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A while ago I blogged about 2 of our most beautiful mashups in the Demo Team, Salesforce and CIO dashboard.

 

Case study: Salesforce mashup

Jazzing up your Mashups

 

After I was asked by many for the source files, here are the 2 github pages

 

GitHub - yianni-ververis/CIO: CIO mashup created by the Demo Team

GitHub - yianni-ververis/Salesforce: Salesforce Mashup created by the Demo Team

 

Upload the qvfs on your server and put the ids into the project.json file. Then in the command line type "npm install" to install all the required libraries and "gulp" to build and run the project.

 

Depending of the version of Qlik Sense you are running, most likely you will get CORS errors and some fonts may not load up. If you have valid certificates for localhost then under ./gulp-tasks/server.js comment out lines 15-18

 

Best,

Yianni

Guided apps are probably the more common data viz pieces nowadays. Are strongly influenced by the traditional journalistic approach to a story and related with storytelling. The goal of guided apps is to walk the reader from point A to point Z.

 

A well-constructed guided visualization is incredible powerful at proving a point, examples can be found almost daily at mass media websites. As a data professional, I love data stories but maybe because I’m such a data geek I usually never get completely satisfied by the visualizations used to emphasize the story. I almost always hungry for ways to explore the data or I simply miss one angle from the story to feel fulfilled.

 

On the other hand, the so-called Discovery apps are intended to let the user to manage the ride and rely on reader capacity to be able to interact and to understand the data they are looking at. Scenarios with simple and familiar data are generally more appropriate for discovery apps.

 

We recently got one of those great data sets for discovery, simple data and containing thousands of potential stories in it. Barcelona Marathon organization contacted us to create a piece to let runners (data users) to explore every corner of their data. They have been collecting runners’ data during the last decade, our part was just to put a nice wrap around it. We like to see it as a nice hybrid (more on the discovery side) of guided and discovery app.

 

barcelonaMarathon.png

 

 

We divided the mashup into three sections trying to help first time users to better get familiarized with the data. It’s just a visual separation of the data, each section belongs to the same data model, filters are global and every selection affect all the charts. For the clarity of it we reduced the use of set analysis as much as possible.

 

The app starts with race overview data, about participation and finishing times. The second section serves as demographic info, with three main characteristics to consider, age, sex and nationality. Finally, we reserved a little bit of complexity for the very last section, we called it Performance. As you can see in the picture below taken from the chart “Avg time by age” the sweet spot age for someone to run this marathon is 35 years old, in average people in that age get the best results.

 

avg time by age.png

 

You can check the mashup live at Barcelona Marathon page here or as a stand-alone version at Marató Barcelona.

 

Regards,

Arturo Munoz (@arturoqv)

excited.png

Hey guys! - I'm very excited to introduce you to our latest release of Qlik Sense, June 2017. Yep - no version number or dots in this naming convention. With the announcement of our continuous release process discussed here, Qlik will begin releasing Qlik Sense every 10 weeks!  Since each release will be similar in scope, we are also replacing our number-based naming convention with releases identified by the month and year they were distributed.  This means that instead of Qlik Sense 4.0, our June release is simply called Qlik Sense June 2017.  (Most other Qlik products will also follow a similar cadence going forward as well.)

 

 

Currently customers and partners are invited to Join the Technical Preview and can get the latest software here. If you are not a customer or partner, our freemium product, Qlik Sense Desktop - will be available later in the month - however you can still experience some of these new features immediately (such as the new data preparation features) without downloading any software by registering with Qlik Sense Cloud.

 

There is so much goodness in this release that I don't want to create a giant text wall telling you about it. I created a brief summary video for your enjoyment as well as longer videos detailing and demonstrating the new features. You can view them at the video index below which include video files and samples. Please note that additional information on our Advanced Analytics integration is available in this community group Advanced Analytics Extensions and requires permission. Please send an email to mailto:insight@qlik.com to gain access. I am in the middle of working on a brief summary and "Hello World"-type video to demonstrate its concepts.

 

We want to hear from you, so please your comments and questions below!

 

Qlik Sense June 2017 - Highlights

 

The main video index for the Qlik Sense June 2017 Release and video .mp4 files and samples can be found here: Qlik Sense June 2017 - What's New

 

NOTE: To increase resolution or size of the video, select the YouTube logo at the bottom right of the player. You will be brought directly to YouTube where you can increase the resolution and size of the player window. Look for the 'settings' gears icon in the lower right of the player once at YouTube.

