Line Charts

A line chart (also known as a line graph) shows a set of points (of information) connected by a continuous segment of line. Line charts are usually used to show how information varies over a time period.

Figure 14.2 shows an example of a line chart.

This chart is built on the data shown in Table 14.1.

In this line chart, the x-axis shows quarters (that is, Q1, Q2, Q3, and Q4) in a financial year, and the y-axis displays the target achieved during each of these quarters. The individual data points that are connected by the line are known as markers. The line connects the markers in a dot-to-dot fashion.

Pie Charts

The pie chart is one of the oldest and most basic chart types used for data visualization. A pie chart, also known as a circle chart, resembles a pie with slices that represent data categories and together make up the whole pie, totaling 100%. The size of each slice is proportionate to its value. Pie charts are ideal for making comparisons and visualizing proportions. Because pie charts tend to be very basic, they are appropriate for giving an overview of data splits and for key takeaways.

Figure 14.3 shows a pie chart based on Table 14.1 for Q1 across all years.

Bubble Charts

A bubble chart is an extension of a scatter plot graph (discussed in the next section). In a bubble chart, each dot represents a single data point, and the value of the variable for every point is indicated by the size of the dot. The bubble chart in Figure 14.4 shows sales revenue across Q1 and Q3 for the sample data from Table 14.1.

Figure 14.5 shows the selections you use to draw scatter charts (discussed in the next section) and bubble charts in Microsoft Excel. As mentioned earlier, you can draw multiple other charts as well by selecting Insert > Charts.

Scatter Plots

A scatter plot, which is very similar to a bubble chart, represents information for two variables, displayed using points plotted against vertical and horizontal axes. A scatter plot is usually used to determine the relationship between two variables. Figure 14.6 shows a scatter plot for the data from Table 14.1.

Bar Charts

A bar chart, also known as a bar graph, categorizes information into a graphic with bars of different lengths, where the length of a vertical bar is relative to the quantity or amount of the information it represents. Along with the pie chart, the bar chart is one of the oldest and simplest visualization methods. To interpret a bar chart, you consider the length of the bar for each category in order to find its value. Figure 14.7 shows a bar chart based on the information from Table 14.1.

Bar charts can be oriented both horizontally and vertically. Figure 14.7 shows an example of a horizontal bar chart.

Histograms

A histogram represents the data distribution over a defined period or a continuous interval period. This type of visualization is useful for presenting a particular occurrence frequency; in other words, it shows how many times a specific value occurs.

Figure 14.8 shows a histogram based on the data from Table 14.1.

What’s the difference between a bar chart and a histogram? Well, a bar chart and a histogram are very similar except that a histogram groups numbers into ranges, and there are no gaps between the bars in a histogram.

Histograms are typically used to show results of continuous data, such as:

• The number of students in an educational institution

• Sales numbers over quarters

• Heights

• Weights

• BMIs

A histogram always looks “backward” in time and never projects forward.

Waterfall Charts

A waterfall chart visualizes data by denoting how a value is modified as it moves between two points and is impacted by various factors, such as time. Such a chart helps identify the net change in a specific value between two points. A waterfall chart is different from a bar chart as it depicts all of the unique elements that lead to that net change and visualizes them individually. This helps the observer understand how a value has declined or grown over a specific period.

Figure 14.9 shows a waterfall chart depicting sales revenue, based on the data from Table 14.1.

In Figure 14.9, you can see that, from right to left, the values form a waterfall shape—hence the name of the visual. A key element of a waterfall chart is that the beginning point of each bar is the ending point of the previous bar.

Heat Maps

A heat map is a visualization that uses color to show differences in information. Heat maps use colors to communicate values and make it simple for observers to determine trends quickly and get a comparative view of a dataset.

If you’re keen to generate your own heat map, you can go to Home > Conditional Formatting > Color Scales in Excel (see Figure 14.11).

Geographic Maps

Geographic map data visualizations, also known as choropleth maps or thematic maps, provide a novel way to show comparative values across states, countries, or regions. A geographic map uses shading, color, and other patterns to visualize the relevant mathematical values across geographic areas. The color of each location on the map is in proportion to its corresponding data values. A geographic map shows how a variable is different from one area to the next. To see an example of this type of visualization, consider the data in Table 14.2.

Figure 14.12 shows a geographic map created based on the data from Table 14.2.

In this case, the geographic map was generated using the built-in function Maps under Insert > Maps > Filled Map, as shown in Figure 14.13.

Tree Maps

Tree maps are used to capture data values in a hierarchical structure and present the information visually. A tree map is a series of rectangles, with the tree’s branches represented by rectangles and any sub-branches represented by smaller rectangles, each of which represents a proportionate data value.

A larger rectangle shows the division of information in the tree and can be broken into smaller rectangles so that, when a quantitative value is assigned to a field, its size is displayed in proportion to that quantity and to the other quantities (in a part-to-whole relationship) within the parent category.

Figure 14.14 shows a tree map for sales revenue across the years 2007 through 2011, based on the data from Table 14.1.

Stacked Charts

A stacked chart, also known as a stacked bar graph, is an extension of a bar chart in which each bar is divided into a number of sub-bars stacked together. A bar is drawn for each level of the categorical variable, and the bar’s length indicates the numeric value of the variable. Figure 14.15 shows an example of a stacked chart.

