Qlik Sense

Build and use Qlik load script functions

alex@techbuilders — Thu, 15 Feb 2018 21:20:10 +0000

Build and use Qlik load script functions alex@techbuilders Thu, 02/15/2018 - 21:20

Based on the fact you're reading this, it's assumed you've graduated from the sum(Amount) stage and waltz through Set Analysis with your eyes closed. You have earned your Qlik developer stripes and seek the extra-black belt to show off around the water cooler. When joining the daily calls, you're starting to hear more and more 'expert' or 'ninja' as a catch-all descriptor for your Qlik skills. If this isn't you, you're going to have a bad time.

All joking aside, the concepts we talk about in this article are about as simplistic as it gets to drive home the functionality. As a beginner, any deviation from the examples given may cause you to question career paths and how long you can stay sane. However, this seldom used feature can be used to expand the capabilities of regular expressions, standardize calculations across applications, and accelerate Qlik development. When used effectively, the limits of these functions are generally the developers creativity. Let's begin!

Let vs Set

Key concept number one when setting a variable in the load script is choosing which identifier to use.

LET evaluates the expression and keeps the result as the variable's value. LET is often used when 'peek'ing at values in a table or doing something with numbers.

SET assigns the value (or expression) as it is without computing. Usually developers believe that using SET is not actually evaluating the formula and just assigning the value of the variable as a string. While it's understandable to think this way, it's not entirely correct. SET still evaluates the expression, but if there are no dollar-sign expansions, then it just returns the string without computing it, which is different from explicitly setting the variable as a string.

Dollar-sign expansion and SET vs LET you have likely heard before and used independently of each other, however the dollar-sign expansion using SET as the identifier together is the keystone of how these load script functions work. We only use SET for these load script functions. Let's take a look at our first example.

SET doeasymath = $1 * $2;

Before we move to the fun stuff you can do with this, let's first see how it works. The $1 and $2 are the functions parameters that get evaluated first before the variable is assigned. Each number reflects the position of the parameter that's passed to it when the function is called. $1 is the first parameter and $2 corresponds to the second. In Qlik Sense, we have created a table and our first measure is

$(doeasymath(rowno(),3))

Parameter $1 = the row number

Parameter $2 = 3

For each row in the table, the row is first multiplied by 3 and then the variable is returned back to the front end. The end result is;

You can call this function multiple times in your dashboard and the result is only associated to the parameters you input. That means that the results are not global and defined on a per chart object basis. You could not (easily) reference the result of one object using these functions to be used in another object using load script functions.

You're not restricted to only using this in the front end, you can call the function in the load script as well.

DemoRows:
Load
RecNo() as [Row],
$(doeasymath(RecNo(),10)) as [Big Numbers]
AutoGenerate(5);

A typical use case for utilizing the function in a table load is when formatting dates or long winded 'if' statements. Any heavily repeated formula is a good candidate for using this method.

Chaining Load Script Functions

What we have spoken to previously is pretty straight forward. Where these functions get interesting is when you start chaining them together. What that means is that the result of one load script function is used in another load script function.

SET doeasymath = $1 * $2;
SET okhardmath = $1 * $(doeasymath);

$(okhardmath(4,RowNo()))

The first parameter (4) and the second parameter (RowNo()) are passed to doeasymath first and the result of that is then used in okhardmath. okhardmath uses the first parameter (4) and multiplies it against the result of doeasymath.

So this is cool but when would someone actually use this? While the example above may not be valuable in the real world, complex formulas should be broken out into separate smaller functions (as much as possible without being a burden). When complex formulas are broken out and compartmentalized, it makes life easier when debugging or making edits. Smaller functions may also have use in other formulas which reduces having to maintain and rewrite code.

How many times do you have to repeat yourself

A central repository where all variables, calculations, and code are stored and distributed amongst applications is a bit of a fantasty, but definitely the goal. Many times this strategy is an afterthought and it becomes an act of congress to dissect all current applications and pull out variables and calculations that could be used across Qlik. During this process, it's often found that code is repeated and duplicate procedures and processes are happening across the organization. This effort usually spawns a much larger 'call to efficiency' and restructuring of loading and using data. If this type of effort is outside of the scope and timeline, mini-efforts can be made in the interim.

