In the previous chapter, we outlined the Qlik Sense application life cycle, which provided an overview of the key Qlik Sense application components. This chapter's goal is to highlight key features in the context of the specific user requirements that Qlik has identified as defining a data discovery consumer.
In this chapter, we'll cover the following topics:
- Data discovery consumption requirements
- The hub
- Navigating and leveraging the associative experience
People's expectations of what technology should be and how it should work have been set high with the rise of mobile and touch devices. The notion of a fixed, predictable desktop has changed to a dynamic, unpredictable virtual desktop that exists on whatever device you have access to at the moment. This can include traditional desktop PCs running Windows, laptops, ultrabooks powered by Microsoft Windows, Apple Mac OS, hybrid devices running Windows 8.x, tablets, Chromebooks, smartphones… the list goes on. This new environment requires new approaches in both architecture and application design that create smarter applications to meet the demands of a broader access from varying devices. Qlik Sense was designed from the ground up to meet the diversity of requirements that now exist in your enterprise when it comes to delivering data to support decision-making.
Qlik Sense adapts to very different devices, including a laptop via Microsoft Windows, Apple iPad Air, and finally, an iPhone 5s, to name a few. The following screenshot shows the diversity of consumption by users today:
The key thing is that these Qlik Sense screenshots could have been taken using any device on the market. Critically, and uniquely, Qlik Sense uses Responsive Web Design (RWD), along with progressive disclosure to provide an optimal data discovery experience for users, whatever the form factor of the device. This is at the heart of the Qlik Sense architecture, the aim being to develop an app once and for it to be consumed/extended across any HTML5-compatible browser. For consistency and ease of illustration, the following key components of a Qlik Sense application will be illustrated from a laptop browser, but all these capabilities are available across tablets and smartphones as well. The following key Qlik Sense application components will be reviewed from a consumer perspective where the user has read-only access.
As noted in the application life cycle in the previous chapter, Qlik Sense provides a rich collaborative environment that is governed by the QMC through streams. Let's begin our review with the hub, which is the center of a data discovery community. The hub is a collection of streams, which contain Qlik Sense applications. Through the QMC, an administrator defines the streams, and Qlik Sense inherits security access to these streams and applications through security rules. Security rules are covered later in Chapter 9, Administering Qlik Sense®, and additional detailed examples are available in the Qlik Sense server user guide.
In this case, the consumer, let's call her Nora, has access to a default stream called Everyone as well as an administer-defined stream called BI Center of Excellence. The hub is designed for touch-friendly navigation (that is, it's designed to support selection and navigation using fingers!) between streams on the left-hand side of the display, searching and organizing the view in a number of sorted ways. Let's take a look at the hub:
Now, let's turn our attention to streams.
Streams are an organizing principle for applications as well as security. Qlik thinks of streams as work streams for information that can be categorized based on maturity with gradual expansion of access by audience, subject matter, or any other organizing principle. Nora has access to two streams, the Everyone stream, which is a public stream created during the server installation, and the BI Center of Excellence stream. The BI Center of Excellence stream contains a single application called Executive Dashboard. Executive Dashboard will be used to illustrate how Qlik Sense provides insights to business decision-makers.
Qlik Sense applications are made up of three main components, which include sheets, bookmarks, and stories. In the case of Nora, who has consumer access, each of these components have been defined by the application author and are identified by the label Approved. This label identifies these items as part of the core components created by the author and cannot be modified once published.
Sheets are a core building block of Qlik Sense. Each sheet contains a collection of objects that are arranged to provide context for analysis on a particular subject. In this case, the sheets are contained in the application called Executive Dashboard. Note that sheets fall into the following three categories:
- Base sheets: These sheets are defined by the author of the application and become read only after publishing. They cannot be modified but can be duplicated as a private sheet for modification.
- My sheets: These sheets are similar to community sheets but are unpublished, so they can only be viewed by the author.
