Category Archives: Qlik Sense

Catwalk — The Alternative Data Model Viewer

Summary: I introduce “catwalk”, an alternative data model viewer for Qlik Sense from the Qlik oss team.  Don’t like reading?  Go to https://catwalk.core.qlik.com/ and give it a spin. 

I’ve been having a lot of fun with catwalk, a fairly new tool from the Qlik oss team.   I call catwalk an “alternative data model viewer” for Qlik Sense.

I’m going to start by showing a few screenshots and then tell you how to get started using catwalk.  It’s easy to try out.

After selecting an app to view, you’ll get a graphical table & field layout.  In addition to a visual depiction of linkage, you’ll get some rich information about cardinatility, relationships  and some nice explanations of subset ratios.

You can also make field selections and see how those selections impact the other tables.  A nice little tool in the lower right corner lets you build hypercubes (straight tables) on the fly to visualize aggregations.

I’m not going to tour all the features here because the first time you enter catwalk you’ll be offered a walkthrough guide.  I highly recommend you take this brief guide.  You can return to the guide at any time from the … menu in the upper right.  A tip on the guide: When it says “you can do X, try X” it won’t let you continue until you try actually try X.  Clever.

 

So how do you get access to all this goodness?  Go to the github page https://github.com/qlik-oss/catwalk for instructions.  Don’t like reading instructions?  Make sure your QS Desktop is started and go to the hosted version at  https://catwalk.core.qlik.com/.  Have fun.

The connection to your Qlik Sense server is from your local browser. No data is passed to the server hosting catwalk.

A really cool way to invoke catwalk is to set up a bookmark with the javascript shown here https://github.com/qlik-oss/catwalk/tree/master/bookmark.  Click the bookmark while in any app in the hub and you’ll open catwalk on that app.   Simple.

So while catwalk may have been conceived  as a data model explorer for Qlik Core (which has no built-in viewer) it’s just as valuable for Qlik Sense Enterprise or Desktop.

Have fun!

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Understanding and Using Subset Ratio

Summary: If you are familiar with subset ratios in Qlik, you may not find much new in this post. But if you are new to Qlik or are unfamiliar with subset ratios in your data model, please read on. 

When loading data into Qlik and building a new data model, inspecting the Subset Ratio of key fields is an important exercise to ensure data quality.

Subset Ratio is displayed in the Preview Pane (Qlik Sense Data model viewer) or Table Viewer (QlikView) when a key field (field linking two or more tables) is selected.

After clicking a key field, in the Preview pane you will see three important numbers:

Total distinct values:  The count of all distinct values for this field (CustomerId) from all tables (Orders” and “Customers”) in the model.

Present distinct values:  The count of distinct values for this field (CustomerId) in the currently selected table (Customers).

Subset ratio: “Present distinct values” divided by  “Total Distinct Values”.  What percentage of total field values are represented in this table?  In this case, 100% of all CustomerId values in the data model are represented in the Customers table.  This is good. We will typically expect to see 100% Subset ratio in a dimension table.

Let’s take a look at the Subset ratio for the same field in our fact table — the Orders table,

It’s less than 100%.  Our Customer table is our “customer master” and represents all of our potential customers.  Our Orders table represents a limited time period, perhaps 12 months.  Only 44 distinct customers, or 22%,  are represented in the set of Orders we have loaded.

Less than %100 Subset ratio is a normal condition for a Fact table.  If we don’t want to include Customer data for those customers who have no orders, we can filter the Customer load with a “Where Exists(CustomerId)” clause.

So far we’ve seen “normal” subset ratios.  Let’s look at some exceptions.  What does it mean when the dimension table (Customers) has less than 100% subset ratio?

It means we have an order(s) that has no link to a Customer row.  That’s a data quality problem. In the example above we can see that we have 1 missing CustomerId (201 – 200).

Why do we have a missing Customer?  We would have to dig into the data to find out why.  It could be that we have loaded historical orders and “inactive” customers are archived from the Customers table.  It could be that we have some bad data due to a bug.  We have to analyze the data and decide on the best path to remediate.