 

Regards,

Michael Tarallo (@mtarallo) | Twitter
Qlik

If you're creating a mashup that includes embedded Qlik Sense charts, there's a couple issues you may run into that you'll want to be aware of.

 

First, if your mashup scrolls, and you scroll down the page, you will notice that the tooltips on the Qlik Sense charts are not positioned correctly, like below:

2017-06-07 11_20_25-Marató Barcelona.png

The tooltips will get more and more displaced the further down the page you scroll. For the tooltips to be positioned correctly, you'll have to adjust how scrolling happens on your page a little bit.

 

The easiest option that you can implement with just some CSS is to set the html and body tags to a height of 100%, hide the overflow on the html tag, and add use overflow: auto on the body tag. That looks like this:

html, body {
height: 100%;
overflow: hidden;
}
body {
overflow: auto;
}









 

Now the tooltips will no longer be displaced when you scroll your mashup. However, there are times when it may be necessary to watch the scroll position of the page, or be able to set the scroll position of the page programmatically, and for some reason, when using the above method the scrollTop attribute of the body tag never actually updates, so there is no way to observe when the page scrolls or set the scroll position programmatically.

 

In instances like this, just a simple extra step will fix the issue. What you'll need to do is add a wrapper element that wraps the entire content of your mashup, and also set that to a height of 100%, and put the overflow on that element. That element's scrollTop will be set correctly, and you can observe or set it programmatically. So, it would be something like this:

<head>
<style>
  html, body, #page-content {
    height: 100%;
    overflow: hidden;
  }
  #page-content {
    overflow: auto;
  }
</style>
</head>
<body>
<div id="page-content">
  <!-- All of your content -->
</div>
</body>









 

The other issue you may run into is the chart tooltip not be styled correctly, since it may be affected by the CSS in your mashup. The most common example I see of this is if using Bootstrap v4. Bootstrap v4 adds some negative margins to the .row class, and the tooltip also uses the row class, and it makes the text in the tooltip get cut off, like this:

2017-06-07 12_11_20-Marató Barcelona.png

To fix this, and any other styling issues you may have with the tooltips, it's helpful to be able to inspect it. A div with the class .qs-chart-tooltip will be appended near the end of the body. If you inspect the page and find that element, then expand it, it's first child element is a div that has display: none set, just uncheck that style and you'll be able to view the tooltip in it's last location. Then you can continue to expand those child elements and inspect the element, looking for any issues. In the case I show above, as I stated, the problem is with Bootstrap v4 and it's negative margins on the .row class. So the css below fixed the tooltip:

.qv-chart-tooltip-inner .row {
margin-left: 0;
margin-right: 0;
}


 

So, now you should be able to address these Qlik Sense chart tooltip issues I often see in mashups. If you have any questions, let me know!

The switch control statement is one of many controls statement that can used to determine the flow of the script.  In Qlik Sense help, it is defined as:

 

The switch control statement is a script selection construct forcing the script execution to follow different paths, depending on the value of an expression.

 

Syntax:

Switch expression {case valuelist [ statements ]} [default statements] end switch


The switch control statement can be used in the script to identify a specific execution path.  With the switch control statement, several paths can be defined and a default path can be defined as well when no match is found in the case clause.  The various script paths cannot cross – they should be individual paths that do not overlap.  In the script below, the expression x will be compared to each case.  When there is a match, the script for that case will be executed.

 

In the example below, Case 1 will be executed – the variable y will be set to Sunday and one record will be generated in the table.

script.png

Below is a look at the record generated.

Table.png

It is also possible to have more than one value for a case, for instance, you can use the script below to run the same script if x matches 1, 2 or 3.

case 1 2 3.png

When faced with various script execution paths, try using the switch control statement.  While I rarely have a need to use it, I like how neat and straight-forward the syntax is.  I have attached an example Qlik Sense app with the full script for you to test out for yourself.

 

Thanks,

Jennell

In this edition of the Qlik Design Blog, our Emerging Technology Evangelist, David Freriks is back discussing integration between Qlik and Kudu.

 

 

Navigating the analytics labyrinth with integration of Kudu, Impala, and Qlik

 


apachekudu_logo_0716_345px.pngUsing Hadoop for Big Data analytics is nothing new, but a new entity has entered the stale file format conversation with the backing of Cloudera – you might have heard of it, it’s called Kudu.

 

What is Kudu?

