1
DATAVISUALIZATION
GUIDE
Make the most of each graph type
Use cases and pro tips
Alternative options for each graph
Helping You Choose the Best Visualizations for Maximum Data Impact
v. 1.1, April 2014
2 3
MAKE YOUR DATA CLEAR AND ACTIONABLE.
TABLE OF CONTENTS
Area chart ............................................................................................ 4
Bar graph ............................................................................................. 6
Box plot ............................................................................................... 8
Bubble graph .................................................................................... 10
Bubble grid ....................................................................................... 12
Combination chart ............................................................................ 14
Cylinder ............................................................................................ 16
Data cloud ......................................................................................... 18
Funnel ................................................................................................ 20
Gantt chart ........................................................................................ 22
Gauge ................................................................................................ 24
Graph matrix ..................................................................................... 26
Heat map ........................................................................................... 28
HiLow stock/candlestick ................................................................... 30
Histogram .......................................................................................... 32
Line chart ........................................................................................... 34
Map .................................................................................................... 36
Microchart ......................................................................................... 38
Network ............................................................................................. 40
Pareto chart ....................................................................................... 42
Pie chart ............................................................................................. 44
Polar chart/radar chart ..................................................................... 46
Scatter plot ........................................................................................ 48
Thermometer .................................................................................... 50
Waterfall ............................................................................................ 52
Weighted list ..................................................................................... 54
Create the most effective data visualizations for your business
needs and goals with this Data Visualization Guide from Lancet.
Whether you’re new to data visualization or relatively seasoned,
this catalog of examples gives you a jump-start on choosing the
right graph and honing it to perfection.
From the familiar bar chart to more complex visualizations like
network charts and polar charts, we show you 26 graph types,
built and formatted by the Lancet design experts, with pro tips
to help you gain maximum business benefit.
We hope you find this guide useful, and feel free to contact us
to learn more!
Lancet Data Sciences
info@lancetdatasciences.com952.230.7360www.lancetdatasciences.com/dashboards
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100K
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Books
Nov - 12 Dec - 12 Jan - 13 Feb - 13 Mar - 13
Jewelry Electronics
AREA CHARTDescription
• Based on a line chart, showing layers• Shows how categories overlap• Displays comparisons through overlapping areas
Pro Tips• Useful to show volume comparisons over time• Use a stacked area to show distribution of related
measures over time• Good for trend displays
Avoid• Opaque colors• Too many metrics• Measurements that are too close in value (making it
difficult to distinguish a difference)
Use Case• Tracking multiple revenue streams over time, showing
total volume as well as distribution
Alternative / Related Visualizations• Line chart• Bar chart• Histogram• Combination: area-line / area-bar• Polar chart / radar chart
The use of distinguishable colors and semi-transparent fills allow the end-user to quickly see trends of independent values and how they compare to the other values within the same visualization.
Units Sold by Category
6 7
Green Beans
Cucumbers
Carrots
Potatoes
Tomatoes
0% 7% 14% 21% 28% 35%
32%
28%
19%
15%
6%
Produce Dry GoodsDairy
$0
$12,000
$24,000
$36,000
$48,000
$60,000
#5034 #4022 #1024 #2032 #1340 #2340 #6001
BAR GRAPHDescription
• Shows values of specific categories• Compares absolute values of multiple items• Easy to interpret and compare
Pro Tips• Use stacked bar graph when comparing parts of a whole• Use to compare percentage to total of multiple items
Avoid• Graphing items with a broad numerical scale• Using too many contrasting colors• Showing zero (0) on the scale if it is not needed• Clustering a large number of items for comparison
Use Case• Comparing categories that are related to one another
(e.g. retail departments)
Alternative / Related Visualizations• Combination: bar-area / bar-line• HiLow stock / candlestick• Histogram• Gantt• Data cloud• Graph matrix• Microcharts• Cylinder• Thermometer• Pareto chart
Sorting a horizontal bar graph in a descending order allows the end-user to quickly ascertain the percentage share of one item compared to the rest.
A stacked bar graph is a great way to visualize the whole a of data element, as well as the components that make up its aggregation.
