Book Image

Learning QlikView Data Visualization

By : Karl Pover
Book Image

Learning QlikView Data Visualization

By: Karl Pover

Overview of this book

<p>While QlikView’s data engine complements our thought processes and gives us the ability to rapidly implement insightful data discovery, we must also learn to use proper analytical and data visualization techniques to enhance our ability to make data more presentable.</p> <p>Learning QlikView Data Visualization presents a simple way to organize your QlikView data discovery process. Within the context of a real-world scenario and accompanying exercises, you will learn a set of analytical techniques and data visualization best practices that you can customize and apply to your own organization.</p> <p>We start our data discovery project by reviewing the data, people, and tools involved. We then go on to use rank, trend, multivariate, distribution, correlation, geographical, and what-if analysis as we try to resolve the problems of QDataViz, Inc, a fictitious company used as an example. In each type of analysis, we employ highlighting, heat maps, and other techniques on top of multiple chart types. Once we have a possible solution, we present our case in a dashboard and use performance indicators to monitor future actions.</p> <p>You will learn how to properly create insightful data visualization in QlikView that covers multiple analytical techniques. By reusing what you’ve learned in Learning QlikView Data Visualization, your organization’s future data discovery projects will be more effective.</p>
Table of Contents (17 chapters)

People


People are the only active element of data visualization, and as such, they are the most important. We briefly describe the roles of several people that participate in our project, but we mainly focus on the person who is going to analyze and visualize the data.

After the meeting, we get together with our colleague, Samantha, who is the analyst that supports the sales and executive teams. She currently manages a series of highly personalized Excels that she creates from standard reports generated within the customer invoice and project management system. Her audience ranges from the CEO down to sales managers. She is not a pushover, but she is open to try new techniques, especially given that the sponsor of this project is the CEO of QDataViz, Inc.

As a data discovery user, Samantha possesses the following traits:

Ownership

She has a stake in the project's success or failure. She, along with the company, stands to grow as a result of this project, and most importantly, she is aware of this opportunity.

Driven

She is focused on grasping what we teach her and is self-motivated to continue learning after the project is finished. The cause of her drive is unimportant as long as she remains honest.

Honest

She understands that data is a passive element that is open to diverse interpretations by different people. She resists basing her arguments on deceptive visualization techniques or data omission.

Flexible

She does not endanger her job and company results following every technological fad or whimsical idea. However, she realizes that technology does change and that a new approach can foment breakthroughs.

Analytical

She loves finding anomalies in the data and being the reason that action is taken to improve QDataViz, Inc. As a means to achieve what she loves, she understands how to apply functions and methods to manipulate data.

Knowledgeable

She is familiar with the company's data, and she understands the indicators needed to analyze its performance. Additionally, she serves as a data source and gives context to analysis.

Team player

She respects the roles of her colleagues and holds them accountable. In turn, she demands respect and is also obliged to meet her responsibilities.