 

Let’s first take a step back and think about the dullest topic in the universe, file system storage formats. Flat files, AVRO, Parquet, ORC, etc. have been around for a while and all provide various advantages and strategies for data access optimizations in an HDFS construct. However, they all suffer from the same issue… static data that can only be appended to – unlike a real database.

 

So, enter Kudu – defined by Apache: “Kudu provides a combination of fast inserts/updates and efficient columnar scans to enable multiple real-time analytic workloads across a single storage layer.” Deconstructing that message – Kudu acts as a columnar database that allows real database operations that aren’t possible in HDFS file formats. It is now possible to interact with your Hadoop data where INSERTS, UPDATES, DELETES, ALTERS, etc. are now available as data operations. This means not just read/write capabilities for Hadoop , but also interactive operations without having to move to Hbase or other systems. IoT use cases, interactive applications, write-back, and traditional data warehousing are now possible without adding layer upon layer of additional technologies.

 

Now that we have a general understanding of what Kudu can do, how does this benefit Qlik? Kudu is fast, columnar, and designed for analytics – but with the ability to manipulate and transform the data to power new use cases.

 

Let’s start simple by showing how easy it is to move some data from an Impala table on Parquet into Kudu.

 

Starting in Hue we need to do some basic database-like work. To put data into a table, one needs to first create a table, so we’ll start there.

 

Kudu uses standard database syntax for the most part, but you’ll notice that Kudu is less specific and rigid about data types than your typical relational database – and that’s awesome. Not sure if your data is a varchar(20), or if it is smaller or larger?  No worries, with Kudu –  just declare it as a basic string.

 

1.png

 

Numerical data are basic as well, there a just few types to choose from based on the length of the number.   This makes creating columns and designing a schema very, very straightforward and easy to setup.  It also reduces data type problems when loading data.

2a.png

Having a general understanding of table creation, we will go ahead and create a table we are going to copy from Parquet.  It’s worth noting there are some differences here versus creating a Parquet table in Hue.

 

•    First:  A Kudu table needs to have at least 1 primary key to be created.

•    Second:  A Kudu table needs a partition method to distribute those primary keys

 

Referencing the schema design guide, we are going to use a HASH partition and use the number 3 (since we have 3 worker nodes).

 

In summary, we have a bunch of strings, a few integers, and some floating decimals to represent prices and profit. We’ve identified our keys and specified our partitions – let’s roll!

 

The query runs for a second and viola – we have our new (albeit empty) table. Next, we need some data. We have an existing table that we would like to copy over into Kudu. We will run another query to move the data and make a little tweak on the keys to match our new table.

 

We had to cast our customer_sk and item_sk columns from string in Parquet to int in Kudu but that’s pretty easy to do as shown in the SQL here.

 

We run the INSERT query and now we have our data moved over into Kudu, and even better – that table is now immediately available to query using Impala!

 

3a.png

 

 

Enter Qlik

 

With the data loaded into Kudu and exposed via Impala – we can now connect to it with Qlik and start building visualizations.

 

Using the latest Cloudera Impala drivers , we start the process of building a Qlik app by connecting to our new data set.

 

4a.png

 

Opening Qlik Sense, we will create a new connection to our cluster and select our new table.

 

Once we have the table and columns selected – we can modify the load script created by the data manager to directly query Kudu (versus loading the data into memory) to take advantage of the speed and power of Impala on Kudu.(we do this using Direct Discovery - NOTE the Direct Query syntax) This change is accomplished with a slight alteration in the syntax to identify dimensions and measures.

 

5a.png

 

We now have live queries running against Kudu data sets through Impala.

 

6a.png

 

The great part about Kudu is that we’re just getting started with the possibilities of how we can leverage the technology with Qlik. Some things we’re cooking up for the not too distant future involve write-back with Kafka and Qlik Server Side Extension integration – so stayed tuned.

 

Please visit cloudera.qlik.com for more demos and to see the Kudu demo in action.

 

Regards,

David Freriks (@dlfreriks) | Twitter
Emerging Technology Evangelist

Last year I blogged about our  Mobile Friendly Horizontal Bar Chart that we use in most of our mashups in the Qlik Demo Team.

 

Since then, many things have changed. For a start, if you have a mashup that uses many objects, you will see the load time to be much faster since I used d3.v4 and I have added a break point on how many bars to create, You can define if you want to show all or only the first 50.