Vegetable Sales by %
Revenue by Store
8 9
BOX PLOTDescription
• Shows distribution of data including minimum, maximum, median, and percentiles
Pro Tip• Use when a baseline exists for comparison
Avoid• If there isn’t a high variance in data fluctuation
Use Case• Measuring student testing across school districts
Alternative / Related Visualizations• HiLow stock / candlestick• Stacked bar chart• Combination bar-and-line chart
Student Test Scores Across Districts
100
90
80
70
60
50
40
30
20
10
0191 252 192 200
School Districts
Test
Sco
res
199 194 659 195
The box shape within the box plot represents the top three quartiles of a particular data element. The top part of the box is the first quartile, the bottom part is the third quartile and the line represents the median or second quartile. The whiskers, or high and low marks of the box plot, commonly represent the highest and lowest numbers of a data element.
In this example, the end-user can see that School District 200 has the most students that tested in the top three quartiles, while its median score is also the highest.
10 11
BUBBLE GRAPHDescription
• Lets users easily analyze three different metrics with bubbles of varying sizes
• Used to perform analyses involving key business ratios
Pro Tips• If data supports it, enable drill down to view more
granularity (e.g. drill down from states to counties, etc.)• Color by category and drill down sub-category• When appropriate and if the bubble graph visualization
supports it, add time as an added dimension
Avoid• Using if there is not enough screen real estate
Use Case• Showing birth, mortality, and total population by
continent then by country
Alternative / Related Visualizations• Bubble grid• Heat map• Scatter plot• Weighted list• Graph matrix• Network
0 1 2 3 4 5 6 7
30
40
50
60
70
80
90
Fertility Rate (births per woman)
Life
Exp
ecta
ncy
(yea
rs) Africa
Americas
Asia
Europe
Oceania
0 1 2 3 4 5 6 7
30
40
50
60
70
80
90
Fertility Rate (births per woman)
Life
Exp
ecta
ncy
(yea
rs)
Americas: ArgentinaLife expectancy: 70Fertility Rate: 4Population: 28,369,799
0 1 2 3 4 5 6 7
30
40
50
60
70
80
90
Fertility Rate (births per woman)
Life
Exp
ecta
ncy
(yea
rs) Africa
Americas
Asia
Europe
Oceania
0 1 2 3 4 5 6 7
30
40
50
60
70
80
90
Fertility Rate (births per woman)
Life
Exp
ecta
ncy
(yea
rs)
Americas: ArgentinaLife expectancy: 70Fertility Rate: 4Population: 28,369,799
The beauty of a bubble graph is that the end-user can gain a lot of insight by showing only three related metrics.
Drilling into a bubble allows the end-user to see the components that make up the larger aggregate figure. This type of analysis enables the end-user to find outliers and ask further questions about the figures.
Life Expectancy and Fertility Rate by Continent and Country
12 13
BUBBLE GRIDDescription
• Helps identify correlations quickly• Color and size of the bubbles identifies where the item
lies on the spectrum between two metrics (e.g. color by profit, size by revenue)
Pro Tips• Ensure data has a wide variance, otherwise bubbles will be
too similar in size
Avoid• Coloring that is difficult to discern for those with color
blindness
Use Case• Measuring performance of product categories across
different regions
Alternative / Related Visualizations• Scatter plot• Heat map• Weighted list• Data cloud
Books
Movies
Music
NW SW NC C S NE SE Web
$179,526$15,222 $351,441
Size: RevenueColor: Profit
Category: MoviesRegion: CentralRevenue: $2,500,899Profit: $275,000Profit Margin: 11%
The color and shape contrast in the bubble grid let the end-user quickly visualize and compare two metrics across multiple dimensions.
Department Performance — Regions
14 15
COMBINATION CHARTDescription
• Graph that depicts any combination of bar, line, and area graphs
Pro Tips• Good for showing year-over-year comparisons• Use proper color variances with combination of graph types• Great when using a dual axis
Avoid• If the difference in scale between elements is too large• If one graph type commonly covers another (e.g. bar
covers lines)
Use Case• Measuring total website traffic compared to traffic coming
from search engines
Alternative / Related Visualizations• Pareto chart• Bar chart• Line chart• Area chart
Dual axis and combination charts like these convey the power and value of combining and trending multiple related metrics of different numerical properties and scale.
