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- Herausgeber: Packt Publishing
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Perform Interactive Data Analysis with Smarter Visualizations and Support your Enterprise-wide Analytical Needs
About This Book
- Get a practical demonstration of discovering data for sales, human resources, and more using Qlik Sense
- Create dynamic dashboards for business intelligence and predictive analytics
- Create and collaborate comprehensive analytical solutions using Rattle and Qlik Sense
Who This Book Is For
This course is for anyone who wishes to understand and utilize the various new approaches to business intelligence actively in their business practice. Knowing the basics of business intelligence concepts would be helpful when picking up this course, but is not mandatory.
What You Will Learn
- Build simple visualization models with Rattle and Qlik Sense Desktop
- Get to grips with the life cycle and new visualization functions of a Qlik Sense application
- Discover simple ways to examine data and get it ready for analysis
- Visualize your data with Qlik Sense's engaging and informative graphs
- Build efficient and responsive Associative Models
- Optimize Qlik Sense for sales, human resources, and demographic data discovery
- Explore various tips and tricks of navigation for the Qlik Sense® front end
- Develop creative extensions for your Qlik Sense® dashboard
In Detail
Qlik Sense is powerful and creative visual analytics software that allows users to discover data, explore it, and dig out meaningful insights in order to make a profit and make decisions for your business. This course begins by introducing you to the features and functions of the most modern edition of Qlik Sense so you get to grips with the application.
The course will teach you how to administer the data architecture in Qlik Sense, enabling you to customize your own Qlik Sense application for your business intelligence needs. It also contains numerous recipes to help you overcome challenging situations while creating fully featured desktop applications in Qlik Sense. It explains how to combine Rattle and Qlik Sense Desktop to apply predictive analytics to your data to develop real-world interactive data applications. The course includes premium content from three of our most popular books:
- Learning Qlik Sense: The Official Guide Second Edition
- Qlik Sense Cookbook
- Predictive Analytics using Rattle and Qlik Sense
On completion of this course, you will be self-sufficient in improving your data analysis and will know how to apply predictive analytics to your datasets. Through this course, you will be able to create predictive models and data applications, allowing you to explore your data insights much deeper.
Style and approach
The course will follow a practical approach with rich set of examples through which it will demonstrate its concepts, features and its implementation. The course will also feature numerous solutions which will cover entire spectrum of BI use cases.
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Seitenzahl: 696
Veröffentlichungsjahr: 2017
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Qlik Sense: Advanced Data Visualization for Your Organization
Qlik Sense: Advanced Data Visualization for Your Organization
Copyright © 2017 Packt Publishing
All rights reserved. No part of this course may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this course to ensure the accuracy of the information presented. However, the information contained in this course is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this course.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this course by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Published on: December 2017
Production reference: 1121217
Published by Packt Publishing Ltd.
Livery Place
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ISBN 978-1-78899-492-7
www.packtpub.com
Credits
Authors
Dr. Christopher Ilacqua
Dr. Henric Cronström
James Richardson
Philip Hand
Neeraj Kharpate
Ferran Garcia Pagans
Reviewers
Arthur Lee
Steve Dark
Holly A. Kraig-Helton
Pablo Labbe Ibaceta
Stefan Stoichev
Gert Jan Feick
Miguel Ángel García
Content Development Editor
Snehal Kolte
Production Coordinator
Aparna Bhagat
Preface
Qlik Sense is powerful and creative visual analytics software which allows users in discovering data, exploring the data, and digging out the meaningful insights in order to take profit making decisions for your business. This course begins with introducing you to features and functions of the most modern edition of Qlik Sense to build grip with the Qlik Sense application. The course will teach how you can administer the data architecture in Qlik Sense, thereby enabling you to customize your own Qlik Sense application for your business intelligence needs. The course also contains numerous recipes in order to overcome challenging situations while creating fully featured desktop applications in Qlik Sense. The course also explains how to combine Rattle and Qlik Sense Desktop for applying predictive analytics to their data for developing real-world interactive data applications.
On completion of this course, you would be self-sufficient to improve your data analysis and how you can apply predictive analytics to your datasets. Through this course, you would be able to create predictive models and data application allowing you to explore your data insights much deeper.