 

I have also changed the currency. If you select the measure to be displayed as 'auto' then extension will use the custom format. You can abbreviate the measure with their respective symbol like 'B' for billions, 'T' for trillions etc and use your custom currency symbol

2017-05-24 18_04_56-Nordea Masters - CBO _ Sheets - Qlik Sense.png

Another new feature is the custom text to display when there is no data. If you make a selection in the sheet and that produces no results then this text will be displayed.

2017-05-25 19_33_42-_Nordea Masters - CBO - 2017 Nordea Golfers _ Sheets - Qlik Sense.png

 

Also, the tooltip is more elegant now and different from the standard Qlik Sense one. I changed it to follow the mouse instead of always aligned center at the top of the bar

2017-05-25 17_40_21-_Nordea Masters - CBO - 2017 Nordea Golfers _ Sheets - Qlik Sense.png

YIANNI

 

Files

Qlik Branch

C_86UVPU0AAZQLi.jpg

First - a bit on Qonnections


Last week was my 6th Qlik Qonnections, our annual partner and user conference. As usual it was a tremendous event filled with learning, networking and of course "fun and games"...literally this time around for those whom attended.  What was in the past, a partner only event, has grown to include our valued customers for its 2nd year. Our customers, partners and analysts from all over the world came to one awesome place (Gaylord Palms in Kissimmee Florida - my home town!) to share, collaborate, communicate and witness all the great innovation each had to offer...of course including a few things from Qlik. In my humble opinion, each year Qonnections has increased in quality and content....and this one felt like the best one yet, credit goes to our amazing events team, our sponsors and of course our customers and partners! If you want to learn more about all the happenings at Qonnections 2017, I suggest you check our company blog for the daily recaps as well as Cindi Howson's latest blog on the Gartner Blog Network: Qlik Reveals More Roadmap and Vision.

 

The Qlik Analytics Platform Demo

 

While at Qonnections, along with my colleague Josh Good, we had the pleasure of presenting a session that in short, basically highlights everything available in the Qlik Analytics Platform. Qlik has so much growing goodness in one box, that it's becoming almost impossible to cover everything we can do for an organization's various needs in just one meeting. So this presentation was created to quickly show what is possible and is performed using 5 "Acts" that demonstrates our core product capabilities while connecting the full breadth of analytic use cases across a fictitious organization - using one coherent story-line. We originally used this as an internal enablement-type resource, but also realized the value it contains for our customers and partners and decided to publish it.

 

There are 2 videos in this blog, including links out to detailed specifics on each of the use cases. The first video (3 min) is basically a short summary of the 2nd video - introducing you the main concepts, but sacrifices the detailed demonstration. The 2nd video is a longer (23 min) step by step demo flow that dives in deeper into each analytic use case. I hope you find this information useful and please note I am checking on the public availability of the demonstration app used in the videos. Once approved I will post this as an attachment to this post. I am also looking into making all the resources available on our Partner Portal.

 

Enjoy!

 

Michael Tarallo (@mtarallo) | Twitter
Qlik

 

 

 

Qlik Analytics Platform Demo Highlights (short)

 

Qlik Analytics Platform Demo (long)

 

 

For more detailed information on the full range of Qlik Analytical use cases, please view this videos at the following links.

 

 

NOTE: To increase resolution or size of the video, select the YouTube logo at the bottom right of the player. You will be brought directly to YouTube where you can increase the resolution and size of the player window. Look for the 'settings' gears icon in the lower right of the player once at YouTube.

 

NOTE:  Can't see the video? Download the .mp4 to play on your machine or mobile device.

 

down-arrow-png-17.png

A few weeks ago, we got into a new project to create an interactive piece with the Canadian media, National Post. The goal was to illustrate the donations candidates of the Conservative Leadership Race received from the start of the race through March 2017. Qlik Sense was integrated with Qlik GeoAnalytics to visualize where the donations were coming from and which candidates received the most donations in each area.

 

The map below was one of our first tries, we decided to use color to illustrate the top candidate by amount collected, and by postal code.

 

1.png

 

Problem with this approach appeared obvious at a first glance, postal codes areas have an insane size variance, regions such as the northern and barely populated province of Nunavut extents thousands of square miles in just one postal code while postal areas in urban zones, such as in Toronto, span a few city blocks and are hidden in the map.

 

So, how to make Nunavut and Toronto visible and comparable?

 

We decided to apply a binning operation to our data to solve most of the issues described. Qlik GeoAnalytics has a wizard that lets you chose operation, making the process seamless. The result is a new table containing squares (or hexagons) geo-polygons.

