Advanced Set Analysis - MLT Vacations

8/7/2019 Advanced Set Analysis - MLT Vacations

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Advanced Set AnalysisMLT Vacations


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Problem

Our goal here is to analyze specific flight patterns and compare thecurrent numbers to the previous year.

We will define our criteria using QlikView selections. Selections work wellin this situation, because they are easy to use within Set Analysis andallow our users the flexibilit to modif the criteria on-the-fl .

Due to the structure of our data, simply making the selections will not beenough to get us the answers we are looking for. Our datasetcontains multiple records for each booking, one record for each

activity the customer will do during their trip. Bookings can alsoinclude multiple customers, so well have to verify that each booking

and customer we include matches the criteria.

Since the specific flight pattern we are looking for will only match onerecord, well need to include any customer where at least one recordmatches our selected criteria.


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Data

Our data is structured as follows. We want to include any customer thattakes a flight from MSP to CUN. We must be sure to include allrevenue associated with that customer, not just the revenueassociated with that specific flight.

oo ng us omer ype r g es en s r ev

12345 A A MSP CUN 1 100

12345 A H 0 0

12345 B A MSP ATL 1 75

12345 B A ATL CUN 0 75

12345 B H 0 0

67890 A A MSP CUN 1 10067890 B A MSP CUN 1 100

67890 A H 0 0

67890 B H 0 0

24680 A A FAR MSP 1 75

24680 A A MSP CUN 0 100

24680 A H 0 0


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Now lets see what happens when we make some selections. We are lookingat flights from MSP to CUN.

Booking Customer Type Orig Dest Clients Air Rev

12345 A A MSP CUN 1 100

12345 A H 0 0

12345 B A MSP ATL 1 75

12345 B A ATL CUN 0 75

12345 B H 0 0

67890 A A MSP CUN 1 100

67890 B A MSP CUN 1 100

67890 A H 0 0

67890 B H 0 0

24680 A A FAR MSP 1 75

24680 A A MSP CUN 0 100

24680 A H 0 0


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Selecting our Origin includes any flight originating in MSP


12345 A A MSP CUN 1 100

12345 A H 0 0

12345 B A MSP ATL 1 75

12345 B A ATL CUN 0 75

12345 B H 0 0

67890 A A MSP CUN 1 100

67890 B A MSP CUN 1 100

67890 A H 0 0

67890 B H 0 0

24680 A A FAR MSP 1 75

24680 A A MSP CUN 0 100

24680 A H 0 0


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We only want customers taking a flight from MSP to CUN, so this firstselection included a record we did not want.


12345 A A MSP CUN 1 100

12345 A H 0 0

12345 B A MSP ATL 1 75

12345 B A ATL CUN 0 75

12345 B H 0 0

67890 A A MSP CUN 1 100

67890 B A MSP CUN 1 100

67890 A H 0 0

67890 B H 0 0

24680 A A FAR MSP 1 75

24680 A A MSP CUN 0 100

24680 A H 0 0


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Making our selection on the Destination eliminates the unwanted records.

Selecting both Origin & Destination requires that both values are present in asingle record, which is what we want for this exercise.


12345 A A MSP CUN 1 100

12345 A H 0 0

12345 B A MSP ATL 1 7512345 B A ATL CUN 0 75

12345 B H 0 0

67890 A A MSP CUN 1 100

67890 B A MSP CUN 1 100

67890 A H 0 0

67890 B H 0 0

24680 A A FAR MSP 1 75

24680 A A MSP CUN 0 100

24680 A H 0 0


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As you can see in the circled cells, including only the selected records willresult in us not counting all passengers and missing out on some revenue.


12345 A A MSP CUN 1 100

12345 A H 0 0


12345 B H 0 0

67890 A A MSP CUN 1 100

67890 B A MSP CUN 1 100

67890 A H 0 0

67890 B H 0 0

24680 A A FAR MSP 1 75

24680 A A MSP CUN 0 100

24680 A H 0 0


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Well use Set Analysis to select every record for any customer who meets theselected criteria.


12345 A A MSP CUN 1 100

12345 A H 0 0


12345 B H 0 0

67890 A A MSP CUN 1 100

67890 B A MSP CUN 1 100

67890 A H 0 0

67890 B H 0 0

24680 A A FAR MSP 1 75

24680 A A MSP CUN 0 100

24680 A H 0 0


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The first thing we will do is build our expression in an intermediate tableusing the natural dimensions.

Building your Expression in an intermediate table will be:

Implementation

Easier to troubleshoot

More accurate

Used directly in our final expression

In this example, our natural dimensions will be Booking and CustomerID. Since this level of analysis is common for us, our dataset containsone field that is a concatenation of both fields.


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Set Analysis structure and terms

Here is the basic syntax for a Set Analysis expression and some terms Iwill use throughout the presentation.