Website Traffic Analysis
16 17
CYLINDERDescription
• Shape is effective for displaying progress toward a goal, or total volume
Pro Tips• If stacking items in the cylinder, use monochromatic
shading to depict a relationship
Avoid• Using unless there is a specific reason for this visualization;
use a more common visualization, like a bar chart, when applicable
Use Case• A non-profit could use a cylinder to show actual progress
against fundraising goals• The stacked visualization is useful to demonstrate the
source of each portion of the funds
Alternative / Related Visualizations• Gauge• Thermometer• Bar chart• Funnel
$0
$5,000
$10,000
$15,000
$20,000
$25,000
$30,000
$35,000
$40,000
$45,000
$50,000
$55,000
$60,000
The use of semi-transparency and a darker fill color give the illusion of volume within a container. This is a necessary feature for making this visualization effective.
Capital Campaign Fundraiser - Goal $60,000
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DATA CLOUDDescription
• Displays data elements as text and is sized accordingly to the value of the metric
Pro Tips• Use colors to depict which items are performing against
milestones and benchmarks, in addition to other metrics
Avoid• Using if there is similar volume in usage between items as
there will be little difference in resulting size
Use Case• Showing popularity of trending topics in the media
Alternative / Related Visualizations• Network• Heat map• Scatter plot• Bar chart
ChinaHealthSyria
ObamacareNSAGovernment Shutdown
ObamaIndiaLou Reed
ImmigrationKrugman
Education
Social Q’s New York
Trending Topics in the News
Sized by number of social media shares
Larger keywords quickly grab the attention of the end-user, while varying and alternating the colors increase legibility.
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FUNNELDescription
• Provides a quick, meaningful view of the incremental phases within the data
• Helps to identify potential problem areas
Pro Tips• Ensure phases are in incremental order from highest to lowest
Avoid• Using if there are no incremental phases • Using when data values are too close to one another
Use Case• Measuring different phases of a sales cycle, starting from
an initial approach to closing the sale
Alternative / Related Visualizations• Cylinder• Stacked bar chart• Waterfall• Pie chart• Polar chart / radar chart
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Closing Ratio: 33.6%
156
202
254
284
348
Prospects Initial Appointments Qualify Prospect Presentation
Address Prospect’s Objectives Close and Sign Customer
Use the inherit shape and properties of a funnel in order to effectively utilize this visualization. Funnels have a natural filtration effect to them. This is important to remember when using this visualization.
Sales Prospects and Closing Rate
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GANTT CHARTDescription
• Type of bar chart that illustrates a project schedule• Shows tasks, dependencies, and milestones
Pro Tips• Color code types of tasks, phases, difficulty of workload,
and more — for easy visual reference
Avoid• Using on a project with an exceptionally large number of
tasks — information can get lost
Use Case• Used often in information technology and business
services for tracking project tasks and goals
Alternative / Related Visualizations• None
Showing tasks and dates in a matrix layout is a very easy thing for the end-user to understand. Adding stylistic components through color and design transforms something simple into something simple and appealing.
Market Research
Define Specifications
Overall Architecture
Project Planning
Detail Design
Software Development
Test Plan
Testing and QA
User Documentation
Aug 16 23
Missed CompleteOff Track
30 13 20 27 11 18 25 8 15 22Sep 6 Oct 4 Nov 1
Project Schedule
On Track
24 25
GAUGEDescription
• Great to measure a single metric• Useful when it has a metric selector to change the value
shown in the gauge• Simple status indicator displays a needle that moves
within a range of numbers
Pro Tips• Make the measurement goal visually obvious• Use colors to show varying levels of performance• Use a scale that accurately represents the goal
Avoid• Using different scales when comparing multiple gauges• Using more than one needle per gauge
Use Case• A sales force may use a gauge to depict how close they
are to hitting goals and benchmarks
Alternative / Related Visualizations• Thermometer• Cylinder• Bar chart
$8,000,000 $16,000,000
$0 $24,000,000
Target:$20,000,000
WEST CENTRAL EAST
For a gauge to be effective, it is important to measure against benchmarks or goals. Furthermore, measure across different elements of a dimension, like specific geographic regions vs. the aggregate of all regions.