 

6.png

 

 

Conservative.gif

 

In this new map version, readers can compare areas easily without the distortion introduced by the different postal code sizes, letting us to see what’s going on in Toronto and in Nunavut at the same time.

 

We've added some extra cool features to the resulting Qlik Mashup. I recommend you to visit it and explore it at http://news.nationalpost.com/news/qlik

 

Enjoy,

AMZ

The following is a recording from our latest Tips and Tricks Webinar.

 

 

We want to hear from you. Please leave your comments and questions in the comments section below.

 

NOTE: To increase resolution or size of the video, select the YouTube logo at the bottom right of the player. You will be brought directly to YouTube where you can increase the resolution and size of the player window. Look for the 'settings' gears icon in the lower right of the player once at YouTube.

Halyard.js is a new open source library that simplifies the Qlik Sense data load experience as it abstracts away the need to write a load script. Halyard.js includes a mixin for enigma.js for loading your halyard representation into the QIX engine. Using halyard.js and enigma.js, it’s now pretty trivial to generate a load script and create an app on the fly.

 

I built an app that uses Facebook’s API to grab user’s posts, halyard.js to generate a load script, enigma.js to create a session app and objects, and then displays a few filters and a visualization just to test out the whole flow, and it was awesome. I made a video of the results below, check it out.



I want to put this app up live so everyone can try it out because it's so cool, but I’m waiting on Facebook approval. In the meantime, you can grab the source code below and try it out on your own machine.


There’s a few steps to do that. First, download the source code and run npm install. Then go to the qapp.js file and enter session info for your Qlik Sense server in the config variable on line 8. Next, you’ll have to go to https://developers.facebook.com/ and create an app. Once your Facebook app is created, grab the App ID and enter it in the fb.js file, on line 26.

For your Facebook App to be able to authorize users, you’ll need to add a platform and app domain in the “Settings” page of the Facebook app.

It’s up to you how to host this. I’ve included a .qext file if you just want to use Qlik Sense Desktop.

 

Once you’ve done that, run npm run webpack to build the project, and it should be good to give it a go!

Happy Tuesday everyone!. You guys are going to love this one. In this edition of the Qlik Design Blog, our Emerging Technology Evangelist, David Freriks is back discussing integration between Qlik and a powerful big data unstructured search platform called Solr. Not only does David discuss an out-of-the-box approach to this integration, he takes it to the next level and touts the power of the Qlik Platform APIs.

 

Solr

 

In case you haven’t seen it – there is a super powerful unstructured search platform used within the big data ecosystem called Solr, built on the Apache Lucene search engine library. What’s great about Solr is that it can index just about anything, text, xml, JSON, PDF, Word, Excel, including almost any kind of text based data. That means you can drop just about anything into Solr and make it searchable using the power of Lucene core which powers the Solr platform.

 

So, where does Qlik fit in you may ask? Well, let’s observe what a Solr query output looks like:

 

1.png

Standard Solr query output

 

Hmmm, not very user friendly, not to mention it was somewhat slow to execute. Here is a little bit about what we’re looking at:

 

  • This data is the collective set of Enron emails from its infamous collapse in early 2000’s.
  • We’ve loaded this data set into our Cloudera cluster and indexed it using Solr.
  • Once this data was loaded and indexed we tested with a series of queries.
  • A full query on someone with a lot of references such as Ken Lay can run upwards of 15 minutes to bring back every email that contains a reference to him.

 

Imagine 10’s or 100’s of users each waiting 10-15 minutes for a single question to be answered, it clearly dilutes the effectiveness of the engine as a business tool.

 

Enter Qlik

 

Qlik has a tremendously powerful REST connector that is perfectly suited for connecting to sources such as Solr. (A great resource created by Mike Tarallo on the Qlik REST connector can be found here: Working with the Qlik REST Connector, Pagination and Multiple JSON Schemas - check it out to understand the basics of how it works and how the response data is assembled within Qlik)

 

What follows is how we are using the Qlik REST Connector to connect to Solr.

 

Qlik In-Memory Analytics with Solr

 

Now that we are armed with the Qlik REST Connector, and the appropriate Solr REST API connection parameters, we can pull the entire Enron email data set into the Qlik engine via Solr. (Refer to the Apache Solr Documentation to learn more,)

 

2.pngQlik REST Connector configuration

 

By pulling the entire data set, and loading it into Qlik, we now ensure that all users have sub-second access to all the data down to the most granular level, and thanks to our associative search technology – all the data has been indexed and correlated in-memory.  We can gain further insights by incorporating stock market data. Combining Enron’s stock performance with their emails tells an interesting story of rising email volume along with collapsing stock prices and elevating trade volumes.