The first step is to create a folder in a shared folder repository where all Qlik applications can pull from. Create a 'formulas.qvs' file where all of your variables, functions, and reproduced code will reside. The formulas.qvs file is then included in the load scripts of Qlik applications (as required). This file is where the standardization magic will reside. Enforcing developers to use this file and become familiar with the how to utilize it and variables contained within is pivotal.

In the Qlik Sense load script, a folder connection must be established to the .qvs path and your import will look like so

$(Must_Include=LIB://IncludePath/formulas.qvs);

After importing, your 'okhardmath' variables will be available to use. Due to the folder connection requirement in Qlik Sense, the syntax for importing the .qvs in QlikView will be slightly different - just a note to keep in mind.

Taking this a step further, the .qvs file can then be used in version control solutions like Git so rolling back to a previous state is incredibly simple.

Get your feet wet

We've put together a POC using the example scripts above. This application and it's contents can be found on our github page at https://github.com/techbui1ders/Qlik-LoadScriptFunctions . All code is free to use and modify, we would love to hear any feedback or questions you guys may have. We've used load script functions in a few of our other blog posts and applications (https://github.com/techbui1ders/QlikSense-LicenseAnalyst as an example) and will continue to push the limits of it's usefulness and flexibility. Another example of load script functions coming soon is our ColorPal script (check our github page) which makes branding and coloring your applications amazingly easy.

When it comes to load script functions, understanding the fundamentals, practicing, and testing is the only way to earn that extra-black belt. We hope this short foray has sparked the creative juices and optimizes your development workflow.

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Making Sense of Qliks new pricing strategy

alex@techbuilders — Wed, 15 Feb 2017 03:46:56 +0000

Making Sense of Qliks new pricing strategy alex@techbuilders Wed, 02/15/2017 - 03:46

Navigating software licensing can be an incredibly complex, humbling, and frustrating ordeal (I'm looking at you Microsoft) especially when trying to compare across vendors. You don't want to get too 'involved' just to find out they don't have certain features power users need or they are not delivering on their product strategy. While you may receive better support and pricing, going with a smaller vendor carries the risk of holding the vaporware that was once the most innovative product on the market. Thankfully, business intelligence is a very competitive space to operate in and many of the large BI vendors offer similar pricing structures, except for Qlik -until now.

What's Changing for Who?

Consistent with Qlik's long term vision, they continue to treat QlikView as the red-headed stepchild. The pricing changes only apply to Qlik Sense customers, QlikView users will not get to take part in any of the changes and should expect to see business as usual. The main takeaways to the pricing changes are below;

Introduction of the new Professional and Analyzer user model for Qlik Sense® Enterprise, available for both subscription and perpetual licensing.
New packaging for Qlik Sense Enterprise will bundle the capabilities of the following products into the user price for Qlik Sense Enterprise:
- Qlik Qlik GeoAnalytics^® base
- Qlik Web Connectors^®
- Qlik DataMarket^® Essentials
- Test & Dev Servers included (Subscription only)

New pricing for Qlik Sense^® Cloud Business
Qlik GeoAnalytics perpetual and subscription offerings are now the same
Updated discount framework and tiers for perpetual and subscription
Consumption based pricing (coming soon!)

What does it mean?

There are four material changes to understand, one not being so obvious. First, let's tackle the subscription vs perpetual vs consumption piece of the puzzle.

Perpetual is the choice if you plan on staying with Qlik Sense for the foreseeable future and have the budget to take the initial hit. Overtime, the total cost of ownership will be very cheap compared to other major vendors and pricing models.

Subscription is a recurring payment that will result in a total ownership cost being higher than perpetual for long term projects, but ideal for those without the healthy starting budgets. This model spreads the cost over the years as opposed to the large first year obligation. Customers can also scale up and down as their needs change with savings realized earlier than the perpetual method.

Consumption is a 'pay only for what you use' type model which works well if value can be tied directly to consumption. It's a double sided sward that's great when usage is low and value is high (healthcare research?!) and painful when usage is high with little tangible value derived in the immediate term.

The second main change to the pricing is a Professional and Analyzer designation. This means the customer gets to determine who the consumers of the dashboards are and who are the developers or power users. The Analyzer license is generally about 57% cheaper than the Professional license. A user can start out on the cheaper Analyzer license, and then migrate to the Professional license as they become more familiar and needs increase. Also, the Analyzer license inherently applies restrictions as opposed to the administrator applying them, which makes life easy. In a scenario where developers are deploying reports to a lot of non-technical folk who have no need for self-service, the Analyzer license is a great way to save money.