By the way, what is the specific value(s) of the missing CustomerId?  A simple way to make this determination is to create a table chart with two columns — The key field and a field that has 100% density (every row has a value) from the Customers table.  I’ll use the CustomerName field. Sort the table by CustomerName and the key value in question will show at the bottom of the table with a null value for CustomerName.

What does it mean when the sum of the subset ratios for two tables equals 100%? It means there are no matching values between the two tables.   This can happen for instance when the keys come from two different systems that use slightly different nomenclature.  Perhaps in your ERP all ProductId values start with “P” but in the spreadsheet that someone provided for additional part info the “P” is excluded because none of the humans use the “P” when identifying parts.

Examining Subset ratio as you build up your data model is an important quality step.  Validating the quality of your data model will make the process of creating visualizations go much smoother.

-Rob

 

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Qlik Sense Document Analyzer V1.5

Version 1.5 of the Qlik Sense Document Analyzer (QSDA) tool is now available for download here.

If you are not familiar with QSDA, it’s a free application profiling tool for Qlik Sense that can help you identify items such as unused fields, poorly performing expressions and data model problems.

Here are the significant changes in V1.5:

The Installer allows editing of all install paths and installation will create a log file in the User’s temp directory.

The  Summary ribbon at top of each sheet provides for sheet navigation by clicking a cell.

 

Improved error handling in the connector. Certain types of errors, such as a chart calculation timeout, will not terminate the script. Error count is reported on Summary sheet and detailed error messages can be viewed on the “Extract Log” sheet.

Items that should be considered incomplete due to analysis errors will highlighted in yellow.  This highlighting is a work-in-progress as I discover new possible errors.

Field widths (Symbol width) are no longer estimated! Field sizes are obtained directly from the engine.  Due to this change, this version will report different values for field sizes than previous releases, generally +/- 10%.

The connector edit dialog has been improved.  Error messages now appear properly in their own window and a progress bar displays when the list of applications is fetching.

If you have general usage questions on QSDA, please use the comments section here or Qlik Community.

If you have a bug to report, use the issue tracker.

The only installation supported by the installer is QS Desktop. You can use QS Desktop to analyze applications on a server.  It is possible to manually install on a server by uploading the application (qvf), the qsda-ribbon extension and the connector directory if you have the need and want to give it a shot.  I do plan to create a supported server installer in the future.

Have fun!

-Rob

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Web Dev for Qlik Devs in US & UK March 2019

March 2019 brings our popular boot camp course to both the US and UK. Here’s an opportunity to fast track your Qlik team in using Qlik Sense APIs to create extensions, mashups, portal integrations and custom content pages that leverage data and visualizations from Qlik Sense.

In this four-day hands-on course you will learn:

  • The fundamentals of HTML/Javascript/CSS as they apply to QS Development and how to get started with popular frameworks and libraries including bootstrap and enigma.js.
  • Creating Visualization Extensions.
  • The differences and use cases for the various QS APIs e.g. Capability, Visualization, Engine.
  • Key QS API concepts such as the generic object model.
  • Connecting to the QIX engine to retrieve existing content or generate aggregations (hypercubes) on the fly.
  • Visualizing data using third party libraries.

See the course syllabus here.

Students will come away with example code and completed exercises giving them the confidence to move ahead on their own.

No prior experience with web programming is required as the course will provide an intro to web dev technologies and how they are used in Qlik Sense Web Development.

The US session will be taught by Rob Wunderlich and the UK session by Nick Webster.

Even if you don’t have a specific project in mind, I recommend taking this course to understand the power and potential of the QS APIs.  You’ll be surprised and inspired!

Cost for the four days is $2,600 / £ 2,000 and includes all course materials and lunch each day. Register at http://websy.io/training/web-dev-4-day

Questions? Reach out to us. See you there!

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Qlik Sense Document Analyzer v1.4

Version 1.4 of the Qlik Sense Document Analyzer (QSDA) tool is now available for download here.

If you are not familiar with QSDA, it’s a free application profiling tool for Qlik Sense that can help you identify items such as unused fields, poorly performing expressions and data model problems.