 

5.png

Power of Qlik Data Visualization - Enron stock performance correlated with email volume


Using a mix of visualization techniques, we can see a pretty interesting collection of data, including the famous “deleted emails” gap on the bottom right chart.

 

Performing some additional analysis, we can drill in on the height of the crash that also correlates with the spike in email volume, followed by a rapid drop in volume.

 

7.pngDrop in trade volume

 

Making a few more selections we can dive down into a specific name, or comment to filter down the result sets further.

 

6.png Detail and specifics - name, email address

 

This associative search allows us to dive down into the details of the “TO” elements of the data set and see the metrics affiliated with those names.  We can also jump over to the final sheet of the Qlik Sense app and look at the individual emails body content filtered by our prior selections made in the application.

 

8.png

 

QIX API Powered Solr Search

 

The above approach of using Qlik in-memory to front end the Solr search engine is just one of the many ways Qlik can access unstructured data in big data systems. Let’s consider another application also using Qlik with Solr – this time with just the Qlik API’s. As a quick refresher, the Qlik engine (called QIX) is a fully API enabled engine with tremendous extensibility that allows Qlik to plug into any web based technology (like Solr). Using the awesome QlikSocial framework from the esteemed Johannes Sunden he adapted the webapp to connect to Solr on demand and build a full webapp from scratch. This is a great example of what we call Custom Analytics.

 

We start with a search box… And our name(s) of interest:

 

9.png

 

Now unlike the formatted Qlik Sense app, when a user hits the “search” bar – everything will happen dynamically on the fly using the API’s.

 

10.png

 

Qlik will dynamically generate a REST connection to Solr, create and load the requesting data into memory, and then build a web app around the data using bootstrap.js and angular.

 

11.png

 

The webapp is still using the Qlik engine, so selections and the search engine are still available – but all the charts and graphics are html and d3js charts – not Qlik. We’re just powering the app and the data interactivity with the QIX engine!

 

Summary

 

Solr is an extremely powerful unstructured search engine that can benefit from the speed and structure of Qlik analytics. It can provide a focusing lens on the core Solr search technology. That data can be consumed in a number of formats including a completely structured Qlik Sense app, or as an API powered web application without any Qlik UI components.

 

For more information, visit our demo site at cloudera.qlik.com

 

Enjoy!

 

Regards,

David Freriks (@dlfreriks) | Twitter
Emerging Technology Evangelist

A couple of years ago I wrote a blog on customizing straight tables in QlikView explaining how you can add an ad-hoc report to your QlikView app.  So, I thought I would share how you can now create a custom report in Qlik Sense using the Climber Custom Report extension.  The Climber Custom Report is an extension that can be added to your Qlik Sense app to give users the ability to create their own ad-hoc reports.  In this blog, I will show you how easy it is to add a custom report to your app using Qlik Sense Desktop.

 

  1. The first step is to download the Climber Custom Report extension from Qlik Branch, unzip it and put it in your Extensions folder (C:\Users\xxx\Documents\Qlik\Sense\Extensions).
  2. In your Qlik Sense app, create a table with all the possible dimensions and measures a user may want to see in a report and then add the table to master items.  The table may look something like this: table.png
  3. Add the Climber Custom Report extension to a sheet in your app and then you are ready to create a report.
  4. In the Visualizations drop down, select the report you just created.  All tables that are in your visualization master items will be listed in the drop down.  Once the table is selected, the dimension and measure lists will be populated with the dimensions and measures that are used in the table as seen below.dimensions and measures.png
  5. Select the dimensions and measures you would like to add to your report by clicking on them.  Your report will look something like the image below after you make some selections.  The dimensions are blue and the measures are orange.selections.png
  6. From the custom report bar above the chart, you can remove a dimension or measure by clicking the x and you can change the order of the columns by dragging and dropping the dimensions and measures into the order you would like them to appear in the report.

 

And that is it - it is that simple to add a custom report to your Qlik Sense app.  With Qlik Sense self-service, a user can create a report by dragging and dropping dimensions and measures into a table but what I like about the Climber Custom Report extension is it makes everything available to the user with a clean, professional and organized look.  Download it now and test it out for yourself.  See the extension in action in the Situational Awareness demo.  Note - the Climber Custom Report extension works in Qlik Sense 3.0 and higher and, like all extensions, are not supported by Qlik.