Actual Revenue vs. Target Revenue
26 27
GRAPH MATRIXDescription
• Quickly analyze trends across multiple dimensions• Like microcharts, it offers a high-level view of a metric over
multiple categories
Pro Tips• Use like graph types across the matrix to identify true
comparisons• Use line or bubble graphs for optimal visualization
Avoid• Using unnecessary elements that may prevent
identification of the patterns
Use Case• Measuring healthcare member demographics and
utilization over time
Alternative / Related Visualizations• Bar chart• Line chart• Area chart• Microchart
The effective use of simplicity and clean layout allows the end-user to easily analyze trends across different dimensions. Patterns emerge that would otherwise need to be determined through a combination of visualizations.
Lifetime Member Utilization
28 29
HEAT MAPDescription
• Enables understanding of the impact of several factors simultaneously
• Metrics are represented by the size and color of each labeled rectangle
• Highly interactive: can pivot to remove attributes to create new comparisons, format colors, refresh to its original state, view deleted items, and use search functionality
Pro Tip• Use red, yellow, and green to indicate performance• Use monochromatic banding when performance isn’t
being measured
Avoid• Using unnecessary elements that may prevent
identification of the patterns• Using when metrics are unrelated• Using when metrics have too great or too small a variance
Use Case• Often used by the financial services Industry to review
portfolios
Alternative / Related Visualizations• Dual-axis combination graph when data has a high variance• Weighted list to view in a more linear fashion• Data cloud• Network
By using monochromatic shading, the user isn’t as inclined to see “good” or “bad” in the cells as much as they are to see volume of density of specific data elements.
Using a red-yellow-green gradient is a natural way to portray negative and positive indicators within a visualization.
Healthcare Gender & Age Demographics
Financial Portfolio by Region
30 31
HILOW STOCK/CANDLESTICKDescription
• Shows minimum and maximum with the fluctuation in between
Pro Tip• Use when there is a large number of data points to create
a more beneficial analysis
Avoid• If there is not a high variance in data fluctuation
Use Case• Showing how stocks open, close, and fluctuate over a
given time period
Alternative / Related Visualizations• Box plot• Histogram• Line chart
20
40
60
80
100
120
140
0Jan 7 Jan 11 Jan 15 Jan 19 Jan 23 Jan 27
CloseHigh
Open
Low
Color and plot shapes are an intuitive way to show growth and trends over time.
Widgets, Inc. High Low Stock Trend
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HISTOGRAMDescription
• Plots density, frequency, and probability of a continuous variable
Pro Tip• Use single color for bars
Avoid• Unnecessary labels
Use Case• Visually depicting units sold over time for a particular item category
Alternative / Related Visualizations• Bar chart• Line chart• Area chart• Microchart
The most important aspect of a histogram is its shape and trend. Labels take a backseat to the flow of the visualization.
Units Sold
34 35
LINE CHARTDescription
• Series of data points connected by curved or straight line segments• Shows trending over time• Good for quick interpretation and comparison
Pro Tips• Use different shapes of markers and colors to distinguish
one series from another• Use subtle horizontal grid lines for the y-axis to avoid
distracting from the data points• Use different line styles to show baselines, benchmarks,
goals, etc.• If showing a trend is more important than showing
detailed values, use minimal styling to create a “sparkline” type of visualization
Avoid• Using markers when comparing multiple items over many
data points• Comparing multiple items with similar values
Use Case• Comparing multiple measures over time
Alternative / Related Visualizations• Area chart• Bar chart• Polar chart / radar chart• Graph matrix• Combination: line-area / line-bar• Pareto chart• Microchart
Varying color and plot shapes allows the end-user to easily cypher one series from the next, even when the values are close in scale.
Jan-13
50%
40%
30%
20%
10%
0%Feb-13 Mar-13
Gross Margin %
Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13
BooksMusic Movies
36 37
MAPDescription
• View by geographies or with overlaid bubbles, sized according to metric data for effortless overview of geography comparison (e.g. state map, country map, store layout, etc.)
