Book Image

QlikView Unlocked

By : Andrew Dove, Roger Stone
Book Image

QlikView Unlocked

By: Andrew Dove, Roger Stone

Overview of this book

QlikView Unlocked will provide you with new insights to get the very best from QlikView. This book will help you to develop skills to work with data efficiently. We will cover all the secrets of unleashing the full power of QlikView, which will enable you to make better use of the tool and create better results for future projects. In the course of this book, we will walk you through techniques and best practices that will enable you to be more productive. You will gain quick insights into the tool with the help of short steps called ”keys,” which will help you discover new features of QlikView. Moving on you will learn new techniques for data visualization, scripting, data modeling, and more. This book will then cover best practices to help you establish an efficient system with improved performance. We will also teach you some tricks that will help you speed up development processes, monitor data with dashboards, and so on. By the end of this book, you will have gained beneficial tips, tricks, and techniques to enhance the overall experience of working with QlikView.
Table of Contents (16 chapters)
QlikView Unlocked
About the Authors
About the Reviewers
Hidden Image List

Dirty data and what to do about it

A major use of QlikView is to create Data Quality Dashboards as the issue of Data Quality affects everyone and is something that we need to bear in mind when designing the data model.


Different data sources have their own levels of quality issues. Databases have field types, which, at least, prevent errors such as text in a numeric field or an invalid date entry in a date field. However, spreadsheets usually do very little in the way of verification. Always try to work with clean data, even if it means extra work before starting the real development work. Ideally, you can ask the data provider to clean up the data for you!

How to do it

Whatever our data source, we have to assume that there could be issues in the data because what works today may fail to refresh correctly tomorrow.

Data Quality can basically be broken down into three types:

  • Incorrect or erroneous data

  • Inconsistent data

  • Duplication

To explain further, incorrect or erroneous data could be...