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Business Discovery Blog

22 Posts authored by: Elif Tutuk

Yesterday we announced QlikView 11.2. The main new capability in this release is QlikView Direct Discovery. Since we announced this new capability in October, we have seen great excitement in our customer and partner community as they see the potential of QlikView 11.2 enabling Business Discovery with Big Data, without any data size limitations.

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Today organizations have the capability to store and process more data faster and cheaper than ever before. Currently, Big Data sources such as Hadoop are thought of as a sort of “staging environment on steroids”—a place to stage and dump a massive amount of stuff.

But as I talk with our customers about Big Data, I keep asking myself, is the more the better? The fact that IT can now store petabytes of data does not mean much to business users unless the business users can benefit from greater relevance. Until business users can seamlessly analyze Big Data along with their other decision support data, asking and answering their own streams of questions (even questions no one anticipated they might have—without having to go back to an expert for a new report or a new visualization), the more does not bring any value to them.

With a single QlikView app, even the least technically savvy person can answer question after question after question, moving along their own path to insight. Users are empowered to explore information freely by clicking on field values, doing searches, and more.

The Direct Discovery capability of QlikView 11.2 brings the same unique Business Discovery capabilities to analysis on Big Data. QlikView Direct Discovery is a hybrid approach that leverages both in-memory data and data that is dynamically queried from an external source. QlikView maintains all the associations in the data, regardless of where the data is stored.

For example, a policy analyst who uses a QlikView app to analyze regional loss and revenue information on a daily basis can now also see the policy-level claim payments for billions of policies (stored in a Big Data system) in the same QlikView app. He does not need to remember policy numbers, he only needs to select the regional info, as he would do every day, and QlikView displays policy-level information from Big Data sources in the same app as in-memory metrics.

With QlikView 11.2, QlikView once again conquers the hearts of business users and IT pros alike—this time by making Big Data user friendly. QlikView Direct Discovery makes IT organizations Big Data heroes. With the rapid and easy development of QlikView Direct Discovery, IT can now make Big Data sources available in existing QlikView apps in mere days and let business users incorporate that data into their Business Discovery. In addition, with QlikView’s Data Governance Dashboard, they can see how the existing enterprise data is being used with the new big data sources. This knowledge of high use data will allow IT people and data administrators to build a more comprehensive enterprise data roadmap. They can easily identify the usage patterns, metrics definitions within the QlikView environment and decide how to position big data and enrich their existing enterprise data sources with big data if necessary.     

The value of the Big Data will not be explored by the pre-determined path of questions.  With Big Data, the business users need to follow the information scent, and be able to ask and answer streams of their own questions to find what is relevant to them. QlikView 11.2 opens a new area for QlikView where the unique Business Discovery capabilities will enable users follow the information scent and chase the value from the Big Data.

On Tuesday, we announced a new QlikView capability, QlikView Direct Discovery. QlikView Direct Discovery will be part of the QlikView 11.2, which is targeted for availability in December. I am very excited about QlikView Direct Discovery because it will expand the potential use cases for Business Discovery and enable business users to analyze Big Data from sources that have not yet been tapped for knowledge and insights.

QlikView Direct Discovery provides QlikView’s associative experience on top of data coming directly from external big data sources and enables users to combine that Big Data with data stored in memory. What’s really special here is that with this unique hybrid approach business users get the QlikView associative experience even with data that is not stored in memory. This is amazing! With Direct Discovery, business users will be able to explore and analyze any data that is useful for analysis. 

QlikView Direct Discovery focuses on the real need of business users: finding what is relevant in Big Data and being able to explore that data in context with other enterprise data, identifying the relationships in the data – seeing what is connected and what is not – to derive insights and make decisions.

