An increase in the demand for user-driven BI
● The prevalence of 64-bit hardware and software
With these trends, the ever-decreasing cost of server hardware and RAM, and a proven stable platform, QlikView was able to show the corporate user that big-company analytics didn’t have to be slow, cumbersome, and static. QlikView made it possible for some development to be done out in the business units and departments, instead of IT. This allowed organizations to control the pace of development, to better match the speed at which requirements were changing. The genie was out of the bottle.
Data Discovery Is the New Black
In the past, business users had to predict what questions they would ask so that IT could build a report to provide the answers. Lots of resources went in to researching and writing down what the business needed out of the BI system. IT was keen to have the business sign off on exactly what it wanted before the tedious and expensive efforts of development began. Of course, the problem with that approach is that the business was likely communicating requirements that it had in the past, not necessarily requirements that it anticipated for the future.
In classic “chicken-or-the-egg” form, IT would ask, “How do you want to see the data in your reports?” and the business would reply, “I don’t know; how can I see the data in the reports?” Being naturally very risk-averse, IT departments are not in the business of building applications as “suggestions” for the business, just to see what sticks. The risk is too great that the application could be rejected, and the project would be sent back to the drawing board having wasted precious time, resources, and reputations.
But the business has a valid question – “How can I see the data in reports?” means “What if my questions are ad hoc?” or “Can the system allow me to follow a path of ad hoc discovery, leading to previously undiscovered insight?” These types of questions require a robust analytical solution. No gigantic binder of month-end reports will serve this need. Static reports from BI systems are, in fact, the opposite of what is needed! Instead, analysis must be driven by the user, not the report-writer. This scenario exactly describes the concept of data discovery, sometimes referred to as business discovery. According to a 2013 report, technology research firm Gartner predicted that “by 2015, the majority of BI vendors will make data discovery their prime BI platform offering, shifting BI emphasis from reporting-centric to analysis-centric.” (This report, “Gartner Predicts Business Intelligence and Analytics Will Remain Top Focus for CIOs Through 2017,” is available on Gartner’s website at http://www.gartner.com/newsroom/id/2637615. More detailed information is available in the report “Predicts 2014: Business Intelligence and Analytics Will Remain CIO's Top Technology Priority” at http://www.gartner.com/document/2629220?ref=QuickSearch&sthkw=schulte%20AND%20BI%20AND%20%22predicts%22.)
Credited for pioneering the data discovery space, Qlik is well positioned to continue as a leader in this new market. With the release of Qlik Sense, Qlik is resetting the bar in offering user-friendly data discovery tools, while providing a well governed and scalable platform.
QlikView 11 Overview
For readers unfamiliar with QlikView or Qlik Sense, this section describes the core elements of the platform, and explains how it differs from traditional BI.
In-Memory Storage Means No Need for Pre-Calculated Cubes
Unlike OLAP systems, QlikView uses RAM as the physical storage medium for data. Since computers can access memory hundreds of times faster than disk, calculations and aggregations can be performed on the fly, with astounding speed. Thus, the limitations of building pre-aggregated cubes are gone! Figure 2-2 shows a data ecosystem with the addition of QlikView. Notice that QlikView can extract from multiple sources and does not require any pre-aggregated cubes.
Figure 2-2: QlikView in the data ecosystem
Using QlikView, transactional data can be loaded into RAM and then summarized at runtime, at the user’s request. If you’re used to the terminology of traditional BI, you can think of QlikView as creating “cubes on-demand,” from RAM. Transparent to the user, the aggregations occur seamlessly in the front-end, with each chart essentially creating its own cube. The benefit of loading the granular detail is two-fold: the data can be aggregated up to any level, and the user can drill down to view the details.
For the small or medium-sized organization, QlikView may replace the need for OLAP or other reporting tools. For the enterprise, QlikView is often added as a data discovery/analytics platform that works alongside OLAP systems – particularly if the organization still requires paper-based reporting.
An Interactive User Experience
A user accustomed to the traditional BI report interface knows that you need a game plan going in, before actually seeing any data. Typically, the user must select a specific report and provide the required parameters or filters before the report is run. QlikView completely rejects this approach, and instead presents the user with all of the available data, immediately accessible in the interface.
When a user opens a QlikView application, data is visible right away, without specifying any parameters. The user interacts with the interface to step through the data in an exploratory way, to zero in on specific results. Figure 2-3 shows a basic example of QlikView application containing sales data for an apparel company. You’ll use this data set, which is available from the book’s download site, throughout the book.
Downloading the Electronic Materials for This Book
If you haven’t done so yet, please download the electronic materials provided for this book. You can find the detailed instructions at the end of this book’s Introduction.
This is a screenshot of a typical QlikView application. Using a tabbed sheet layout, developers place objects on the sheet to allow for searching and selecting data and visualizing measures.
Figure 2-3: Example QlikView 11 application
In this app, a few filter objects called list boxes are shown across the top (Year, Quarter, Month) and down the left pane (Channel, Product, Season). Three visualization charts are shown: a pie chart, bar chart, and straight (non-pivot) table. The data in the charts reflect the entire data set, with no filters applied. In QlikView parlance, filters are called selections. The current state of the selections can be tracked in the Current Selections box, shown in the upper left.
Using a familiar tabbed sheet layout, this simple QlikView application invites the user to make selections to explore the data and click on the tabs to explore the layout. By default, selections made on one tab are persistent throughout the entire application (this behavior can be changed by the developer, depending on requirements). In Figure 2-4, the app is shown with selections applied for Channel and Season.
Figure 2-4: Filters applied in a QlikView 11 application
As soon as the user makes selections, the data in the charts dynamically update. No need to press Go, Generate, or Apply – results are rendered immediately. All visual objects in