I’m pleased that Mike Steedle of Axis Group has joined me as co-developer of QSDA.   Mike contributes his many years of experience in profiling and tuning Qlik applications.

 

Here’s what’s new in version 1.4:

  1. Installer improvements. The correct directory for Connectors and Apps is automatically detected.
  2. New attribute “ObjectIsExtension”. Possible values are:
    • False – not an extension.
    • True – object is an extension but not a widget.
    • Widget – object is a widget.
    • Missing – object is an extension, but extension is not present on server.
  3. Unused Master Visualizations, and the Dimensions and Expressions therein, are now extracted and processed.
  4. DimensionLabel field added to “Dimensions” table.
  5. New table “Bookmarks”. Bookmarks are now extracted and linked to Fields.
  6. MB Constant changed from 1000*1000 to 1024*1024. This means these numbers now scaled in MB will have slightly smaller values than previous versions.
  7. Calc Time is now displayed in seconds instead of milliseconds.
  8. Dimensions and Expressions summary added to Objects sheet.
  9. Some analysis of the data model is performed, and the results and recommendations expressed as flag fields. New sheet “Flag Summary” will display an overview of found conditions.
  10. Color highlighting of detected problems.
  11. Reorganization of sheets and sheet layouts.
  12. Addition of a “Glossary” sheet provides descriptions for flags.

The installer currently only supports installation on Qlik Sense Desktop, although you can  analyze applications on Enterprise Server.

Improving the server analysis capabilities and possibly a server install will be a focus of the next update.

If you have general usage questions on QSDA, please use the comments section here or Qlik Community.

If you have a bug to report, use the issue tracker.

I hope you find QSDA useful.  I’m excited to see it maturting and pleased to have the help from Axis Group.

-Rob

 

 

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Loading Varying Column Names

Summary:  A script pattern to wildcard load from multiple files when the column names vary and you want to harmonize the final fieldnames.  Download example file here.

I’m sometimes wondering “what’s the use case for the script ALIAS statement?”.  Here’s a useful example.

Imagine you have a number of text files to load; for example extract files from different regions.  The files are similar but have slight differences in field name spelling.   For example the US-English files use “Address” for a field name, the German file “Adresse” to represent the same field and the Spanish file “Dirección”.

We want to harmonize these different spellings so we have a single field in our final loaded table.  While we could code up individual load statements with “as xxx” clause to handle the rename, that approach could be difficult to maintain with many variations.  Ideally we want to load all files in a single load statement and describe any differences in a clear structure.  That’s where ALIAS is useful.  Before we load the files, use a set of ALIAS statements only for the fields we need to rename.

ALIAS Adresse as Address;
ALIAS Dirección as Address;
ALIAS Estado as Status;

The ALIAS will apply the equivalent “as” clause to those fields if found in a Load.

We can now load the files using wildcard “*” for both the fieldlist and the filename:

Clients:
LOAD *
FROM addr*.csv (ansi, txt, delimiter is ',', embedded labels, msq)
;

It’s magic I tell you!

What if the files have some extra fields picked up by “LOAD *” that we don’t want?  It’s also possible that the files have different numbers of fields in which case automatic concatenation won’t work.  We would get some number of “Client-n” tables which is incorrect.

First we will add the Concatenate keyword to force all files to be loaded into a single table.   As the table doesn’t exist, the script will error with “table not found” unless we are clever.  Here is my workaround for that problem.

Clients:
LOAD 0 as DummyField AutoGenerate 0;
Concatenate (Clients)
LOAD *
FROM addr*.csv (ansi, txt, delimiter is ',', embedded labels, msq)
;
DROP Field DummyField;

Now let’s get rid of those extra fields we don’t want.  First build a mapping list of the fields we want to keep.

MapFieldsToKeep:
 Mapping
 LOAD *, 1 Inline [
 Fieldname
 Address
 Status
 Client
 ]
 ;

I’ll use a loop to DROP fields that are not in our “keep list”.