With Direct Discovery, business users will be able to:

  • Analyze in-memory data and data stored in a Big Data back end together, even on the same chart.
  • Explore Big Data freely rather than being confined to a predefined path of questions.
  • Seamlessly analyze data from multiple sources together within the same interface, including Teradata, SAP, Facebook, Google BigQuery and others.
  • Associatively make selections in any of the data sets (in-memory or Direct Discovery) and always see what is associated and not associated with the same meaningful QlikView colors: green, white, and gray.
  • Leverage QlikView’s collaborative and mobile capabilities for Big Data analysis.
  • Conduct visual analysis against massive volumes of data without a complicated ETL (extract, transform, and load) process and lengthy development effort.

We are very excited about enabling business users to tap into Big Data sources and to experience that data in context, with the QlikView associative experience. If you are also excited, stay tuned for more in December!

For more information about QlikView Direct Discovery see the data sheet and FAQ. We are expecting to make the beta version of QlikView 11.2 available on QlikCommunity in early November.

Last week we announced that QlikTech joined the Google Cloud Platform partner program. This program aims to help technology providers use and build solutions upon Google’s cloud platform. Taking advantage of this new partnership, QlikView customers and partners can create Business Discovery apps and solutions that take advantage of the power of the Google cloud infrastructure.

A great example of QlikTech working with the Google Cloud Platform is the QlikView Google BigQuery integration (see videos below).

 

In partnership with Google, we created a custom connector and an extension object providing seamless integration between QlikView and the BigQuery platform. Google BigQuery enables developers and business users to quickly and easily gain business insights from massive amounts of data without any hardware or software investments. (I wrote about our BigQuery integration in this earlier blog post: “Insight from Big Data with QlikView and Google BigQuery.”)

At QlikTech we team with leading technology vendors such as Google to provide our customers with powerful, integrated Business Discovery capabilities. We are thrilled with our technology partners as we collaborate with innovators who share our belief in simplicity and self-service. These integrated solutions help us achieve our mission: Simplify decisions for everyone everywhere!

Last month Google announced the public launch of Google BigQuery, a service to bring Big Data analytics to all businesses via the cloud. Google BigQuery enables developers and business users to quickly and easily gain business insights from massive amounts of data without any hardware or software investments. With Google BigQuery, users can run ad hoc, SQL-like queries against datasets that contain billions of rows.

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QlikView Google BigQuery demo application (http://Qlikview.com/bigquery)

Last week we created a QlikView demo app showing an example of QlikView integrated with Google BigQuery. The demo app contains birth record data for all babies born in the U.S. between 1975 and 2004. Users can interact with huge amounts of data in a simple, visual way, asking questions like, “What is the average age of mothers now vs. in 1975?” The app churns through millions of rows of birth record data stored in BigQuery in mere seconds.

The demo app provides seamless integration with BigQuery using two QlikView capabilities:

  • A custom connector. QlikView developers can use the QlikView BigQuery connector to load BigQuery data into QlikView’s in-memory data model so business users can remix and reassemble it in new views and create new visualizations on the fly. Users can make selections in the data and see what data is associated, and what data is not.
  • An extension object. For massive sets that are too big to fit in memory, even when compressed, QlikView developers can create an extension object to directly query the BigQuery database. Business users can interact with the BigQuery data by making selections in list boxes to get just the relevant cut of the data they need in a user-friendly chart or graph, without creating a single line of SQL code.

People at work are constantly being challenged to efficiently access, filter, and analyze massive amounts of data. This demo shows how QlikView, integrated with Google BigQuery, can provide Business Discovery for business users who want to find insights in very large data sets. With QlikView’s unique associative experience, business users can navigate and interact with the BigQuery data any way they want to, asking ad hoc questions as they come to mind.

The QlikView integration with Google BigQuery enables non-technical and non SQL-savvy users to interact with billions of rows of data in seconds. They can navigate through the massive amounts of data to find what’s relevant to them, and to get answers to their specific business questions without requiring specialized skills.  

Predictive analytics exploit patterns found in historical and transactional data to help people identify risks and opportunities in their business. According to Gartner*, predictive analytics is of great interest to many organizations, but only a small percentage of organizations have made significant progress deploying it.