- Community sheets: These are private sheets that have been defined by a user and published to the hub. These can be defined based on duplicated approved sheets and/or new sheets that are assembled through the use of the application library. This will be discussed in detail in the next section, Realties of data discovery power user.
In the case of the Executive Dashboard application, there are five approved sheets that cover key application areas: KPI Dashboard, Sales Analysis, Account Receivables Analysis, Inventory Analysis, and Product Analysis. Each of these sheets provide a baseline for the consumer's analysis and exploration.
Additionally, there are two community sheets, Pipeline Analysis and Inventory Variance Analysis, which were created by users who have contributor access rights. This is a power capability of Qlik Sense that allows users to share key findings across applications. Like base sheets and my sheets, approved sheets are stored with the Qlik Sense application.
Qlik Sense continues this popular feature, which was established in QlikView. Bookmarks allow a user to save the state of a sheet (their selections) so that they can be revisited at a future time, shared, and can be used to create data stories that allow users to combine key discoveries across many Qlik Sense sheets and add additional context through annotations. This example application contains four bookmarks as part of the published application.
The Approved bookmarks section includes the KPI dashboard for alcoholic beverages, Australia's sales analysis, convenience store account receivables, and convenience stores' inventory analysis for deli and alcoholic beverages. Qlik Sense consumers can create bookmarks to save key discoveries to view at a later date. Once interesting information is found, a user may wish to combine visualizations and add annotations that highlight any key discoveries. This leads us to our next topic, Data storytelling.
Qlik Sense Stories are a collection of snapshots of key findings (visualization objects) that are assembled to share insights with others in an organization. Snapshots are a graphical representation of the state of visualizations at a certain point in time and are stored in the story media library. Although snapshots are static, they contain embedded bookmarks back in the source sheet, which enables users (or people who want to debate the detail of a narrative) to continue the exploration with live data from the point at which the snapshot was taken. Like sheets and bookmarks, base stories (published with the application by the author) and community stories (published by users who have contributor rights) can be seen.
The Executive Dashboard application, shown in the preceding screenshot, contains four stories available for Nora to review. Community stories were published by Elif, David, and Pat highlighting product analysis, inventory analysis, and sales analysis, respectively. Additionally, there is an approved story named Application Overview, which was published as part of the application by the author to outline the goals and use of the application. It is a recommended best practice for application authors to include a story to spur the adoption of an application within the user community. This topic leads us to our next topic, Navigating and leveraging the associative experience, in which we will use the Application Overview story to provide an overview of the application.
As mentioned earlier, Qlik's intent in building Qlik Sense was to create a user experience that provides a natural and intuitive way to explore data and share key findings. To facilitate our discussion, we will refer to the Application Overview story. When selecting an application from the hub, Nora is provided with an application overview. This displays the application name, a short description, and a published date and time that provides key context for the timelines of the information.
Additionally, there are three key areas to explore in a Qlik Sense application; they include sheets (highlighted), bookmarks, and finally, stories, which were discussed earlier. This application contains both approved sheets (developed by the application's author) and community sheets that are the results of contributors who have published private sheets they wish to share with the community. This process will be discussed in detail in the next section.
Now, let's open the first sheet named KPI Dashboard. As discussed earlier, sheets are an amalgamation of smart objects that display information based on the amount of space available. In KPI Dashboard, we can see that the sheet is divided into three key areas: Expenses, Revenue vs Last Year, and Accounts Receivables:
Each of these objects can be used as a filter to see data association and just as importantly, to see nonassociated data (informally known as "The Power of Gray" based on its default coloring that users of QlikView have enjoyed for years). Additionally, each of these objects can be expanded to fullscreen, as shown in the next screenshot. The expense sparkline chart can be expanded to fullscreen to reveal additional data points and trends. This also facilitates viewing and selections on mobile devices, where screen real estate is limited.
As we review the Sales Analysis sheet, there are a number of innovative features that highlight the capabilities of Qlik Sense. First, let's review the sales margin versus sales revenue scatter chart. What makes this chart smart is how Nora interacts with it.
