' , '|Gross Profit|'
, '|Volume|'),'sum({$<_ActualFlag={1}>} 
     [Net Sales USD])','sum({$<_ActualFlag={1}>} 
     [Gross Profit USD])','sum({$<_ActualFlag={1}>} [Quantity])') 

=pick(match('|' & GetFieldSelections(_ColorMetric,'|') & '|'
, '|Net Sales|' , '|Gross Profit|'
, '|Volume|'),'sum({$<_ActualFlag={1}>} 
     [Net Sales USD])','sum({$<_ActualFlag={1}>} 
     [Gross Profit USD])','sum({$<_ActualFlag={1}>} [Quantity])')

Dsc

=if(vAscDsc='Asc',1,-1) 

Diverging

10

The user now has a way to create custom visualizations using only a few variables. We can continue to create more variables to control the property options defined by an expression field or preconfigure certain properties that can only be modified in the properties windows. However, the result of the previous exercise allows users to create the best possible charts using the fewest variables.

The cyclical dimensions are also more user friendly as they are located next to their axis or legend. We create three of them because graphs may use a maximum of three dimensions. Each should be sorted each dimension alphabetically or numerically by default, but we can easily select an expression by which to sort them in either ascending or descending order. We've also added a variable to limit the number of dimension values as there are often more than those that can fit in a graph at one time.

The metrics are divided by left and right axis as it is common practice to visualize two metrics that do not share the same scale. We also include the ability to add a heat map to the custom visualization to make them more insightful. The heat map can either be sequential, if the metric can only be positive, or it can be diverging if the metric can also be negative.

Although it seems like we use few variables in comparison to the hundreds that exist in the chart properties windows, the users can create a wide variety of different visualizations. Users who want the ability to create even more personalized charts should start working with Qlik Sense, which we will review in Chapter 11, Mastering Qlik Sense Data Visualization.

Contrary to what we may think, the currency used to analyze data does not depend on a user's country. Although some analysis may be done using the local currency, it is common to analyze data using one of the reserve currencies, such as the US dollar or the Euro. For this reason, we often add a currency filter to the user interface.

The values of the currency field correspond to the names given to the monetary amount fields in the data model, such as [Net Sales LC] and [Net Sales USD]. In this way, we can easily make our application multicurrency using the following code:

sum({$<_ActualFlag={1}>} [Net Sales $(=Currency)]) 

In a similar way to how we make our application multicurrency, we also make it multilingual. We create a table with one field called Language that contains values that correspond to the field names in another table that contain the texts belonging to each language:

Then, in every multilingual label, we use the following code to calculate a label. We use a descriptive ID, like Sales, for our labels so that we can identify expressions and objects without having to manually look up numerical IDs in a table:

=only({$<LabelID={'Sales'}>} $(=Language)) 

Along with the labels, we also choose which descriptive field to use for list boxes and dimensions. For example, we have two fields in our Customer table that describes customer groups. [Customer Group ENG] contains English descriptions and [Customer Group ESP] contains Spanish descriptions. We use the following code as an expression in our list box or as a calculated dimension:

=[Customer Group $(=Language)] 

Although we give the user the option to select any language, the application should open in the user's preferred language. One way to do this is to distribute a copy of the QlikView file with

the language prefiltered by the QlikView Publisher. Another way is to use section access to reduce a field that we use to select the preferred language upon opening the QlikView document.

Date and number formats depend on the country and it should be automatically selected when opening the QlikView document. We use a set of variables that return the preferred formats based on a user's region along with the formatting functions, num() and date() in order to dynamically format the data.

We can define a user's region using Section Access. The following code is an example of how the dynamically formatted expressions will look:

date([Date],$(vRegional_DateFormat))
num(sum(Quantity),$(vRegional_NumberFormat_FixedDecimal)
    ,$(vRegional_Decimal),$(vRegional_Thousand))