 

With such shining promise, why are many organizations yet to employ predictive analytics to improve their businesses? There are three main reasons for this:

  • Users are confused about what “predictive analytics” means. Generally, the term predictive analytics is used to mean predictive modeling, scoring data with predictive models, and forecasting. However, people are increasingly using the term to describe related analytical disciplines such as descriptive modeling and decision modeling or optimization. These disciplines also involve rigorous data analysis, which is widely used in business for segmentation and decision making but has different purposes and the statistical techniques underlying them vary.
  • It’s complicated. Predictive analytics stirs together statistics, advanced mathematics, and modeling, and adds a heavy dose of data management, to create a potent brew that many hesitate to drink. Many organizations do not know whether predictive analytics is a legitimate business endeavor or an ivory tower science experiment.
  • Business users are left out of the picture. In our view, this is the most common barrier to adoption. The tools and techniques for predictive analytics are relatively mature; however, business users do not know when and how to use them. Use of tools and processes for building predictive analytics and deriving insights from the data have been limited to a small number of highly trained and experienced statisticians and analysts. Business users are only end users who passively consume what others produce for them.

We believe that predictive analytics needs to be more pervasive to deliver significant value and competitive advantage to organizations. Predictive analytics should be part of a decision making process in which the predictive terminology should be familiar to the business users. The essence of predictive analytics is to predict a number, a category, or propensity. Business users should be able to use this functionality without memorizing algorithm names.

We think that the future of predictive analytics lies not only in statistical models predicting the future, but in the human aspects of prediction. A model may predict that 68% of potential buyers of a new product are college students, for example, but if 68% of your existing customers are college students, then this prediction doesn’t help the business a whole lot. Success requires that business users who have a deep understanding of the business, know the nature of the data, and know how to interpret the results own the process.

The bulk of the work in predictive analytics is in understanding the relationships in the historical data and using them to predict the future. The QlikView associative experience is a perfect fit for understanding relationships in historical data. It gives business users the flexibility to ask and answer their own questions and identify patterns and outliers in the data.

By using QlikView integrated with a third-party predictive analytics tool, users can get these same benefits with predictive analytics. This video shows a solution example that integrates QlikView with R, which is an open source language and environment for statistical computing and graphics. In this example, business users can conduct business discovery as they normally would with selections in QlikView. When they find an interesting data set they can click on a button that transfers the selected data set to R. R calculates the desired predictive analytics and the result set becomes part of the QlikView’s associative in-memory data model upon which the user can do further exploration. 

Gartner indicates that making advanced analytics available to an expanded set of users will require a new consumer-oriented approach. The analytics should be available at the point of the decision. The tools need to become more consumer-oriented, social, collaborative, and mobile. These characteristics are core to QlikView and with QlikView’s integration capabilities, business users can now do predictive business discoveries, expanding the Business Discovery horizon to the future!

 

 

*Source: Gartner Advanced Analytics: Predictive, Collaborative and Pervasive Report, February 2012

One of the core strengths of QlikView is its simplicity. QlikView is simple to install and use, and it’s simple to create Business Discovery apps. QlikView’s simplicity enables business users to make better, faster business discoveries. Users can ask their own questions and get answers with the simplicity of a mouse-click. This simplicity also opens the door to innovation, such as motion sensing input with Microsoft Kinect.

Kinect* is a motion sensing input device. It enables users to control and interact with the Microsoft Xbox 360 without the need to touch a game controller, through a natural user interface using gestures and spoken commands. I have seen many examples of people hacking Kinect to interact with other devices through body gestures, but this one really impressed me as it involves QlikView!

Project Brokers, a QlikTech partner, developed a QlikView solution for integrating Kinect with QlikView so users can control QlikView apps using their body movements. In this video, Adam Vaughan, senior consultant at Project Brokers, demonstrates the solution. He uses his hands to perform mouse actions as he interacts with QlikView.

