Chart versus table - when to choose the right visualization
Companies generate massive amounts of data on a daily basis. Choosing the visualizations most appropriate for your needs will make interpreting this inflow of data easier and be more visually appealing. While both tables and charts bring data to life, each offers a unique advantage and function.
Table v Chart
While both tables and charts bring data to life, each offers a unique advantage and function. Choosing which to use depends on factors such as your target audience, the type of data you wish to review, and the impact of your visualization. Sometimes we are also creatures of habit and tend to use the tool we are most comfortable with and in the process may compromise the effectiveness of a presentation. Next time you are reviewing your information, we encourage you to consider your options before defaulting to what you know best.
When to use a table
Tables are appropriate when precise figures are needed and to compare a number of values. For example, if your sales manager is analyzing qualitative values as a whole, he or she can look up the value of a specific customer for a certain month in the table. Data visualization expert and author Stephen Few explains in his book, Show Me the Numbers: Designing Tables and Graphs to Enlighten, a table makes the most sense when it is used to look up individual values or to compare individual values. Tables can include both summary and detail values.
When to use a chart
Instead of presenting data in precise values, charts show the patterns that emerge or relationships between different variables in bar or pie graphs. While charts may sacrifice some precision and granularity, they allow for a broader scope of high-level analysis and quicker comprehension of the data.
By simplifying complex datasets and highlighting distributions, trends, and numerical patterns, charts visually present your data, making it easier to understand. Stephen Few says it’s best to use charts when the data is used to convey a message contained in the pattern of the data, or to show a relationship between many values. When it comes to visualizations, Phocas allows users to toggle between the two views – table and then charts.
Different charts in the toolbox
Similar to a bar chart, a column chart displays a number of variables together. Column charts are good for simple comparisons such as monthly output.
A line chart plots performance over time, for example, a customer's sales for this year vs. last year.
A pie chart displays the percentage share of a number of variables, such as the results for different branches within a company or sales to different customers.
An area chart plots performance over time, displaying data as a shaded area that falls below a set of points connected by straight lines. Area charts are good for comparisons - for example, using two color-coded shaded areas to display this year vs. last year, or sales vs. orders.
A bubble chart uses color-coded circles or ‘bubbles' plotted on an x and y axis to represent measures. The first measure will be the x axis, the second measure is the y axis and the third measure determines the size of the bubble.
A combo chart combines a column and a line chart. They are useful for simple comparisons involving more than one data set, for example, sales by different reps this calendar year to date (YTD) vs last calendar YTD.
View a comparison or variance as a gauge that changes color as the pointer reaches a certain target. A gauge is used to view data containing a comparison or variance (for example, sales vs budget). Red, yellow and green each represent a range entered by the user, typically relating to business goals or targets
A waterfall chart gives you a visual overview of positive and negative changes to a value over a period of time. It is often used to gain insights into key processes within an area such as inventory. It can also be used to assess financial performance. For example, to build a step by step picture of growth or decline in cash flow.
A pareto chart shows the relative importance of differences between large sets of values, and is often used for root cause analysis, such as to highlight the most significant cause of a certain outcome.
To continue to make visualisations more effective for analysis, Phocas created a two-in-one which combines the Grid and charts so you can add simple visualizations to the grid. These include mini graphs that sit alongside the Grid numbers in the form of spark lines to spot trends, and variance for comparisons.
Andy is an Implementation Manager in Phocas Software's UK office
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