This chart is based on the data from Table 14.1. As you can see, the quarterly achievements for each year are stacked together and shown as a categorical representation with clear demarcations across Q1–Q4. This visualization provides an easier-to-read and easier-to-understand view of information than would a bar chart with four bars for each year.

Infographics

An infographic, or information graphic, is a visual illustration of data that makes it easier to understand information, often in a fun way. Infographics tend to combine otherwise disparate images, data, and text to tell a compelling story that is easy for stakeholders to understand. Infographics provide a very user-friendly way to view trends and patterns. Figure 14.16 shows an example of an infographic about smart home features.

Many online services can create infographics for you, such as:

• Canva: https://www.canva.com/create/infographics/

• Visme: https://visme.co/make-infographics/

• Vista: https://create.vista.com/create/infographics/ (which was used to create Figure 14.16)

Word Clouds

A word cloud, also known as a tag cloud, is a visual in which text content is shown in a random graphic manner. As a general rule, the more frequently a specific word is mentioned in a dataset, the larger it appears in the word cloud.

Word clouds are frequently used as eye-catching graphics. In addition to being larger than other words in a word cloud, key words may look bolder and may leverage a color scheme that indicates their frequency. Figure 14.17 shows a word cloud based on sales key words.

Static Reporting

As the name suggests, static reports are static in nature and offer insights about data or trends at a point in time or during a specific time period. With static reports, decisions can be made based on data from a particular day, month, or year. Essentially, static reports help examine data points and key information from the past to drive future decision making. For example, during a sales campaign, the number of respondents who responded to the campaign and the features they liked most in a newly launched product could be presented in a static report that would help guide the product owners and other stakeholders to ensure that they incorporate the in-demand features in the upcoming release of the product. In simpler words, static reports help examine the data points and key information in the past to drive future decision making.

Static reports can be saved in many formats, including PDF, Excel, and Word files. Figure 14.18 shows a static report that details sales achievements for fiscal year 2021.

Static reports are typically archived after their initial use. However, they can be used later to analyze trends such as sales trends across previous years and to provide direction for things that can be improved in the upcoming year.

Dynamic Reports

In contrast to a static report, a live report portrays information about events as they happen (similar to streaming movie). For example, your personal wearable health device shows you real-time data such as your heartbeat and calories burned during your daily run; this is a form of live reporting. While live reporting is useful at an individual level or perhaps even at a team level, not all live reporting is useful at corporate and leadership levels.

Dynamic reporting is a mashup of static reporting with elements of live reporting. Dynamic reports are usually graphical outlays that combine live and static reporting elements so that an observer can click through links to the different types of data needed—on demand. For example, the dynamic report in Figure 14.19 shows a Q1 sales performance report with live data on projections for the upcoming week.

Table 14.3 describes the key differences between static and dynamic reports.

Ad Hoc/One-Time Reports

Ad hoc reporting, sometimes also called one-time reporting, helps users generate reports on the fly such that they don’t have to wait for reports to be generated to answer business questions immediately. For example, if you’re about to walk into a leadership meeting and want to be equipped with updated sales revenue or performance data for the past 2 weeks, you won’t want to wait for a standard quarterly analysis report but would want to generate a one-time report to augment the discussion.

Some of the professions/industries where ad hoc reporting is commonly used are:

• Sales

• Recruitment

• Retail

• Education

• Healthcare

Ad hoc reports are not a substitute for other reports; rather, they should be seen as augmenting to the recurring (static or dynamic) daily, weekly, or monthly reports. Business users should be able to use ad hoc reports to improve the data-driven decision-making process.

Self-Service/On-Demand Reports

As the name suggests, self-service, or on-demand, reports can be generated by end users without any intervention from IT or analysts. Ad hoc reporting is a very good example of self-service reporting.

Users can leverage business intelligence tools to generate self-service reports, which reduce the workload for IT, provide cost savings, save time, and empower users to create their own reports rather than chase down someone to generate reports for them. End users (including executives) can customize reports as they like in order to tell a particular story and put things into perspective. Now, this is user empowerment!

Recurring Reports

Recurring reports are reports that are scheduled and generated based on predetermined KPIs. These reports are useful in that they save time and cost because they are run at known intervals, such as weekly, fortnightly, or monthly, and users can rely on these reports to come in so they can go about getting insights from these reports. Recurring reports may be either sent to specific email addresses or distribution lists, depending on the report content and at the report owner’s discretion. For example, whereas a sales revenue report might be sent to all VPs and executives, a performance report might be shared with all sales staff.

There are three categories of recurring reports—compliance, risk and regulatory, and operational reports—as detailed in Table 14.4.

Tactical/Research Reporting

In a research report, a researcher reports findings on a topic of interest such that readers of the report can understand the outcomes in a straightforward manner. These reports are commonly used in science, medicine, education, and other fields.

Tactical reporting is focused on more immediate goals related to improving operational metrics. These reports focus on associations with operational tasks that are performed in groups or individually to realize strategic outcomes.

When you combine tactical and research reporting, you get tactical research. For example, an organization may have data analysts compare products from competitors, including pricing and the sales figures a class of products is achieving as compared to the parent company. In this case, the analysts may be conducting a tactical pricing comparison while researching key factors for increased sales of competitive products.