For idx = NoOfFields('Clients') to 1 step -1
  let vFieldName = FieldName($(idx), 'Clients');
  if not ApplyMap('MapFieldsToKeep', '$(vFieldName)',   0) THEN
    Drop Field [$(vFieldName)] From Clients;
EndIf
Next idx

The final “Clients” table contains only the fields we want, with consistent fieldnames.

Working examples of this code for both  Qlik Sense and QlikView  can be downloaded here.

I hope you find some useful tips in this post. Happy scripting.

-Rob

 

 

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Art of the Possible: Dynamic Values

One of my goals in doing presentations and classes on Qlik Sense APIs is to get people to see the “Art of the Possible” — that is, seeing what opportunities may exist in your organization to leverage the power of the associative engine and the Sense APIs, beyond the standard client and hub.

Today I’ll highlight a demo built by my colleague Nick Webster.  This chart actually came out of a class when a student asked “could we…”.

This example uses a standard Qlik Sense table that shows Sales in both USD and Euro.  The twist is that the Euro column is calculated dynamically using an exchange rate fetched from a web service.

http://websy.io/demos/aop1 (select “Live Currency” from menu)

This visualization appears in a web page, but the data and the visualization (optionally we shall see later) are in Qlik Sense.

The Euro column is the sales amount multiplied by a variable representing the Euro rate. The Measure is:

Sum([Sales Amount]) * $(vEurRate)

Every 20 seconds a JavaScript function in the webpage makes a call to a web service to get the current USD/Euro rate.  The new rate is then assigned to the variable with a single API call:

app.variable.setNumValue("vEurRate", eurRate);

The chart will  refresh with the new calculation. Do we have to do anything to get the updated values to display? No! The visualization is automatically refreshed.  The API takes care of all the plumbing to detect the change and update the display.

Does this table viz need to appear in the Qlik Sense app?  It may be created and maintained in the app , in which case it is inserted into the web page with a single line of code:

app.getObject("pageLocation","objectId");

Alternatively, you can create the entire table visualization using JavaScript code in the web page.

You have options for reuse of existing content  and deciding where the code will reside.  For example, leveraging the skills of the Qlik Devs for expression authoring and visualization creation.  Or creating the visualization by using code only for tight integration with web development.  Or splitting the work where the Qlik Team authors Master Measures in the app and the Web Team builds code generated visualizations that utilize those Measures.

On December 3-6 I will be teaching a “Web Development for Qlik Developers” class in Atlanta.  In this four day class we’ll explore the “Art of the Possible” and get you enabled to begin implementing those possibilities as mashups and visualizations using the Qlik Sense APIs.

The class is geared to Qlik Sense Developers who have no prior experience coding web with web technologies.  We’ll start by learning the basics of HTML, CSS and JavaScript as they apply to Sense.  We’ll move on to reusing existing visualizations and create new visualizations from scratch, even using libraries beyond Qlik Sense.  The class is full of hands on exercises and you’ll come away with your work as well as many samples.

Along the way we’ll look at the requirements and options for licensing and deployment, and integration with popular web frameworks like Angular and Bootstrap.

You can register for the class here.  If you have any questions before registering, reach out to me on the Contact Form.

-Rob

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Web Dev for Qlik Devs in Atlanta

Here’s an opportunity to fast track your Qlik team in using Qlik Sense APIs to create extensions, mashups, portal integrations and custom content pages that leverage data and visualizations from Qlik Sense.

In this four-day hands-on course you will learn:

  • The fundamentals of HTML/Javascript/CSS as they apply to QS Development and how to get started with popular frameworks and libraries including bootstrap, enigma.js and picasso.js.
  • Creating Visualization Extensions.
  • The differences and use cases for the various QS APIs e.g. Capability, Visualization, Engine.
  • Key QS API concepts such as the generic object model.
  • Connecting to the QIX engine to retrieve existing content or generate aggregations (hypercubes) on the fly.
  • Visualizing data using third party libraries.
  • Using Qlik javascript libraries picasso.js and enigma.js.

Students will come away with example code and completed exercises giving them the confidence to move ahead on their own.