As mentioned earlier, Qlik Sense was developed for mobile devices, which implies touch interaction. In this case, the scatter chart supports multitouch selections on both the axes. In this example, Nora has selected to highlight the performance of sales representatives who have margins between 41 to 48 percent and sales between 3.69 million to 7.01 million. Additionally, these selections are in preview mode, which allows Nora to see the impact of these selections before confirming and moving on to the next phase of her discovery.
A second area to highlight is the use of smart scrolling noted in both the Average Sales Per Day area and the Total Revenue by Product Group horizontal chart. The scroll bars use thumbnails of the chart so that Nora can easily navigate to the key area for review. Additionally, scroll bars appear after the chart has reduced its size to a point where the entire dataset can no longer be shown in the allocated space within the sheet. This allows Nora to enter the numbers in a range selection within any chart, for example, the scatter—you can type in the exact number for the range filter. Also, you can move the filter range keeping the range as you scroll along the x or y axis.
Selections and filtering can also be accomplished through the Qlik Sense global search capabilities. This allows for contextual search to narrow down the search criteria without restarting the search, like other search engines. Using the power of the associative engine, Nora can type various products to preview their impact on revenue and any association between these products. In this case, the search was conducted on hot dogs and beer. Note that there is no specific query language needed or requirements to be formed in a specific syntax. Additionally, the result set is shown in preview mode, where the search can be appended and/or modified before commitment to these filters. This facilitates quick interrogation of the data and helps users make more insights.
To accompany global search, a fully structured approach to filtering is available on every sheet in the top right-hand corner called the global filter. In the global filter, we can see current selections in the top half of the sheet highlighted in green. The bottom half of the sheet is reserved for dimensions that have not been included in the filtering. Note the associated colors of green for selected elements, white for none selected, and gray for nonassociated elements. Light gray indicates excluded only by selection in the same field, whereas dark gray means excluded by selection in other fields. We can see that the current selections of ARAge as 31-60 Days, Customers as A&R Partners, and A2Z Partners and AccountDesc as Communications are selected and highlighted in green. If we look at the Customer dimension, we see that all other customer names are dark gray because a customer can only have one name in this model. We also see that the other ARAge and AccountDesc dimension elements are light gray because they are excluded based on selections in other fields. This could change with a change in the selection criteria. Based on this example, global filtering provides a very powerful view of the relationships in the application's associative data model. It also centralizes filtering, leaving valuable screen real estate for visualization based on filtering and the exploration of information, and once selected, it appears in the SELECTIONS pane.
Now, let's turn our attention to the Account Receivables Analysis sheet. This sheet is an interesting example of where there are no formal filter panes or listboxes (as there would commonly be in a QlikView app). Instead, each of the objects can be used to select areas to explore, and global filtering and global search can be used to augment or refine the selections at a finer detail level. In this case, revenue contribution for sales representatives by channel is displayed. Qlik Sense also supports a full range of objects, such as the table object to the right, which can be used to filter columns and supports exception formatting for variance reporting.
Finally, the table object has the ability to hide and show columns based on the allocated space for the table. The column selection menu within the table allows Nora to orient columns based on the viewable space available to the table.
As noted in Chapter 1, Qlik Sense® and Data Discovery, the rise of BI consumerism and self-service is becoming an increasingly important attribute to meet the needs of the next generation consumers. Qlik Sense embraces this important requirement through Library. The Qlik Sense Library is a governed area where an application's author can store dimensions, measures, and preconfigured charts that can be used to create compelling analysis that can be shared across an organization. In this case, Nora is taking advantage of the Customer count trend line chart to extend an application.
This chapter covered how Qlik Sense meets the new requirements of consuming and extending discovery-based applications, meeting these requirements across a myriad of platforms spanning PC, Mac, and the never-ending flow of new mobile devices. This required Qlik Sense to be built with a new approach that is responsive to these new realities of self-service and mobile use.
Now, let's turn our attention to the contributor who seeks to not only consume but also extend and share their data discovery insights.