Project Brokers did an exclusive demo of this solution at the QlikTech Business Discovery World Tour event in London. Vaughan said that response to their demo was overwhelmingly positive.  He believes accessing and manipulating data via the Xbox Kinect will be part of a growing trend toward QlikView users managing their Business Discovery needs in an intuitive way.

When I saw the solution, I first thought about Tom Cruise in the film+ Minority Report+, where he faced a large display and interacted with the information by his hands. Not only is the solution interesting and fun, but the Kinect integration also has the potential to be extremely effective in places where users do not have a mouse or other device to interact with the PC, and can only use their hands. As an example, think about environments like hospitals or labs, where hygiene is extremely important and users are not supposed to touch a screen or use a mouse.

With solutions like Project Brokers’, we can truly enable business discoveries everywhere. And QlikView’s simplistic user interaction capability already enables this!  

 

* [http://en.wikipedia.org/wiki/Kinect | http://en.wikipedia.org/wiki/Kinect]

Have you ever wondered about when your older kid will start babysitting the younger one? Think about the advantages; they already know each other and the “system” in the house. The older one can provide this service for free (or at least you hope they will). This is what I think about the QlikView System Monitor/Server Performance app; QlikView can babysit QlikView for IT admins!

Monitoring app.PNGFor IT administrators, monitoring systems is important to avoid difficult situations. The QlikView System Monitor/Server Performance app is a free QlikView app — you can download it from QlikCommunity. This app provides 360 degree monitoring of the QlikView environment. It provides information on system usage, QlikView app usage, licensing, data refreshes, Publisher tasks, and more. With this QlikView app, IT admins can more easily conduct daily — even hourly — checks, which can prevent anything serious -such as high RAM and CPU consumption, Publisher tasks failures etc…-  happening in the system. QlikView System Monitor/Server Performance leverages all of the ordinary QlikView functionality, such as associative search, visual clues, alerts, trend analysis, and an endless array of visualization options.

The latest version of the app was developed by Michael Terenzi, a QlikView support technician at QlikTech. Here are some highlights from the new release:

  • QlikView Directory Service, QlikView Web Service, Internet Information Services (IIS) Web Server, QlikView Management Service, SAP Connector, SalesForce Connector and Publisher logs are all incorporated into the app, providing a full overview of what is going on with the system.
  • It supports clustered environments and provides information on each node in the QlikView cluster.
  • QlikView audit log statistics are linked to QlikView session information, giving IT admins a better understanding of which user is doing what, and when.
  • The app contains quick links to our customer and partner portals, as well as a link to email QlikView support.
  • The app contains links to the new QlikView Power Tools (a free package of utilities designed to help QlikView developers and IT admins use, troubleshoot, and extend QlikView functionality).
  • The app is mobile ready. IT administrators can use the app from the mobile device as well as from their desktop. They can monitor the system from anywhere, anytime!

If you are not already using QlikView System Monitor/Server Performance app, you can download it here. Let QlikView babysit QlikView for you!

Elif Tutuk

QlikView “Aha!” Moments

Posted by Elif Tutuk Mar 16, 2012

I was thinking about why developers become so addicted to QlikView after they start using it. Why did I become a QlikView addict? My reason is that QlikView gives users a moment of clarity, an “aha” moment, while they are creating apps. QlikView lets them use the features that they already know in different ways where they gain new wisdom to use their curiosity and creativity.

 

 

I decided to list and share some of my QlikView “aha” moments with you. The list has some simple and some advanced capabilities. The video is a quick run-through showing some of them in action.

