Advanced Functions – Exhaustive DSO using dollar-sign expansion with parameters

As everybody probably knows by now, the book “QlikView 11 for Developers” by MIguel Garcia and Barry Harmsen is an excellent resource.  Other than the cover photo and the title that could lead someone to think developing Qlik involves hardcore programming; and the space wasted on showing the pie, grid, and funnel chart, I enjoyed reading what is to date the best didactic material about Qlik.

Even though I’ve worked with Qlik for eight years, I learned a few tidbits from the book.  For example, I hadn’t noticed that you could add parameters to variables, and with the help of dollar-sign expansion, pass parameters to those variables.

I avoid using techniques in Qlik that make it feel like you’re programming because I believe Qlik should be as simple and as open as possible for business users.  However, sometimes the benefit of using advanced techniques is too great to ignore.

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Set Analysis – New and Lost Customers with Nested Advanced Search

I love the analysis that can be done using Qlik’s Set Analysis, but its syntax leaves too many business users lost and confused.  Those same business users that use Excel today for their analytical needs and aren’t completely convinced that Qlik is accessible enough to perform their own custom analysis.

I believe that one day applying simple and complex business rules will be made easier, but until then, I’m going to share tips and tricks to keep Set Analysis syntax as simple as possible.  Additionally, I will use examples of commonly used indicators that you can re-use for your own Qlik applications.

One of the confusing attributes of Set Analysis syntax is knowing when to use double quotes ( ” ) and when to use single quotes ( ‘ ).  According to Qlik Help (a great resource),

A search is always defined by the use of double quotes, e.g. <Ingredient = {"*Garlic*"}> 
will select all ingredients including the string ’garlic’.

A search can also be based on a formula or a range.  For example, <Customer = {“=sum(Sales)>10000”}> will select all customers that have a sum of sales greater than ten thousand and <Year={“>=2008<=2010”}> will select all including between and including 2008 and 2010.

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Advanced Scripting – Creating an e-mailing list in Qlik

Recently, I set upon creating an e-mail list for a bi-monthly newsletter that my company Evolcon is going to send with updates on everythings related to Qlik and becoming a more data-driven organization.  Of course, I used Qlik to parse and clean the e-mail list, and in the process, I used some not so common scripting functions that are fun to use.

The first step was to extract the e-mail information from Outlook and Gmail.  You can easily find sites that will lead you through the process in Google.  I used a Google script found on this blog and the Outlook extraction was pretty straight forward.

Parsing with subfield()

Once I extracted all the e-mail addresses from my e-mail and copied them to an Excel file, I started to write my script in QlikView to parse and clean the e-mails.  The first challenge I encountered was parsing the domain from the e-mail.  That’s a pretty simple job with the subfield() function, and the following function did the job:

SubField(Email,'@',2) as Domain,

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Thoughts on being a Qlik Luminary

2014 Qlik Luminary Digital Badge

Life is made up of moments, and I remember clearly the moment I asked by former boss for a career change. Eight years ago I decided to leave a future of implementing ERPs and bet on a new future helping people analyze their data with a software called QlikView.

In 2006, QlikView was new to Mexico and it wasn’t easy to convince prospects that we were better than the OLAP-based competitors that had already been around for decades. However, we knew it was the product of the future because almost every time we competed with OLAP-based software in Seeing is Believing events, we would leave the prospect in awe and win the project. I’ll never forget the time I made a business user shed tears of joy after seeing an analysis in QlikView that the company had never been able to perform after years of numerous, futile attempts with other tools.

I’m more an analyst than a salesperson, so I know QlikView is not perfect. I respect what Stephen Few has done for data visualization and I’ll always have a place in my heart reserved for Tableau, but as I commented in my recent book, I believe QlikView is the best all-around data discovery software. There’s more to data discovery than data visualization. Rapid, efficient and easy data extraction and transformation along with an innovative associative data model are all vital tools to discover data, and this is why I still prefer QlikView.

Now eight after first choosing QlikView, it has been renamed Qlik and as a new, game-changing version is ever closer to being unveiled, I’m going to bet again on Qlik. I’m honored to be among a group of the Qlik Luminaries that includes an impressive list of customers, partners and enthusiasts. As a Qlik Luminary, I promise to take on the responsibility to share how great Qlik is to all those who still suffer from information deficiency, and I also promise to represent the needs of my customers to make Qlik an even greater data discovery tool.

I will keep you updated on what I can share with you during what looks to be an excellent 2014.

Let’s do it again! Win a Free Copy of Packt’s Learning QlikView Data Visualization.

Packt Publishing is going to be giving away 2 free copies of Learning QlikView Data Visualization this week.

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Overview of Learning QlikView Data Visualization

  • Explore the basics of data discovery with QlikView
  • Perform rank, trend, multivariate, distribution, correlation, geographical, and what-if analysis
  • Deploy data visualization best practices for bar, line, scatterplot, heat map, tables, histogram, box plot, and geographical charts

How to Participate
During the
last giveaway, I asked for ideas on what data visualizations you would like to add to QlikView.  Now, I can’t imagine the development team at QlikTech being able to focus on creating and improving every chart and graph in QlikView, so let’s help them focus on the best data visualization techniques, and therefore leave behind some of the charts and graphs in QlikView that don’t do a good job of helping us discover data.

Continue reading “Let’s do it again! Win a Free Copy of Packt’s Learning QlikView Data Visualization.”

Is AutoNumber() really worth the hassle?

AutoNumber() can be a pain when trying to debug problems in a QV data model, especially if you are integrating multiple data sources and need the original source’s keys to trace problems. Sometimes I get the impression that people recommend it based on the idea it will make the links between tables more efficient because numbers are more efficient key fields than strings, but given that all data whether a string or a number value is assigned a binary record pointer automatically, QlikView makes links between tables using those same binary addresses.

Autonumber() does nothing more than slim down the RAM QlikView uses by reducing the size of the symbol table that contains the unique values of a field.  Therefore, it makes no sense to transform an ID with autonumber() for a key field and also keep the ID in its original state in another column.  The only exception to this rule is when the original ID is used as a dimension or in an expression.

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Congratulations to the winners!

Thanks to all those who responded to my post in QlikCommunity and in this blog about what data visualization they would like to see in QlikView.  I learned a few things about what people would love to do in QlikView.  Most visualizations that were posted are possible to create in QlikView, but what frustrates many users seems to be the difficulty creating these visualizations through tricks, extensions or third-parties.

I think we can expect great advances in data visualization in QlikView after the company bought NComVA, a company dedicated to data visualization.  Along with QlikView’s continuous improvements, I believe it is important to continue creating new and improving existing extensions.  There is always going to be a visualization that QlikView cannot create out-of-box, and that’s why extensions are such a key element.

So, enough talking.  The winners of the three Learning QlikView Data Visualization e-books are:

  • Philipe Grenier
  • Rebeca Gums
  • Sokkorn Cheav

If you are a winner please send me a message in QlikCommunity with your e-mail address so that I can send you your e-book.

Thanks again for all those who participated.

Hope to see you around,

Karl