Pro Tips• Color code shapes to depict performance comparison• Consider differently-styled map pins to show different
categories (e.g. round, square, triangular pin, etc.)
Avoid• Using an entire map if only a specific subset needs to
be presented (e.g. use only the Northeast instead of the entire U.S. map)
Use Case• Healthcare system plotting different locations based on
service types (e.g. clinic uses square pin, hospital uses round pin, etc.)
• Color coding counties based on presidential election results
Alternative / Related Visualizations• None
Different map pin styles allow the user to differentiate one type of health provider from another.
Using existing color paradigms, like political
affiliation, is a natural and intuitive way for the end-user to gain deeper
understanding of your visualization.
Using gradients that follow the color wheel is an effective way to show density, especially on a map visualization.
Healthcare Providers
Election Results by US County
Population Density
38 39
Regional Revenue Tracking
Southwest
Southeast
South
Northwest
Northeast
Mid-Atlantic
Central
$10,234
$34,000
$53,200
$28,635
$42,019
$15,287
$37,298
20%
17%
32%
27%
28%
31%
18%
$89,000
$102,198
$130,187
$83,209
$183,298
$93,207
$108,000
Region Revenue 12 Month Trend Revenue TargetUnits Sold Current Month
Revenue% of Previous
YearRevenue
YTDMin: 1200Max: 2870
Low Medium High
Min: 987Max: 3024
Min: 1189Max: 4198
Min: 832Max: 1645
Min: 1567Max: 4870
Min: 732Max: 2570
Min: 857Max: 2013
MICROCHARTDescription
• Fits several intuitive chart formats into one area in combinations and formats of your choice (e.g. sparkline, bullet, and bar charts)
• View metric performance over time, specific values, comparison-to-goal data, and more — at a glance
• Small in design and dense in data
Pro Tips• Great to measure KPI trending• Best used for trending over time
Avoid• When needing to depict more than a summary-level
presentation
Use Case• Tracking KPIs across different geographies or product
categories
Alternative / Related Visualizations• Bar chart• Line chart• Area chart• Histogram• Graph matrix
Combining several small visualizations into one is not an easy thing to do. The visualization can become clogged and appear busy. This microchart shows that it is possible to combine several visualizations while still providing valuable insight and maintaining legibility.
The histogram part of the microchart allows the end-user to visualize the trend of a metric, as well as see it’s high and low in plain text.
This bullet chart works much like a box plot, with the exception that it doesn’t need to show quartiles. The dark gray indicates a low range of values, the middle gray indicates a medium range of values, and the light gray indicates a high range of values. The solid, vertical line represents a goal or benchmark, while the blue bar indicates the actual value of the metric. This example shows that the metric fell short of its goal and is within the medium range of acceptable values.
A line graph that is minimalistic in style is often called a “sparkline.” This sparkline enables the end-user to see the trend
of the metric without distracting them with additional clutter.
Min: 1200Max: 2870
40 41
NETWORKDescription
• Great to depict relationships between related items, using nodes (circles) of varying sizes and lines of varying thickness that represent the relationships between the nodes
• Size of nodes and thickness of lines represent metric values
Pro Tip• Use colors to distinguish relationships and patterns
Avoid• Using if there are only small sets of data • If relationship connections are irrelevant
Use Cases• Retail stores demonstrating customer buying habits,
especially in terms of combinations (e.g. “customers also bought” visualizations)
• Tracking airline flight path metrics• Viewing relationships on LinkedIn or other social media
Alternative / Related Visualizations• Heat map• Graph matrix• Scatter plot
Showing product affinity and buying relationships effectively can be a daunting challenge. The network visualization is a great way to solve this problem. By both color coding and adding weight to the affinity lines, the end-user can quickly grasp relationships and their performance in relation to one another.