  1. Drag and drop to open a QlikView application:
    • Drag and drop a QlikView application (qvw) file into the QlikView Developer client to have it opened.
  2. The power of gray and selections:
    • With QlikView, users can literally see relationships in the data. They can see not only which data is associated with their selections, they can just as easily see which data is not associated. This generates new insights and unexpected discoveries.
    • With a right click, they can reverse their analysis by selecting the non-associated data (select excluded).
    • By using the “show alternatives” option on list boxes, the user can get further insight on the data values that are related to the selection state besides the green value.  When a selection is made on a list box, the selected value is highlighted in green and all of the other values are highlighted in grey. If the user would like to get insight on the data values that are still relevant with the selection state in addition to the green value, they can check the “show alternatives” option and can get insight on all of the relevant values in addition to the selected value.    
    • The user can move between selected values in a list box by using the down arrow on the keyboard. As the selection changes with the down arrow pressed, the charts recalculate on the fly and the user sees changes in the data. 
  3. List box with expression:
    • The user can create new data selection points by creating a list box with an expression. For example, the expression can define the sum of sales at the customer level. The user can then make selections on these new data points to do further analysis.
  4. Calculated dimensions:
    • The dimension values on charts do not need to exist in the data model; new data points can be created and used as dimension values on charts. For example, in a chart showing the inventory quantities by the number of weeks, the number of weeks is a calculation that is used as dimension values. 
  5. Bookmark:
    • In QlikView, the current state of selections can be saved as bookmarks for later use. To create the bookmark, QlikView does not store the actual data values; it stores the criteria that are used while the selections are made (the filters the user applied). If the selection criterion is an expression, let’s say “top 15 products,” QlikView will store the expression and when the data refresh happens, the updated top 15 products will be displayed when the bookmark is selected.  
  6. Document chaining:
    • With document chaining, it is possible to open one QlikView application from another QlikView application and carry the selection states from the first to the second application.
  7. Power of in-memory data transformation:
    • QlikView provides tons of functionality to transform data in memory. It is possible to create new tables, and new fields in memory to use them in Business Discovery. Please see the script syntax part of the QlikView reference manual document.
  8. Data exploration:
    • On the table viewer, when hovering with the cursor above the fields, users can get information about the data density and subset ratio to understand any data integrity issues. The number of selected values vs. all of the values is displayed on the right bottom part of the QlikView screen.
  9. Binary load:
    • With binary load, it is possible to load the in-memory data model from one QlikView application to another one. Binary loads are very fast. It is possible to do further in-memory data transformation on the data after the binary load.
  10. Search:
    • QlikView allows search not only by actual data values but also by new data calculations. For example, the user can type “=rank(sum(Sales)) <=5” on a product list box. This would select the top 5 products based on sales. The same type of search can be done on a search box. In that case, QlikView not only will display the top five products but also all of the associated data (e.g., sales people, regions, price, etc. . . anything related to these five top products). Pretty powerful! 

These aha moments are some of the “unlisted” benefits of QlikView. Although people have different experiences in their lives that would result in “aha” moments, only QlikView users will experience all of these aha moments while doing Business Discovery or creating Business Discovery apps!

I was at a party last weekend and I realized cheese and crackers is my favorite combination of food. The combo serves as a great snack, especially for get togethers. It is easy to make. This is a food combination loved by both rich and poor, whether you put cheap old cheese on store bought crackers, or the finest truffle laced mature brie onhand made crackers. Then I started thinking about my favorite QlikView 11 features combo.


Which QlikView 11 features when combined together will be easy to develop, unbeatable both for the power users and the business users and would lead users to unexpected business discoveries? My match in heaven for QlikView 11 is Comparative Analysis and Conditional Enabling! And here is why.

Comparative Analysis is a QlikView 11 feature enabling comparison of multiple data sets in a QlikView application. It is a user driven feature. It gives the flexibility to business users to define the values that make up the data sets and visually compare them. Conditional enabling provides the capability to define the content of a QlikView chart on the fly. By using this feature, the developer can define conditions to enable the dimensions and the metrics on the chart.

What happens when you combine them? Users can pick dimensions and metrics to create their own analysis. Based on what they discover with this new and personal analysis, they can create new data sets and assign these data sets to groups to further analyze them in other charts. Don’t you already feel like you are in business discovery heaven?  

The combo is easy to develop as can be seen in the video.  The QlikView application is also attached to this blog. It is simple enough to be used by business users and analytical enough to ease power users’ lives. The combo of comparative analysis and conditional enabling leads to unexpected business discoveries because users can create their own data sets with any dimensions and metrics values and can visually compare them for business discovery.  