No prior experience with web programming is required as the course will provide an intro to web dev technologies and how they are used in Qlik Sense Web Development.

Even if you don’t have a specific project in mind, I recommend taking this course to understand the power and potential of the QS APIs.  You’ll be surprised and inspired!

The instructor for this course is Rob Wunderlich, a well-known and respected Qlik Consultant and Trainer, Qlik Luminary and publisher of QlikCookbook.com. For more information on the course please contact rob@robwunderlich.com

Cost for the four days is $2600 and includes all course materials and lunch each day. Register at http://qlikviewcookbook.com/registerAtlanta/

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Theming the Qlik Sense Script Editor

Summary: In this post I show how to modify the style of the QS Script Editor window.

An astute reader — Johan Roelofsen — of my blog on bookmarklets noticed I had a bookmarklet named “QS Blackboard” and asked if this was used to change the window background color.  Excellent guess, spot on, but there’s more to it.

Changing only the background color can yield a poor result because the text begins to blend into the background.  I’ll want to change the text colors and possibly size as well to yield something like this:

Fortunately QS uses the CodeMirror (CM) editor which provides a theming capability.  Theming the CodeMirror window is done by loading a style sheet and then making an API call to use that style.

The instructions that follow will show how to implement your own custom theme in QS Desktop (I assume it will work in Enterprise as well, just haven’t tried it).

Note that we will not be modifying any of the installed Qlik software files!

  1. In the folder :
    C:\Users\userid\AppData\Local\Programs\Qlik\Sense\Client

    Create a new subfolder (below Client) named “cmtheme”.  This is the folder that will contain your CM style sheets.

  2. Download or build a theme-name.css file in the cmtheme directory.  You can try out various existing themes on this demo page here and download the corresponding css file from the CM repo here.

“Projector1” available here is a theme I’ve built for projecting. If you read the doc or look at the examples, you’ll see the pattern whereby you must define .cm-s-themename selectors in your CSS.

If you start with one of the CM themes, you’ll want to add selectors for QS script specific elements like function, table and field.

.cm-s-projector1   .cm-function {color: #c678dd;}
.cm-s-projector1   .cm-table {color: #d19a66;}
.cm-s-projector1   .cm-field {color: #d19a66;}

All that’s remaining is to  invoke your theme while in the editor.  I use this bookmarklet that first loads the css file and then calls SetOption on the CodeMirror editor instance:

javascript: (function () { 
 var theme = "Projector1";
 $('head').append('<link rel="stylesheet"  href="../resources/cmtheme/' + theme + '.css" type="text/css"/>');
 $('.CodeMirror')[0].CodeMirror.setOption("theme", theme);
 }());

It’s the same bookmarklet code for any theme, I just change the hard-coded theme variable.

To “unapply” your theme and return to QS native, just press F5 to refresh the browser.

Have fun.  And remember when you tinker with something like this the best approach is to not update the vendor (Qlik) software files and instead seek a non-intrusive approach.

-Rob

Hey Rob, I’m a Qlik Dev. This CSS + Javascript stuff looks like a foreign language to me.  How I can upskill to be able to leverage the Qlik Sense APIs including creating Mashups and Extensions?

Easy answer.  Take the  “Web Dev for Qlik Devs” course from Websy.  You can self-study online through the Websy Academy,  take an on-line instructor led course or have one of the Websy team — including Rob — deliver a course at your site to your entire team. 

 

 

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Running QS Regression Test in Batch

If you’ve ever seen my presentations on automated testing of Qlik apps, you know I’m a big fan of the free Qlik Scalability Tools  — both QV and QS.

I use the Regression Test feature to automatically validate Qlik app changes before promoting to production.   Regression testing allows us to validate that charts continue to produce correct results after updates are made to the application or platform software.

This graphic provides a brief overview of the regression testing concept.

The Qlik Sense Scalability Tool (QSST) provides a GUI workbench to run and analyze regression tests.  The workbench is a great tool for a developer or QA Analyst to validate an app on an adhoc basis.

What if I want to run the analysis unattended on a schedule?  For example, after every reload to validate that my app is still working correctly and my expected data was loaded.