Product Affinity
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0
10
20
30
40
50
60
0%
20%
40%
60%
80%
100%
iPhone Samsung HTC Motorola Nokia LG
Num
ber o
f Ret
urns
% o
f Tot
al R
etur
ns
Note on MetricsAxis Y1: Actual AmountsAxis Y2: Running Percent = Running Amount/Total Amount
PARETO CHARTDescription
• Contains both a bar and a line graph• Values are represented by descending bars• Running % to total is represented by the line• Depicts percent to the total while displaying actual values
Pro Tips• Use to compare percentage to total of multiple items• Use subtle horizontal grid lines for the y-axis to avoid
distracting from the data points• Use different line styles to show baselines, benchmarks,
goals, etc.• If showing a trend is more important than showing
detailed values, use minimal styling to create a “sparkline” type of visualization
Avoid• Using too many contrasting colors• Graphing items with a broad numerical scale• Showing zero (0) on the scale if it is not needed• Clustering a large number of items for comparison• Using data markers when comparing multiple items over
many data points
Use Case• A retail store graphing the most commonly returned items based on defects
Alternative / Related Visualizations• Pie chart• Stacked bar chart
This valuable and easy to understand visualization is great for showing the age-old “80-20 rule.” By graphing absolute values on the bars and calculating a running percent to total on the line, the end-user can see where the 80-20 split occurs.
Smart Phone Returns From Defects
44 45
PIE CHARTDescription
• Shows proportions of categories to the whole
Pro Tips• Be aware of chart size when determining number of
categories for comparison• Be aware of color combinations; avoid distracting colors• Show percentage to the total as well as the actual values
Avoid• Using if data contains multiple categories of similar size• Using when there are too many categories to compare
(for example, do not exceed five or six)
Use Case• Comparing census demographics in a specified geography
Alternative / Related Visualizations• Polar chart / radar chart• Stacked bar chart• Stacked area chart• Funnel• Cylinder
White - 333
19%
6%
25%37%
13%
African American - 225
American Indian - 54
Asian - 114
Hispanic - 117
This example of a pie chart does a great job at both showing the percentage share of a pie slice, as well as its absolute value. The use of color from blue to green is a natural color progression and as a result, easy for the end-user to follow.
Population by Ethnicity
46 47
POLAR CHART/RADAR CHARTDescription
• Grid lines emanate from a center point, representing larger values for each additional outer line
• Data markers on the grid lines are connected by straight lines, resulting in shapes that visually depict data concentrations
Pro Tip• Shade with a semi-transparent color to show overlap
Avoid• Unless data is exceptionally suited for this representation• If data is consistently the same• Using if data contains numerous categories
Use Cases• Plotting common retail figures for various product
categories within a store• Showing multiple figures and their share in relation to one
another over an extended period of time
Alternative / Related Visualizations• Pie chart• Scatter plot• Bubble grid
This example quickly illustrates the relationship between two metrics across multiple categories. A larger, more spread-out shape would show that a metric is performing quite well. A smaller, condensed shape would illustrate that the metric could likely do better.
This type of visualization is a
great way to show the share of multiple
metrics over time. Florence Nightingale
provided the most famous example of
this visualization, diagramming the
causes of mortality in the military field
hospital where she worked.
Unit Performance by Product Category
48 49
SCATTER PLOTDescription
• Shows two metrics in a set of data• Plots one metric on each axis• Shows the effect of one metric on the other• Shows concentration as well as outliers within a large dataset
Pro Tip• Useful for a large body of data containing two related metrics
Avoid• Trying to depict precise reporting
Use Case• A healthcare organization plotting patient utilization rates
versus claim cost
Alternative / Related Visualizations• Bubble grid• Microchart• Interactive bubble graph• Polar chart / radar chart• Heat map
Util
izat
ion
%
Claim Cost
75%
65%
55%
45%
35%
25%
15%
5%
$5,000 $10,000 $15,000
Scatter plots are an excellent way to show patterns and groupings of things. On the flip side of that coin, it is also a great way to show outliers or data points that don’t group with others. This type of analysis allows the end-user to look further into these data points and analyze why they are different from the rest.
Patient Utilization Rates / Claim Costs
50 51
THERMOMETERDescription
• Like gauge and cylinder, the thermometer visualization is effective for measuring the progress of a single metric toward a goal
• Arguably better than a gauge because the goal is at the top rather than at the side
Pro Tips• Use threshold color to indicate performance
Avoid• Using only red due to its negative connotation
Use Case• Tracking department sales goal in a retail environment
Alternative / Related Visualizations• Bar chart• Cylinder• Gauge
The classic thermometer shape makes it intuitive for the end-user to see how a metric can grow.