Sum({} FACT)

Set Expression: {}

Set Modifier:

Element Set: {'VALUE'}


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Bk Cust Bk T e Le Ori Le Dest Bk Clients AirRev

Building Our Revenue Expression

We will start with a basic Sum function:

Sum(AirRev)

12345A A MSP CUN 1 100

12345A H 0 0

12345B A MSP ATL 1 75

12345B A ATL CUN 0 75

12345B H 0 0

67890A A MSP CUN 1 100

67890B A MSP CUN 1 100

67890A H 0 0

67890B H 0 0

24680A A FAR MSP 1 75

24680A A MSP CUN 0 100

24680A H 0 0


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Using Set Analysis and the 1 modifier, we will ignore all selections:

Sum({1} AirRev)

12345A A MSP CUN 1 100

12345A H 0 0

12345B A MSP ATL 1 75

12345B A ATL CUN 0 75

12345B H 0 0

67890A A MSP CUN 1 100

67890B A MSP CUN 1 100

67890A H 0 0

67890B H 0 0

24680A A FAR MSP 1 75

24680A A MSP CUN 0 100

24680A H 0 0


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The P() Function [and E()]

We will bring our selections back in to play by utilizing the P() function

Set Modifiers with Implicit Value Definitions

n y ava a e n et na ys s as ement ets

Represents the Element Set of Possible values and Excluded Valuesrespectively

Can include a Set Expression

Much faster than alternative methods, such as Concat

Format:

{}


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Using P() we will select all possible BkgCust values

Sum({1} AirRev)

12345A A MSP CUN 1 100

12345A H 0 0

12345B A MSP ATL 1 75

12345B A ATL CUN 0 75

12345B H 0 0

67890A A MSP CUN 1 100

67890B A MSP CUN 1 100

67890A H 0 067890B H 0 0

24680A A FAR MSP 1 75

24680A A MSP CUN 0 100

24680A H 0 0


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Using P() we will select all possible BkgCust values

Sum({1} AirRev)

12345A A MSP CUN 1 100

12345A H 0 0

12345B A MSP ATL 1 75

12345B A ATL CUN 0 75

12345B H 0 0

67890A A MSP CUN 1 100

67890B A MSP CUN 1 100

67890A H 0 067890B H 0 0

24680A A FAR MSP 1 75

24680A A MSP CUN 0 100

24680A H 0 0


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Variables to simplify Set Analysis expressions

Variables can be used in place of expressions saving you fromrepeatedly typing the same expression which can lead to errors

Sum({1} AirRev)

Set a variable to represent your Set Expression

vSA= {1}

We can then simplify our expression using the variable

Sum($(vSA) AirRev)


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Adding a Previous Year Expression

We add a Set Expression to the P() function to define the date span

Sum({1} AirRev)


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Adding a Previous Year Expression

We add a Set Expression to the P() function to define the date span

Sum({1} AirRev)

Define the Element Set as a range

Sum({1} AirRev)

It is a good idea to use valid, pre-defined values when first constructing

the expression


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Defining the Previous Year Span

Our current year span will be defined by a selection, we will use thisselection to define the previous year span

Start with the smallest, selected date

Min(DeptDate)


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Min(DeptDate)

Then modify it for the previous year

AddYears(Min(DeptDate),-1)


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Min(DeptDate)

Then modify it for the previous year

AddYears(Min(DeptDate),-1)

We will use similar logic for the largest valueAddYears(Max(DeptDate),-1)


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Adding the Functions Using Dollar Sign Expansions

We must use Dollar Sign Expansions for our value functions

$(=AddYears(Min(DeptDate),-1))



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If you think back to our expression with pre-defined values, wellkeep the Element Set the same, but replace the dates with ourselection-based functions inside Dollar Sign Expansions

{>= 7/1/2010


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If you think back to our expression with pre-defined values, wellkeep the Element Set the same, but replace the dates with ourselection-based functions inside Dollar Sign Expansions

{>=$(=AddYears(Min(DeptDate),-1))


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Tip: Dollar Sign Expansions in Set Expressions

When building Set Expressions with Dollar Sign Expansions, put yourexpression into a Straight Table, but dont give the expression a label

When the chart is rendered, the label will be your Set Expression withthe Dollar Sign Expansion evaluated

Sum({=$(=AddYears(Min(DeptDate),-1))

}

AirRev)


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Final Expressions

We now have working expressions for our selected date span and for theprevious year. These expressions can be used in tables or charts.Since they are dynamic based on a selection, they can be modifiedby the user on-the-fly

Sum({1} AirRev)

Sum({1


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Final Expressions

We now have working expressions for our selected date span and for theprevious year. These expressions can be used in tables or charts.Since they are dynamic based on a selection, they can be modifiedby the user on-the-fly

Sum($(vSA) AirRev)

Sum($(vSA_LY) AirRev)


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Charting our Expressions

And here are our expressions in action


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Set Analysis Summary

Here are some things to remember as you build your own expressions

Simplify the problem by using an intermediate expression in atable with natural dimensions

When working with dollar sign expansions:

First hardcode a returnable value to verify that your Set

Expression is working Create a chart and enter your expression without a label to

determine what the dollar sign expansion is returning


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Advanced Set Analysis - MLT Vacations