Comparative analysis and conditional enabling is my combo QlikView 11 features to be the match in heaven, what is yours?



We need information in every aspect of our lives. We search for information when we want to see a movie, when our kids are sick and we need a doctor, and when we want to compare prices while buying electronics. QlikView, with its user-friendly associative experience, can be used in our daily lives to help us filter information and quickly get to what’s relevant.

This video shows a housewife who needs to buy cheesecake from a grocery store. She’s in a rush. She uses “Quick Finder” to find the location of the cheesecake in the store. You can find the QlikView application and the extension object used in the video in here.


The idea for this was born out of a recent shopping excursion. I was doing my grocery shopping at a store that I was not familiar with. After spending many minutes walking down aisles to find things on my grocery list, I started thinking how nice it would be to have a QlikView application that could show me the location of products. I thought about a QlikView extension object that would show me the floor plan of the grocery store and as I selected products, with the location of the product highlighted in color on the floor plan. Maybe it could be made available to shoppers via a tag barcode.

I got excited about the idea of a “Quick Finder” application so I went home and created one. It took me a few hours to develop the QlikView application. I turned on an Amazon EC2 instance in the cloud and put my app on a QlikView 11 server in the cloud. I created a tag with the URL of the QlikView application by using Microsoft Tag Manager. This way, shoppers could use the free tag reader app on their smart phone and the app would automatically open the QlikView application.*

People’s phones are an essential part of their daily life, connecting them to their entire world of information. Using recognition technologies, we can make virtually anything “Qlikable” to enable people to use a Qlikview application from anywhere to find the information they need. QlikView’s extensible and flexible platform can be used with recognition technologies and provides innovative ways of using QlikView in our daily life.

Our goal at QlikTech is to touch the life of one billion users. I believe QlikView is such a flexible product that with this type of innovative use we would help billions of users, including desperate housewives in grocery stores!

* Tag barcodes and quick response (QR) codes are recognition technologies. Companies use them to connect customers to information, entertainment, and interactive experiences via their smart phones.

A couple days ago, we were talking about Siri at lunch. Siri is the intelligent personal assistant that is available on iPhone 4S. It helps you get things done just by asking by using your voice to send messages, schedule meetings, place phone calls, look up information, and more. After that lunch conversation, I started to think how nice it would be to have a personal assistant in QlikView, one that would allow me to use my voice to do Business Discovery. I’d like it to talk back to me and guide me through the data to reveal the informationI need for decision making.

Then I started thinking that QlikView already has all of the pieces needed to get this working. It has extension objects capabilities, which can run custom code from QlikView to get the voice commands working. It also has text box capabilities to automatically generate the voice script with the data for the assistant’s audio. I thought about using free text to speech software to convert the text to audio.

So I did a little research on HTML5 and sat down with QlikView. Within about two days, I built a prototype. I got so excited about it that I gave my personal assistant a name: “Q.” Check out this video. I posted the QlikView application and technical information about creating the speech input and audio extension objects with HTML5 on QlikCommunity.


 

“Q” is a great example of QlikView’s extensible platform. QlikView provides developers with a comprehensive and integrated set of tools that help them expand the possibilities of a Business Discovery application. If developers are interested in adding speech input capabilities to a QlikView application, they can easily create an extension object by using QlikView Application Programming Interfaces (APIs) and other technologies such as HTML5. Once the extension object is created, it can be used in other QlikView applications, just like any other QlikView object. If you are interested in learning more about QlikView’s extensibility, please visit the QlikView SoftwareDevelopment Kit (SDK) page on QlikCommunity’s Integrations and Extensions Community. The community provides documentations on QlikView SDK and APIs with sample codes.

By the way, if you are wondering what else “Q” can do, I am leaving that to your imagination. With QlikView APIs, it would be very easy to put the pieces together!