 

Thanks,

Jennell

Wow that's some title huh? Ooooh - "Qlik Sense Cloud Business and the Web Connectors" - sounds like the title for a fantasy adventure novel. Seriously, Denise LaForgia and I are back with a Qlik Sense Cloud Business update including some new videos to briefly introduce you to some really cool and new capabilities available in Qlik Sense Cloud Business - our new Web Connectors starting with access to data for Google Analytics, Twitter and Facebook. Take it away Denise!

 

Thanks Mike!

 

As promised in my blog last month, I’m back with more exciting updates about new features in Qlik Sense Cloud Business. Following our launch of REST Connectivity, I’m excited to announce that Facebook, Twitter and Google Analytics data sources are now also available in Qlik Sense Cloud Business under our new Web Connectors package.

 

For business users in particular, these connectors provide an easy way to bring together and analyze multiple data sources and data sets that are critical to sales, marketing, and other business initiatives. While some tools for social and sentiment analysis might allow you to analyze data from those sources individually, the power of Qlik Sense lets you associate this data about social and digital activity with other information about your customers, sales, marketing campaigns, customer service, and more.

 

Here’s an overview of the type of data each connector can return:

 

Google Analytics

The data returned includes many of the fields you’d see in the Google Analytics dashboard, such as page views, top landing pages, most visited pages, etc. You can retrieve data on any Google Analytics-enabled website.

  • Accounts: returns the accounts that the user has access to
  • DataFromQueryURI; enter a query URI on this table
  • DataFromTemplateQuery: returns a report from one of the available prebuilt queries
  • WebProfiles: returns the profiles that the user has access to
  • WebProperties: returns the web properties the user has access to

 

Watch Mike's brief video to get a general idea of how it works:

 

Community page and video download

 

 

Twitter


The content returned includes all tweets that include a hashtag or search term, and you can use Twitter query operators to pull data for more specific, detailed searches.

  • Mentions: returns up to 800 tweets for a Twitter screen name
  • Search: returns tweets based on a search term and other parameters
  • SearchAdvanced: returns tweets based on search term and other parameters and returns more columns than simple search
  • UserSearch: returns information about an account based on a named user search or topic search

 

In this video Mike shows how simple it is to get after Twitter data:

 

Community page and video download

 

Facebook Fan Pages and Groups

 

The data retrieved includes textual content (posts and comments) as well as counts of likes and shares.

 

  • Feed: returns the feed of posts (including status updates) and links published by the selected page, or by other users on the page.
  • Page: returns a single page
  • User Info: returns a single user - note - user identify / vanity id is used as the parameter

 

In the final video we close the loop on the last of the connectors by simply getting access to Facebook data:

 

Community page and video download

 

How to Get Started

 

While in your Qlik Sense Cloud Business workspace, you can set up your connections within your app by going into the data load editor and selecting the Create New Connection button. You’ll have to authenticate each connection using credentials from an account – your personal account, or one belonging to your business, group or organization. Once the connection is established, you can begin retrieving data.

 

5-2-2017 6-57-50 AM.png

 

4-28-2017 10-42-32 AM.png

 

 

We’re rolling out additional connectors in the next few weeks, so stay tuned for additional information!

 

Learn more


Of course check out the videos and for more detailed information and instructions, visit these resources:


Enjoy your day!

 

Denise LaForgia

Senior Product Marketing Manager

Qlik

 

Resources:

 

After reading Michael's wonderful post on the 3.2 features, https://community.qlik.com/blogs/qlikviewdesignblog/2017/04/04/introducing-qlik-sense-32?et=blogs.comment.created#commen…, I admit, I wanted to get into more details on each of the topics he mentioned. Even though this is impossible since there are so many goodies hidden in 3.2, I decided to focus more on the properties panel while creating custom extensions.

 

Some of these will make us retouch some of our extensions since, personally, I used workarounds like custom color in an input field as hex, inject dropdowns as html etc

 

Below I show the latest properties and at the end I attach an extension with everything working... Please note that, as the help pages suggest, some of these are "considered EXPERIMENTAL and may be subject to change or be removed in future releases."