March Jewelry Sales Goal Progress
$10K
$20K
$30K
$40K
$50K
$60K
$70K
$80K
$90K
$100K
$110K
$120K
52 53
$0
$28,000
$56,000
$84,000
$112,000
$140,000
Revenue Damaged LaborCosts
MaterialCosts
Refurbished Sales
Profit
$125k ($10k)
($30k)
($15k)
$34k $104k
WATERFALLDescription
• This visualization is great for “what if” analyses (e.g. how sales could affect returns)
• Shows how different aspects of the business positively or negatively affect the bottom line
Pro Tips• Specify color for positive and negative values across metrics• Use for theorizing possible outcomes
Avoid• Using as a true predictive analytic tool
Use Case• A company adjusting their income and cost stream
projections in order to see how it would affect their bottom line
Alternative / Related Visualizations• Funnel
The use of different colors supports the ebb and flow of the descending and ascending bars. Typically, one might use green to indicate growth and red to indicate loss.
July Shoe Sales
54 55
Midwest Unemployment Rate and Population
WEIGHTED LISTDescription
• Combines the visual impact of a heat map with the intuitive, linear nature of a table
Pro Tips• Use red, yellow, and green to indicate performance• Use monochromatic banding when performance isn’t
being measured
Avoid• Using with a long list that would be better presented in
the compact nature of a heat map to avoid scrolling• Two-color transitions unless using monochromatic banding• Using when metrics are unrelated• Using when metric variance is too high or too low
Use Case• Measuring population and unemployment rate for a
geographic region
Alternative / Related Visualizations• Heat map• Data cloud• Bubble grid• Scatter plot
State UnemploymentRate Population
North Dakota
South Dakota
Nebraska
Iowa
Minnesota
Kansas
Michigan
Wisconsin
Indiana
Ohio
Illinois
2.7%
3.7%
3.9%
4.6%
4.8%
5.6%
6.5%
7.5%
7.5%
8.9%
9.0%
699,628
833,354
1,855,525
3,074,186
5,379,139
2,885,905
5,726,398
6,537,334
11,544,225
12,875,255
9,883,360
Many end-users love tables. By adding color to show performance, and proportionally-sized rectangles to indicate size, the end-user can gain additional insight to the figures — without losing the linear, easy-to-follow layout of a table.
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LEARN MORE!ABOUT LANCET
ABOUT THE LANCET DESIGN TEAM
This guide is only the tip of the iceberg when it comes to
visualization best practices that can enhance your business
strategies.
Learn more via our blog, www.lancetdatasciences.com/blog
Including:
• Details that can make or break the impact of your visualization
• Your target audience: three things you cannot afford to forget
• Common errors that make you look like a rookie
The Business Intelligence (BI) specialists at Lancet℠ help IT
professionals and business leaders with strategic leadership,
hands-on project implementation and professional services
across the entire lifecycle of the BI program. Solve your most
complex challenges using the experience and knowledge of the
Lancet team to provide options and deliver solutions.
• Focused on BI since 1997• Recipient of numerous vendor, partner and
industry awards• Hundreds of successful BI projects completed• Over 1 million hours of services delivered• More than 100 consultants serving clients worldwide
The Lancet Design Team is a group of design professionals
dedicated to the craft of designing and implementing web and
mobile Business Intelligence dashboards. Their role is to deliver
concept and production dashboards that exceed industry
expectations for usability, user adoption and general appeal.
THE LANCET GUIDE SERIESData Visualization Guide
Guide to Basic Analytical TechniquesDashboard and Mobile Survival GuidePlatform Administration Field Guide
Download at:lancetdatasciences.com/lancet-bi-guide-series
COMING SOON
58
11980 Portland Avenue South • Burnsville, Minnesota 55337 • 952.230.7360 • www.lancetdatasciences.com
Los Angeles | Minneapolis | Charlotte | New York | Bangalore
Contact Lancet for design consulting, custom visualizations or dashboard development.
Learn more:
www.lancetdatasciences.com/dashboards
Maximizing Return on Data ®
[email protected] | 952.230.7360