This week I did a QlikView demonstration with the purpose of showing QlikView’s self-service BI capabilities. I was tasked with loading a data set and building an analysis user interface. When I opened the demo data file for the first time, I saw that some of the column names were actual data points and needed to be changed to row values to be used in the analysis. The data had a cross table structure and needed to be transposed.

As a former QlikView technical expert, as I started to become familiar with the data, my right brain was already thinking about the data load design and scripting to transform the data but all of a sudden my left brain took over and said, “Stop! There is a wizard to do this!”

After a couple of minutes, I transposed the data by using the crosstable wizard. The following video shows the use of this wizard and shows how to build a QlikView application from start to end in four minutes.

I guess our background always plays an important role on how we use the technology. The reason I loved using QlikView when I was a developer was the power it provided me to transform the data with the scripting capability of the data load editor. QlikView provides a purpose built in-product ETL (extract, transform, load) interface and script API to enable powerful manipulation of data. The interface provides auto-complete, debugging, and wizard functionality. Although there are data load and transformation wizards, I tend not to use them. I guess the developers always aim to write the coolest script without following the steps provided by the wizards as they become familiar with the software. The same is true for other technologies, for example, people use keyboard commands instead of mouse clicks or they use a command line interface instead of a graphical user interface. But I learned my lesson this week: wizards really make development simple and faster, even for experienced QlikView developers!

 

The bicycle was invented in 1817 by Baronvon Drais. He envisioned it as a walking machine to help him get around the royal gardens faster. It featured two same-size in-line wheels,mounted to a frame which he straddled. He propelled the device by pushinghis feet against the ground, thus rolling himself and the device forward in a sort of gliding walk. The bike was made of wood, which made it very heavy. There were no pedals, so forget about going uphill. And without brakes, going downhill was probably challenging. His invention enjoyed a short lived popularity as a fad, not being practical for transportation in any place other than a well maintained pathway such as in a park or garden.

When I read about this first attempt at building bike, I thought about traditional BI tools. The way traditional BI tools enable data analysis is similar to Baron von Drais’s bike; the data can only be analyzed with predefined drill down paths or by running queries one at a time, so business users are limited to a “well maintained pathway” to do analysis. BI was introduced 25 years ago at a time when storage, memory, and computing resources were scarce. In many cases, the same query -or cube- based technologies are still being used today. In these cases, business users do not have freedom to analyze the data in their way.

Bicycle2.png

Image source: Wikipedia. Link here: http://en.wikipedia.org/wiki/File:Draisine_or_Laufmaschine,_around_1820._Archetype_of_the_Bicycle._Pic_01.jpg

When I thought about today’s modern bicycles and their ease of use to go anywhere, I realized that QlikView is the bicycle of business intelligence! With QlikView’s associative experience, business users can enjoy their own journey through the data. They can literally see the relationships in the data, because with every data point selected in their analysis, an entire network of data, and relationships between them, is implied. An associative search returns data that represent things that are related as well as not related, via various forms of associations that exists in the data. An associative search looks through a network of associations for the things that are connected to users’ selections, and guide them quickly home in to the unknown unknowns that are hidden in the data. With cube or query based technologies on the other hand, each additional search term only provides a linear benefit, there is no exponential amplification using networks that exist in the data.

Two centuries later after the first bike attempt, children all around the world learn to ride a bike and have fun. So my question is: shouldn’t business intelligence be easy and be for everyone just like riding a bicycle? I think so!

 

* Source: About.com. Link here: http://inventors.about.com/library/inventors/blbicycle.htm

QlikView makes enterprise BI personal to each business user. Probably you are now all thinking about the term ““self service” BI or “ad-hoc” analysis as I mention “personalization.” What I mean by personalization with QlikView is more than these. With QlikView, business users can interact with the data in their own way, create their own analysis context, change visualization and navigate in the analysis based on their preference. This video walks you through the scenario that I cover below demonstrating QlikView capabilities enabling personalization.

 

 

Let’s think about a business analysis scenario and go through the steps to personalizing it with QlikView.