What this learning path covers
Module 1, Learning Qlik Sense: The Official Guide Second Edition, in this module, you will learn about Qlik Sense, Qlik's self-service visualization platform. Our aim is to help you get more from your data by applying Qlik Sense and its unique capabilities to your analytic needs. At the beginning of this module, we'll cover why Qlik chose to develop Qlik Sense, what data discovery is and can do, and the strategy and vision behind the product. Later, we'll address practical considerations, including the Qlik Sense application's life cycle, how to meet the needs of different types of users, how to develop and administer engaging Qlik Sense applications, data modeling and getting the most out of the QIX engine. The module concludes by outlining a series of example applications built using Qlik Sense, to address analysis needs in sales management, HR, T&E management, and demographics.
Module 2, Qlik Sense Cookbook, this module uncovers all the wonderful features of Qlik Sense product. It will help you to overcome the challenges faced in day to day Qlik Sense implementations. The solutions are discussed through simple and easy to understand recipes.
Module 3, Predictive Analytics using Rattle and Qlik Sense, the objective of this module is to introduce you to predictive analytics and data visualization by developing some example applications. We'll use R and Rattle to create the predictive model and Qlik Sense to create a data application that allows business users to explore their data. We use Rattle and Qlik Sense to avoid learning programming and focus on predictive analytics and data visualizations concepts.
What you need for this learning path
Module 1:
You will need a copy of Qlik Sense Desktop, which is available for free at http://www.qlik.com/us/explore/products/sense/desktop. After that, you just need some time and a good comfortable chair. Additionally, the sample application's examples and many others are available for you to explore live on http://sense-demo.qlik.com/. Please bookmark this link as additional demonstrations and examples are constantly being added and updated.
Module 2:
The user needs to install Qlik Sense Desktop version 2.1.1, which can be downloaded for free from: http://www.qlik.com/try-or-buy/download-qlik-sense. The user also needs to install Qlik Sense Server version 2.1.1 for the recipe titled Publishing a Qlik Sense application on Qlik Sense Server, given in Chapter 4, Managing Apps and User Interface. The Qlik Sense Server installer file can be obtained from: http://www.qlik.com.
One needs to login using the customer account credentials to get access to the files under Support | Customer Downloads. You also need to install the SAP connector for the recipe titled Extracting Data from custom Databases from Chapter 1, Getting Started with the Data. In order to work with the SAP connector, you will need to obtain a license from Qlik. A part of this recipe also makes use of QlikView which can be downloaded for free from: http://www.qlik.com/try-or-buy/download-qlikview.
Module 3:
To install our learning environment and complete the examples, you need a 64-bit computer:
Who this learning path is for
This course is for anyone who wishes to understand and utilize the various new approaches to business intelligence actively in their business practice. Basics of business intelligence concepts will be helpful when picking up this course, but not mandatory.
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Downloading the example code
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Questions
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Part 1. Module 1
Learning Qlik Sense: The Official Guide Second Edition
Get the most out of your Qlik Sense investment with the latest insight and guidance direct from the Qlik Sense team
Chapter 1. Qlik Sense® and Data Discovery
In this chapter, we'll start getting to grips with what Qlik Sense offers by getting a better understanding of Qlik's background and how Qlik Sense was developed. In addition, we will examine the discovery-based approach to business intelligence that Qlik invented.
We will cover the following topics:
Continuing disruption
In the world of technology, there's a lot of talk about creating new products that disrupt existing markets, but very few organizations can say they've done it for real. Qlik is one of them.
In 2007, the business intelligence (BI) software market changed forever. Oracle bought Hyperion, SAP bought Business Objects, and IBM bought Cognos. The conventional wisdom was that BI would effectively cease to exist as a standalone market, subsumed into larger stacks of technology.
However, this wasn't the case. In fact, by 2007, a revolution was already well underway. The BI world was being fundamentally disrupted, challenged by the new approach pioneered by Qlik (then called QlikTech). The disruptive technology Qlik developed was called QlikView. To differentiate QlikView from the established BI products, Qlik began to call the new disruptive approach Business Discovery, later adopting data discovery as this term gained industry-wide adoption.
Surprisingly though, when it was launched in 1994, what became QlikView was not consciously targeted at the BI software market. Rather, its initial task was to help its customer understand which of a number of individual parts and manufacturing materials were used across the range of the complex machines it manufactured, and which parts were not associated with particular items (a critical point we'll explore later in this chapter and revisit throughout this book). The goal was to visualize the logical relations between the parts, materials, machines, and products. This origin led to an approach completely different from BI at the time, one in which all the associated data points are linked automatically, enabling discoveries to be made through free exploration of data.