In this post I’ll demonstrate using a system monitor to run the regression test as an ongoing validation and send an alert if the validation fails.

I won’t go into the details of setting up the Scalability Tool.  You can get that from the product documentation.  If you would like me to do a presentation on automated testing for your team contact me here.

We will need a system monitor that is capable of running commands on a schedule, monitoring the command output and sending alerts or status via something like email or Slack.  You may already have a capable system monitor installed at your site.

NodeGraph is my current favorite Qlik-centric testing tool for ongoing quality monitoring (I’m a partner).  NodeGraph’s Test module allows for testing expression values,  presence of fields and update times.  At the moment NodeGraph does not support running QSST Regression tests, but I expect it will be part of the product by 2018Q4.

For the time being, I’ll demonstrate batch regression testing using Woodstone’s Servers Alive, a low cost but powerful system monitor I’ve used in the past.  You can try Servers Alive for free.

Let’s assume we have used the QSST workbench to author the regression test scenario and have executed the scenario to create a  baseline log.  When using the workbench, we would re-execute the scenario at a later time to create a compare log and then analyze the differences between the logs using the workbench Analysis tool.

QSST provides command line versions of both the scenario executor (“SDKExerciserConsole.exe”) and the regression log analysis (“RegressionAnalyzerConsole.exe”) .  We will need to bit of script to stitch these two operations together and process the output.

I’ve posted a powershell script here that wraps all the necessary operations and exits with an ERRORLEVEL of “1” if validation fails (differences found between compare and baseline logs), or “0” if no differences are found.

  1. Download the RunRegressionTest.ps1 script and place it in a directory named “Regression”.
  2. Create a subdirectory under Regression named “baseline”.
  3. Copy your baseline log file for each app of interest to the baseline directory.   Do not rename the file.
  4. Following the comments in the file, update the first three variables in  RunRegressionTest.ps1 to identify the location of your QSST install and your scenario json file(s).

We can check that the script runs correctly from a powershell command prompt in the “Regression” directory.

.\RunRegressionTest.ps1 "ABC Sales Demo"

where “ABC Sales Demo” is the name of a json file in our scenario directory.  If all goes well, we should see output messages like:

PS C:\QlikSense-Projects\Regression> .\RunRegressionTest.ps1 "ABC Sales Demo"
 Comparing C:\QlikSense-Projects\Regression\temp\results\ABC Sales Demo_localhost_[1-0-1--1]_18072311263304_regression.log
 to baseline: C:\QlikSense-Projects\Regression\baseline\ABC Sales Demo_localhost_[1-0-1--1]_18072216105188_regression.log
 Differences found

Now to implement this in Servers Alive.  In Servers Alive we define things to test as “checks”.  In this case I’ll use the External(errorlevel) check type and provide the command string to run my powershell script.

The full command string is: (no line wrap)

powershell -NoProfile -ExecutionPolicy bypass -File "C:\QlikSense-Projects\Regression\RunRegressionTest.ps1"  "ABC Sales Demo"  "p2"

where “ABC Sales Demo” is the name of my scenario json file.  “p2” is a dummy parameter that works around a windows bug.  Without that extra parm, a blank space is added to the previous parm causing a failure.

On  the Alert tab I’ll specify to send a message to Slack on failure. On the schedule tab I’ll specify when to run this check.

All set up!  When run either manually or on schedule, a failed check — that is, the regression test found unexpected differences — the check will display red on the SA console and I’ll  also receive a Slack message.

 

 

 

 

I’ve just introduced a number of moving parts.  If this is all new to you what I hope you’ll take away is that formal, structured and automated monitoring of your Qlik Applications is possible with relatively low cost and effort.

Want some assistance with planning your testing strategy and implementation?  I offer consulting in planning and implementation of automated testing and monitoring for your Qlik environment. Contact me if you want to chat about your needs and how I can help.

I also typically do an optional lunchtime session on testing at the Masters Summit for Qlik.  Come along to Philadelphia or Johannesburg to talk testing and many many more Qlik topics.

-Rob

 

 

 

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