 

Analysis Scenario: Sales Analysis by Region, Product and Time


  • Step 1: Select metrics and dimensions.Organizations use many metrics to measure the sales performance: sales amount, margin, net sales, etc . . . With a traditional BI approach, IT group or power users create reports with some of these metrics with pre-defined drill down paths (e.g., product group, product category, month, state, etc.) based on the requirements that they collected from a group of business users. Based on the combination of the metrics and breakdowns required, there may be tens of reports available to any given user. But what if the user’s analysis needs are different or have changed? With QlikView’s conditional enabling feature, business users can create their own personalized analysis on the fly by just clicking on dimension and metrics names. With QlikView, all of the aggregations are done on the user interface on the fly so there is no need to “execute” this new analysis, as would be the case with a traditional query-based tool. As user executes clicks, they see the chart coming to life before their eyes, with their selected dimension(s) and metric(s), in real time with no wait.
  • Step 2. Select data values. Once business users create a personalized chart, perhaps the next thing they would like to do is drill down more on this new analysis to look for specific products, time periods, etc. With QlikView’s associative experience, business users can navigate through the analysis, applying filters by just clicking on data values.
  • Step 3. Select visualization type. Different types of analysis require different types of visualization. As business users personalize their analysis with conditional enabling in real time, they can also change the visualization type on the fly with QlikView’s fast change capability, available on charts.
  • Step 4. Socialize the personalized analysis. Once business users discover new insights on their personalized analysis, they can fire up a real time collaborative session and invite others to immediately interact with the new analysis. Or they can create a bookmark and share the bookmark with others. Bookmarks include the selections the user made and when others open the bookmark, QlikView automatically recreates that personalized analysis on the fly.

 

With QlikView, personalizing the business analysis and creating your own discovery is just few clicks away. No drapging and dropping, no wait time to execute the new analysis, and no force-fed drill down paths, just Qliks!

In today’s fast moving competitive environment, every minute counts when business users see an opportunity and want to make a fact-based decision on that opportunity by analyzing data.  The term “analysis latency” describes the time taken to analyze the data and turn it into actionable information. Analysis latency could be a good measure of ROI on BI investments.

Analysis Latency.PNG

With traditional BI solutions, because business users highly rely on IT department to make changes to analytics, it is very challenging to decrease analysis latency. In these environments, the ratio of business users to IT staff determines the backlog and time it takes to make needed changes. (Please see my blog post, “Traditional BI in Babushka Doll,” where I discussed some of these shortcomings.)

With its rapid analytics app platform, QlikView users are already ahead in this game.  With the new QlikView 11 features, we are empowering business users and developers to act even more quickly as business dynamics change.

 

New Rapid Analytic App Platform Features in QlikView 11

QlikView 11  enables business users and developers to build apps quickly and painlessly with a bunch of new capabilities:

  • Granular chart dimension control enables developers and business users to create meaningful comparisons among dimensions more easily. Would you like to see the products that make up 80% of your sales? Or the top x sales reps? With this new capability, the answers to these questions are just a couple clicks away.
  • Conditional enabling of dimensions and expressions gives developers the flexibility to change the context of QlikView charts based on a user’s action, selections, role, or underlying data conditions. With this new capability, business users can create their own ad hoc analysis with any dimensions and expressions by just picking them.
  • Improved Ajax dialog boxes makes creating QlikView objects easier than ever before, especially for non-technical users.
  • Metadata is exposed in more places so business users can get an explanation of the content and context of chart elements more easily.
  • Version control integration creates an interface to connect QlikView applications to a source control system such as Microsoft Team Foundation Server. With this new capability, developers and administrators can improve the efficiency of application development by accessing and utilizing a central source control system.
  • Document extensions enable developers to execute custom code in QlikView applications. A developer could, for example, track usage patterns of a QlikView application by interfacing with Google Analytics.

 

The focus of the QlikView Business Discovery platform is on enabling decision makers at all levels of an organization to make decisions at the speed of business. With these new QlikView 11 capabilities, this happens even faster!

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