As it became more widely used and deployed, it was evident that what QlikView was being used for was a new type of BI. QlikView's speed, usability, and relevance challenged the standard approach that was dominated by IT-deployed data reporting products, which are slow performing, hard to use, and built around models that struggle to keep up with the pace of modern business needs.
QlikView's intuitive visual user interface, patented associative data handling—running entirely in memory—and its capability to draw data together from disparate sources changed the landscape. Discovery-led BI is about giving people the power to interact with and explore data in a much more valuable way than the older, reporting-led BI incumbency could. This is massively compelling to people who need to quickly ask and answer questions based on data in order to learn and make decisions, and proved very compelling to people jaded with the way things had been done before. QlikView became very successful, dominating the market it pioneered.
So what did Qlik do then? Sit back and relax, proud of its disruptive chops, safe in the knowledge that it had recast an established market in its image? No. Far from it. Instead, Qlik took the decision to transform the BI market again with a new product.
Qlik Sense® and the QlikView.Next project
Qlik decided to design and develop a next generation data discovery platform. Developed under the project name QlikView.Next and launched as Qlik Sense, the product was anchored to five themes:
Making sense of modern business
You may say, "Well, that's all good, but it doesn't really tell me why this matters or why Qlik Sense is important."
To answer this, we have to think about what the focus of technology in our organizations has been in the recent past. For 25 years, most of our investment in IT has been on effectively improving reliability, using ERP or transactional applications to streamline processes, drive out inefficiencies, and deliver our products or services effectively. However, if most organizations, and particularly groups of competitors, are now operating at similar levels of procedural effectiveness, a key question arises, "What do we do differently to win?"
The answer lies in out-thinking our competitors through the use of data and analysis. This requires a shift of focus in both how we run our businesses and the IT world needed to do so. So far, analytics has too often been a poor cousin, something that happens afterwards on the edges, a tactical rather than strategic activity. That's no longer good enough. Businesses using data-driven decision-making perform measurably better than those that don't. When we can see (and measure) new things, we are driven to seek answers and thus, new ways of thinking and operating. Organizations that do not have analytics as a central part of their business activities will not thrive, or even survive, in the new reality.
Qlik Sense is about doing exactly that—freeing up the analytical skills of individuals in organizations, whatever their role. This book shows you how to make the most of that and alter how your organization uses information.
What is data discovery?
So we've already mentioned the new style of BI that Qlik pioneered, data discovery, a few times. In this section, we'll look at that in more detail.
Over the years, there have been many names of the different business intelligence methods and tools, such as:
Do we really need an additional label for something that in principle is the same thing? The answer is yes.
There is a fundamental difference between older technologies and data discovery, and it is in the approach. Most of the preceding tools are oriented towards technology, but data discovery is not. Instead, data discovery is oriented towards people—towards the users who need the information in their daily work.
Most of the preceding tools were developed for a small, select number of decision-makers, but again, data discovery is not. Data discovery is for everyone.
Decisions are made at all levels in a company. Obviously, managers are decision-makers, but we sometimes forget that machine operators and receptionists are also decision-makers, albeit at a more local level. They also need information to make better decisions.
We, at Qlik, believe that information can change the world and that every user can contribute to this transformation. Everyone should easily be able to view data, navigate in data, and analyze data. Everyone should be able to experience that "a-ha" moment of discovery.
Data discovery is not just business intelligence. It is user-centric, dynamic, and empowering. And it is fun!
The empowered user
Since its founding in 1994, Qlik has believed that a business could improve its processes and product quality by empowering employees and encouraging them to engage in lifelong learning. And Qlik meant all employees—we saw everyone as a decision-maker, not just managers.
Although some things have changed since then, much remains the same. Users are still often in a situation where they are unable to analyze their data—data that they have the right to see, or should have the right to see, in order to do a good job. Rigid systems, technical limitations, and poor user interfaces are usually the culprits.
However, people's expectations of software have changed dramatically during the last decade. Applications from Google and Apple invite users to interact with simple, friendly interfaces. Search bars, Like buttons, and touchscreens have transformed the way people explore, consume, and share information. Today, people want the same ease of use from their business tools as they get from their consumer tools at home.
The current trends such as the consumerization of software, performance improvements of hardware, usability improvements of software, mobile devices, social networks, and so on just accelerate this change. All these trends are reshaping user behavior. Yesterday, a user was a passive end user, but the user of tomorrow will be both able and demanding. They will demand tools that are fast, flexible, and dynamic. They will demand tools that they can use themselves. The empowered user is here to stay.