To add more complexity, the third material change is tiered pricing. Tiered pricing means that regardless of designation (Professional/Analyzer), the customer can accrue discounts based on the the number of licenses obtained. For the Subscription based model, the discounts are based on total licenses purchased in aggregate. For Perpetual, the discounts are per transaction.

For example, if the client has 100 licenses and is purchasing an additional 200 perpetual licenses they would get a 0% discount for the first 50, 5% on 51-100, and 10% on 101-250. This equates to a discount around 7% or so over a non-tiered based method.

The fourth and final material change is not so obvious. Qlik no longer requires purchasing licenses in packs of 5. This move towards Professional and Analyzer designation only requires 1 Professional license to begin, and any implementation is going to have a Qlik Sense admin so this plays well for the consumer. Additional licenses can be purchased one at a time, catering to the consumer as needs change - this is a big benefit! One downside detail is that starter packs are no longer available, but all things considered that's a non-issue considering 1 Professional license is still less than the cost of 1 starter pack priced license (woot!)

Great, I'm still confused

In general, your Qlik partner or Sales Rep will be able to help you with your unique situation.

If you're just starting out, I would break the changes down into three steps.

Determine Perpetual, Subscription, or Consumption based on typical user base, long term goals, and funding.
Determine the number of developers you have to get a sense of how many Professional licenses you'll need immediately, then think about number of users you'll need in the testing process and number of power users you'll roll out to first (if different from the UAT testers). You want to purchase just enough to be productive, but not so many they are sitting idle.
Take advantage of Tiered pricing and work with your partner to meet your budget requirements. As a partner, there are a few levers we can pull to make sure the client is a happy camper - utilize your influence and partner relationships.

We have built a Qlik Sense dashboard that should help paint broad strokes from a pricing perspective. Choose the License Model type, number of Professional and Analyzer licenses, the project timeframe and a sample plot of the annual fees will display with a few other key metrics. The pricing used is based on the highest dollar amount per license type, as mentioned in the third bullet there are other levers that can be pulled. Consumption based pricing is not as straight forward, and thus removed from the analysis.

Often times, we have customers interested in the price per user per month. This application is focused on deriving that value and showing the weighted monthly cost per user depending on how long your time horizon is. Generally speaking, the longer you use your Qlik Sense assets, the cheaper it is per user per month.

The enormous benefit of Qlik Sense is that users can have access to an unlimited amount of dashboards without a marginal increase in cost.

An example, using our dashboard for 5 Professional and 100 Analyzer Users, the effective cost in a perpetual model is $26/month after 5 years for access to unlimited dashboards... that.is.AMAZING!

This dashboard can be found on our github page at https://github.com/techbui1ders/QlikSense-LicenseAnalyst . Take a look and let us know if you have any questions or feedback!

Please note this is using USA based pricing as of 2/2018 and is not to be used as a basis of a quote. Please reach out to your partner or rep for an accurate quote.

Keeping your enemies closer

The payment structure and user segmentation was a hurdle that was figured out early by Tableau, and many other vendors followed suit. Qlik has generally taken the position of distancing themselves from competitors by thinking independently. In this case, imitation is just what Qlik needed to keep current customers happy and drive adoption and usage with new customers.

Wrapping it up

Software licensing continues to be complex to the point of giving up, and Qlik is really no different. While annoying to juggle, these changes are a major step forward for Qlik and we look forward to seeing how this new pricing ultimately plays out. The features coming in the 2018 releases should continue to position Qlik Sense as a top player in the business intelligence field at fantastic price points.

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Margie (not verified)
Making Sense of Qliks new pricing strategy | TechBuilders

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Tue, 05/01/2018 - 13:34

Stefan (not verified)
Making Sense of Qliks new pricing strategy | TechBuilders

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I'll go ahead and bookmark your site to come back in the future.
All the best

Sat, 06/02/2018 - 04:50

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Qlik Sense

Build and use Qlik load script functions

Let vs Set

Chaining Load Script Functions

How many times do you have to repeat yourself

Get your feet wet

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Making Sense of Qliks new pricing strategy

What's Changing for Who?

What does it mean?

Great, I'm still confused

Keeping your enemies closer

Wrapping it up

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