For more details, please bookmark Qlik Sense Developer's help page

http://help.qlik.com/en-US/sense-developer/3.2/Subsystems/APIs/Content/extensions-api-reference.htm

 

SIMPLE TEXT DESCRIPTIONInteger
2017-04-28 23_07_23-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png2017-04-28 23_08_10-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png

text: {

    label:"This is a description for the properties panel (Text Component)",

    component: "text"

},

fontSize: {

    type: "integer",

    expression: "none",

    label: "Font Size (Integer)",

    defaultValue: "10",

    ref: "vars.fontSize"

},


 

INPUT TEXTBUTTON
2017-04-28 23_09_25-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png2017-04-28 23_09_40-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png

inputText: {

    type: "string",

    expression: "none",

    label: "String (Input Text)",

    defaultValue: "This is a test app to checkout custom properties",

    ref: "vars.inputText"

},

button: {

    label:"My Button (Button Component)",

    component: "button",

    action: function(data){

        alert("My visualization extension name is '"+data.visualization+"' and have id '"+data.qInfo.qId+"'.");

    }

},

 

BUTTON GROUPHeader 2
2017-04-28 23_09_54-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png2017-04-28 23_10_06-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png

weight: {

    type: "string",

    component: "buttongroup",

    label: "Font Weight (Button Group)",

    ref: "vars.weight",

    options: [{

        value: "bold",

        label: "Bold",

        tooltip: "Select for Bold text"

    }, {

        value: "normal",

        label: "Normal",

        tooltip: "Select for normal text"

    }],

    defaultValue: "normal"

},

show: {

    type: "boolean",

    label: "Show extra div? (boolean)",

    ref: "vars.show",

    defaultValue: false

},

 

COLOR PICKERDROP DOWN
2017-04-28 23_10_14-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png2017-04-28 23_10_24-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png

colorPicker: {

    label:"Background (Color-picker)",

    component: "color-picker",

    ref: "vars.color",

    type: "integer",

    defaultValue: 0

},

dropDown: {

    type: "string",

    component: "dropdown",

    label: "Select Options (dropdown)",

    ref: "vars.dropDown",

    options: [{

        value: "option1",

        label: "Option 1",

        tooltip: "Select for Option 1"

    }, {

        value: "option2",

        label: "Option 2",

        tooltip: "Select for Option 2"

    }, {

        value: "option3",

        label: "Option 3",

        tooltip: "Select for Option 3"

    }],

    defaultValue: "option2"

},

 

LINKSLIDER
2017-04-28 23_10_40-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png2017-04-28 23_10_59-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png

link: {

    label:"http://help.qlik.com/en-US/sense-developer/3.2/Subsystems/APIs/Content/ExtensionAPI/property-definition-link.htm",

    component: "link",

    url:"http://help.qlik.com/en-US/sense-developer/3.2/Subsystems/APIs/Content/ExtensionAPI/property-definition-link.htm"

},

slider: {

    type: "number",

    component: "slider",

    label: "Letter Spacing (Slider)",

    ref: "vars.slider",

    min: 1,

    max: 10,

    step: 1,

    defaultValue: 1

},

 

RANGE SLIDERSWITCH
2017-04-28 23_11_07-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png2017-04-28 23_11_14-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png

rangeSlider: {

    type: "array",

    component: "slider",

    label: "Range slider",

    ref: "vars.rangeSlider",

    min: 1,

    max: 20,

    step: 1,

    defaultValue: [8, 17]

},

switch: {

    type: "boolean",

    component: "switch",

    label: "Show Border (Switch)",

    ref: "vars.switch",

    options: [{

        value: true,

        label: "Show"

    }, {

        value: false,

        label: "Hide"

    }],

    defaultValue: false

},

 

TEXT AREAARRAYS
2017-04-28 23_11_23-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png2017-04-28 23_11_40-Helpdesk Management - Google Charts _ Sheets - Qlik Sense.png

textarea: {

    label:"Textarea",

    component: "textarea",

    rows: 7,//the amount of rows in the textarea component (default is 3)

    maxlength: 100,//will not allow more than 100 characters

    ref: "vars.textarea",

    defaultValue: "This can be your fottnote/legend to your visualizations"

},

MyList: {

    type: "array",

    ref: "listItems",

    label: "List Items",

    itemTitleRef: "label",

    allowAdd: true,

    allowRemove: true,

    allowMove: true,

    addTranslation: "Add Item",

    items: {

        label: {

            type: "string",

            ref: "label",

            label: "Label",

            expression: "none"

        },

        textarea: {

            label:"My textarea",

            component: "textarea",

            maxlength: 100,//you shouldn't write too much

            ref: "myTextarea"

        }

    }

}

 

Attached find the extension.

 

Yianni

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