Interaction with data
The classic picture of business intelligence is that the user has one or several questions, and that the data holds the answers. So the problem boils down to creating a tool where the user can enter their questions, and the tool can return the answers.
However, this picture is incorrect. The truth is that the user does not always know the question initially. Or rather, if the user knows the question, they often already know the answer. So, the first thing the tool should do is help the user find the questions.
Finding the questions is a process that involves exploring the data. It involves testing what you suspect but don't know for sure. It also involves discovering new facts. Further, it involves playing with data, turning it around, scrutinizing the facts, and formulating a possible question. You use your gut feeling as a source of ideas and use the data to refine the ideas into knowledge; or to discard the ideas, if facts show that the ideas are wrong. You need to be able to play with the data, to turn facts around and look at them from different angles before you can say that you understand the data, and you need to understand the data before you can talk smartly about it.
When you have found a relevant question, you also need to be able to conduct an analysis to get a well-founded answer to the question.
Finally, the process involves presenting the answer to the question to other people as a basis for a decision or an action. The tool must support the entire process of going from ignorance to insight.
Hence, one major difference between data discovery and the more old-fashioned tools is that data discovery software supports the entire process—the process of coming from a blank mind, not knowing what you are looking for, all the way to attaining knowledge and taking action.
This is what data discovery is all about—helping you to prepare before you speak, act, or make a decision. It is the process of going from the darkness to the light, from the unknown to the known, from ignorance to insight. It is the process of going all the way from a blank mind to a substantiated argument.
Traditional business intelligence architecture
It is quite clear that users representing the business want the ability to ask and answer questions on their own so that they can make better decisions, but traditional business intelligence solutions aren't well suited for user demands. Instead, it is common that the systems are created in a report-centric manner, where governance and system demands set the goals, rather than user demands. The solutions often have preconfigured dashboards, fixed drill-down paths, predefined queries, predefined views, and very little flexibility.
With traditional BI, the creation of the business intelligence solution often belongs to the IT organization, which has to do the following: create data models, establish a semantic layer, build reports and dashboards, and protect and control the data. Often, the creation of business intelligence solutions is not driven by user demands. The following figure depicts the traditional BI architecture:
When analyzing data, you might want to set filters so that you can make selections, but with traditional tools, you often need to start at the top of predefined hierarchies. So, instead of selecting a customer directly, you may need to answer this question, "Which market does this customer belong to?", then the country the customer belongs to, and only then can you specify the customer.
Further, in the drill-down hierarchy, you are often limited to the choice of one or all. For example, you can look at either a single customer or all of them. The possibility of choosing two or three specific customers doesn't exist, unless this has been specifically predefined by the data model developer.
Numbers are often precalculated to ensure short response times, but this has a drawback that if the developer hasn't anticipated a specific calculation, the tool will not be able to show it.
Further, the architecture of the tool is often made in three layers—referred as the stack. The first layer is the Extract, Transform, Load (ETL) layer, or the data load layer. The second is the Data Store / Engine layer, and the third is the User Interface (UI) layer. The three layers are different pieces of software, sometimes delivered by different software vendors.
These three layers also demand different skill sets. Often, the ETL expert knows little or nothing about the UI software, and the UI expert knows little or nothing about the ETL.
The product stack in traditional BI
This architecture also leads to problems. When an application is built, the feedback comes from users trying to use the application. It could be that KPIs are incorrectly calculated or that dimensions or measures are missing. It could also mean that the user realizes that the initial requirements were incorrect or insufficient. The feedback could imply changes in the UI, or in the data model, or even in the ETL component.
This type of feedback is normal—it happens with all business intelligence tools. It only means that the development of applications is a process where you need to be agile and prepared. The expectation that you should be able to define an application completely and correctly prior to a prototype or an intermediate version is just unrealistic.
This is where the architecture leads to problems. In order for a project to be successful, you need to be able to implement change requests and new user demands with short notice, and this is extremely difficult since three different pieces of software and three different groups of people are involved. The distance between the user and the ETL component is just too great for efficient communication. Hence, the traditional architecture leads to a broken process.
The Qlik® way
Qlik has tried to solve all the drawbacks discussed in the preceding section by doing things differently.
First of all, you click and view. You don't need to formulate your question or tell the system more specifically what you want to look at. You just click, and by that, you say, "Tell me more about that…". Then you look at the calculation, KPI, or the field that might be interesting.
