Data Visualization with Excel Dashboards and Reports
eBook - ePub

Data Visualization with Excel Dashboards and Reports

Dick Kusleika

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eBook - ePub

Data Visualization with Excel Dashboards and Reports

Dick Kusleika

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Large corporations like IBM and Oracle are using Excel dashboards and reports as a Business Intelligence tool, and many other smaller businesses are looking to these tools in order to cut costs for budgetary reasons. An effective analyst not only has to have the technical skills to use Excel in a productive manner but must be able to synthesize data into a story, and then present that story in the most impactful way. Microsoft shows its recognition of this with Excel. In Excel, there is a major focus on business intelligence and visualization. Data Visualization with Excel Dashboards and Reports fills the gap between handling data and synthesizing data into meaningful reports. This title will show readers how to think about their data in ways other than columns and rows.

Most Excel books do a nice job discussing the individual functions and tools that can be used to create an "Excel Report". Titles on Excel charts, Excel pivot tables, and other books that focus on "Tips and Tricks" are useful in their own right; however they don't hit the mark for most data analysts. The primary reason these titles miss the mark is they are too focused on the mechanical aspects of building a chart, creating a pivot table, or other functionality. They don't offer these topics in the broader picture by showing how to present and report data in the most effective way.

What are the most meaningful ways to show trending? How do you show relationships in data? When is showing variances more valuable than showing actual data values? How do you deal with outliers? How do you bucket data in the most meaningful way? How do you show impossible amounts of data without inundating your audience? In Data Visualization with Excel Reports and Dashboards, readers will get answers to all of these questions. Part technical manual, part analytical guidebook; this title will help Excel users go from reporting data with simple tables full of dull numbers, to creating hi-impact reports and dashboards that will wow management both visually and substantively. This book offers a comprehensive review of a wide array of technical and analytical concepts that will help users create meaningful reports and dashboards.

After reading this book, the reader will be able to:

  • Analyze large amounts of data and report their data in a meaningful way
  • Get better visibility into data from different perspectives
  • Quickly slice data into various views on the fly
  • Automate redundant reporting and analyses
  • Create impressive dashboards and What-If analyses
  • Understand the fundamentals of effective visualization
  • Visualize performance comparisons
  • Visualize changes and trends over time

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Información

Editorial
Wiley
Año
2021
ISBN
9781119698739
Edición
1

Part I
Display Data on a Dashboard

  • Chapter 1: Dashboard Basics
  • Chapter 2: Dashboard Case Studies
  • Chapter 3: Organizing Data for Dashboards

CHAPTER 1
Dashboard Basics

In This Chapter

  • Determining When to Use a Dashboard
  • Establishing User Requirements
  • Assembling the Data
  • Building the Dashboard
  • Formatting the Dashboard
Dashboards have never been more popular. We have more data available to us all the time and better visualization tools than ever before. At its core, a dashboard is a collection of charts. But it's much more than that. If you put some charts on a page, you would technically have a dashboard, but perhaps not a very good one. Creating a good dashboard takes some preparation, knowledge, and skill. In this chapter, I introduce you to dashboards and the concepts, skills, and best practices you'll need to create them.

Determining When to Use a Dashboard

Dashboards are used to present data. Data can be thought to be at various stages: raw, aggregated, analyzed, and presented. The stage your data is in depends on where it comes from and what you plan to do with it. There are many levels of aggregation and an infinite number of ways to analyze or present data. For example, an invoice is an aggregation of invoice lines and a sales report is an aggregation of invoices. Relative to an invoice, the invoice lines are raw data but relative to the sales report, the invoices are the raw data. Figure 1.1 shows data in its various stages.
Snapshots of the data shown as raw, aggregated, and analyzed and presented.
Figure 1.1: Data shown raw, aggregated, and analyzed and presented
Raw data is data that hasn't been processed. It can be transactions that come out of an accounting system, sales information from a point of sale, or readings from a measuring device like tank levels or temperatures. If you're starting with raw data, you will have to do some aggregating and possibly some analyzing before it's ready for a dashboard.

NOTE

A workbook containing the charts in the figures for this chapter is named Chapter1Figures.xls x and can be found on this book's companion website at www.wiley.com/go/datavizwithexcel/.
Aggregated data has been grouped and summarized in some way. A report of units produced by month sums the units produced each week or each day. And that may be a sum of units produced by shifts for a day. In many cases, dashboard builders start with aggregated data.
Dashboards tell a story about the underlying data. Analyzing data is determining what stories the data tells and which of those stories is worth telling. Analyzing is more than just drawing conclusions from the data. It's also understanding the nature of the data and what questions the data raises. It's common during data analysis to have to take a step back and aggregate the data in a different way.
Finally, there's the presentation stage, where dashboards live. The dashboard building process can start at any stage. If you get the source data from a data analyst, the story to tell may have already been determined and it's just a matter of presenting that story in an effective way. Conversely, if you start with raw data, you'll need to first aggregate and then analyze the data to make those determinations.
Dashboards are constantly evolving. At one time they were only static visuals telling one story. Now, dashboards include self-service business intelligence (BI) tools that either tell multiple stories or allow the users to find the meaning in the data themselves. With Microsoft's Power BI tool and its integration into Excel with Power Pivot and Power Query, self-service BI is becoming more mainstream and accessible.

CROSS-REFERENCE

Power Pivot, Power Query, and Power BI are introduced in Chapter 3, “Organizing Data for Dashboards.”

What Is a Dashboard?

A ...

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