Color coding
The color coding defines the answer. Some things are associated with what you clicked on, and they remain white. Others that are not associated become gray. The color coding is for simplicity. The user quickly gets an overview and understands how things work.
Showing the excluded reveals the unexpected, creates insight, and creates new questions. Hence, the gray color is an important part of making the Qlik experience an associative one—a data dialog and an information interaction—rather than just a database query. Showing you that something is excluded when you didn't expect it means answering questions you didn't ask. This surprise creates new knowledge in a way that only a true data discovery platform can.
Freedom of data navigation
Via the associative experience, a user has total freedom to navigate through data and make any combination of selections. Any number of values can be selected. No drill-down paths need to be predefined. This allows the user to follow their own train of thought instead of someone else's. Start anywhere and just follow your intuition.
This total freedom when exploring data is really the core attribute of data discovery.
Calculation on demand
Further, no numbers need to be precalculated. Via the QIX engine, QlikView and Qlik Sense calculate everything on demand, usually in a fraction of a second. The short response time allows the user to have a conversation with the data, where one answer leads to the next question, which in turn leads to next, and so on. Only this way can you interact with data so that you learn from it.
The developer does not need to anticipate all questions that the user will pose. All they need to do is to create a logical, coherent data model, and Qlik Sense will be able to answer the question correctly:
The stack (ETL-Data Store / Engine-UI) is replaced by a single integrated environment. This makes it possible to develop applications in close cooperation with the users, and it can often be done by the users themselves. Feedback is implemented instantaneously and the changes can be evaluated just seconds later. This shortens the development cycle and ensures that the application meets the user demands much sooner than it would otherwise.
This stepwise implementation is crucial for the success of a business intelligence project. It is also the core of modern agile methodologies that are used in all types of software development.
With Qlik Sense, all BI stack functions are integrated into one tool
The development of business intelligence applications must be done as close to the user as possible to enable user feedback and short development cycles. It does not necessarily imply self-service capability, although it is good if this capability exists.
With the introduction of Qlik Sense, the groundbreaking work continues by enabling a new class of users who are highly mobile and require greater self-service capabilities. In Qlik Sense, the self-service capability has become a core feature. Users can define new graphs and visualizations that the app developer didn't think of. This functionality empowers the users even further.
With Qlik Sense, it has also become easier to share your findings and communicate them. This is something that is necessary in all environments where human interaction is important, which is pretty much everywhere.
Data discovery—the evolution of BI
Data discovery is the future of business intelligence. With data discovery, users pursue their own path to insight, make discoveries collaboratively, and can arrive at a whole new level of decision-making. Users are not limited to predefined paths or precalculated numbers. They do not need to formulate questions ahead of time. They can interact with data, find the questions, ask what they need to ask, and explore up, down, and sideways, rather than only drilling down in a predefined hierarchy.
Organizations might still need standardized reporting for many cases, but data discovery is the approach that ultimately fulfills the promise of business intelligence for everyone.
Data discovery is the inevitable consequence of demands from active users who want information from the ever-increasing amount of data. From the very beginning, the core of the Qlik philosophy was the empowered user. It affects both the view of how BI solutions should be developed and how the user interface of the tool should be designed.
In summary, data discovery is user-centric; it is BI for the empowered user. It means total freedom in how data is explored. It should be simple and have as few limitations as possible. Data discovery means a user-centric development process so that user feedback can be implemented instantaneously.
Summary
In this chapter, we looked at why Qlik developed Qlik Sense and at the ethos and value of data discovery in contrast to older forms of BI.
In the next chapter, we will look in detail at Qlik Sense itself and how its features help in meeting these requirements, beginning with the application life cycle.
Chapter 2. Overview of a Qlik Sense® Application's Life Cycle
In the previous chapter, we outlined the evolving requirements driven by the market, and more importantly by business users seeking to help make better decisions within their organization. This chapter's goal is to highlight key features and benefits of Qlik Sense in meeting these requirements. There are thousands of features in the initial release of the software, and this chapter will serve as a guide to the major components, features, and benefits of Qlik Sense as you start exploring it.
In this chapter, we'll cover the following topics:
Overview of an application's life cycle
As we begin our overview of a Qlik Sense application life cycle, it is best to start at the center of a Qlik Sense community collaboration, which is called the hub. The hub is made up of a number of streams that contain applications that are published by authors as well as users who can extend these applications by adding personal sheets and data stories. The Qlik Sense Management Console (QMC) governs this publishing through streams that have security rules. This approach provides the highly governed system that IT needs, while granting users the ability to explore information and share and collaborate on their findings.
Let's dig a bit deeper in each of these areas:
Overview of the Qlik Sense hub
Starting application authoring
The need for a Qlik Sense application often starts with simple questions, such as these: Why are sales down in my region? What products are not selling well? Are there opportunities to sell additional products to existing customers? When a customer purchases a product, do they also purchase a companion product? These types of questions lead to the identification of the place to find this data. Qlik Sense provides two starting points that can be from either the Personal (Desktop) or Enterprise Edition. This chapter will focus primarily on the Qlik Sense Enterprise Edition and mention the differences in the Desktop Edition.
The hub is made up of two main parts. The first is My Workspace, which enables users to create new Qlik Sense applications. The second part comprises defined Streams, which contain published applications to be used and extended by users. Streams are defined in the QMC, which provides a broad range of security rules to meet organizational requirements. Once an application is completed, it can be published to an authorized stream by the author. When published, the application cannot be altered without republishing by the author. The Desktop Edition contains only a hub for the creation of Qlik Sense applications and the application author must send all artifacts of the application, which must include at least the Qlik Sense document (QVF) and extensions used in the development of the application. Once received by the administrator, these artifacts are imported through the QMC and then published.
What makes up a Qlik Sense® application?
Now, let's turn our attention to what components make up a Qlik Sense application. They are shown in the following diagram:
A Qlik Sense application component
Qlik Sense applications are made up of a number of components. Starting from the data source, these components include the following:
All these components combine to create a dynamic baseline application to be explored by users.
Sharing an application
Let's turn our attention to how an application is shared with the Qlik Sense community. There are two methods:
Once a Qlik Sense application is complete, the author can share it by publishing it to a stream in the Qlik Sense hub. The publishing process can be accomplished by an administrator who is responsible for a stream and has publishing rights in the QMC. A Qlik Sense author notifies a stream administrator that a Qlik Sense application is ready for publishing. The stream administrator logs into the QMC, identifies the Qlik Sense application by name and author, and publishes the application in a stream.
Qlik Sense Enterprise application publication
Note
This method moves the application from the personal workspace, so a copy of the application should be made prior to publishing. Publishing and best practices for delegating publishing rights to an author in the QMC will be discussed in more detail in Chapter 9, Administering Qlik Sense®.
Once an application is published to a stream, it is ready to be explored by users:
Qlik Sense Enterprise application consumption
Qlik Sense Cloud
Qlik provides a free and easy way for up to five people to create and share Qlik Sense visualizations in the cloud. There are two ways to take advantage of Qlik Cloud:
Qlik Sense Cloud will be explored in more detail in Chapter 7, Qlik Sense® Apps in the Cloud.
Continuing the application's life cycle
One of the key features of a Qlik Sense application is its dynamic nature, which helps meet the broad requirements of data discovery. Users can explore the published sheets and data stories as well as create and share private sheets and stories based on the application library. The library allows for the creation of personal sheets and data stories in a controlled manner. As mentioned earlier, the library is a collection of dimensions, measures, and charts that are defined by the application author and cannot be modified once they are published to a stream but can be republished from the author's workspace. It allows a user to extend an application and share findings through personal sheets and data stories, while keeping consistent definitions across an organization.
Taking a step back, let's look at this new application model. A published Qlik Sense application is just at the beginning of its life cycle. Once published, the application can be expanded by the contributor within the stream using additional published sheets and stories based on the original application.
Qlik Sense application life cycle
Summary
Enterprise Qlik Sense applications are built based on governed data sources defined in the QMC. These data sources are transformed into a QIX Engine. Once the model is defined, key dimensions and measures are created within the library. This library will be used to create sheets. Next, the application is published to a stream within the hub for consumption. The application is then explored by users, and key findings can then be shared through bookmarks, private sheets, and data stories. These artifacts enrich the application and can be published back in the stream for collaboration between other members of the stream.
The next chapter will explore each of these capabilities in more detail and how they meet the needs of key stakeholders within your organization.
Chapter 3. Empowering Next Generation Data Discovery Consumers
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
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:
Diversity of consumption
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.
Introducing the hub
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:
The hub
Now, let's turn our attention to streams.
Introducing 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.
The BI Center of Excellence stream
Let's start with the components of a Qlik Sense application.
Exploring the components of the application
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
