This document provides an overview of best practices for creating compelling Power BI reports through storytelling with data. It discusses choosing the appropriate visualizations depending on the audience and data, using color and design principles to avoid clutter, and prompting the audience with the next steps. Key tips include using simple text, tables, line graphs and bar charts to tell stories with data, avoiding overused visuals like pie charts, and providing context through bookmarks and a help section. The target audience is analysts and decision-makers who need to present data to prompt action.

1. Storytelling with Data with
Power BI
How to create compelling Power BI reports
By Ike Ellis, MVP

2. • /ikeellis
• @ike_ellis
• www.ikeellis.com
• youtube.com/IkeEllisOnTheMic
• Founder of San Diego Power BI
UserGroup
• Founder of the San Diego Software
Architecture Group
• Co-chair of San Diego Data
Engineering Meetup
• MVP since 2011
• Author of Developing Azure
Solutions, Power BI MVP Book
• Speaker at PASS Summit, SQLBits,
DevIntersections, TechEd, Craft,
Microsoft Data & AI Conference
Ike Ellis
General Manager
Data & AI Practice Solliance

3. Agenda
• Before you begin
• The importance of context
• Identifying your audience
• Choosing a tone
• Choosing the correct visual
• Text
• Tables
• Heatmaps
• Line graphs
• Vertical bar chart
• Vertical Stacked Bar Chart
• Waterfall charts
• Visuals to avoid
• Design the report
• The appropriate use of color
• Organizing data
• Avoiding clutter
• Prompting the next steps
• Use bookmarks
• Help tab
• Final thoughts and recommendations
Target audience
• Anyone who uses data to prompt action for
themselves or others
• Including:
• Analysts
• Decision-makers
• Students
• If you are asked to “show data”, this
presentation is for you

4. The difference in exploratory vs explanatory work
Exploratory Analysis
• You are understanding the data
• Looking for interesting data that
might prove or disprove assumptions
• Hunting for a diamond in the rough
• May create many visuals and data
artifacts that are of negligible value
• Should not be shared for public
consumption
Explanatory work
• Should be brief
• Resist the urge to share everything
you’ve learned
• Focus on what your audience needs
to know

5. Before you begin
• What is your relationship with
the audience?
• Do they already trust you?
• Is this presentation meant to
show how smart you are?
• How receptive with you
audience be?
• The presentation is not about
you
• Facts might not need trust
• Reports should focus on
teaching, warning, or action
• After consuming your content,
audiences should be asked to
make a decision about what to
do next or what they learned

6. Before you begin
• Define success
• Think about the delivery
mechanism
• Live meeting
• Email report
• Ad hoc
• Scheduled report
• Think about consistency

7. How to choose the correct visual

8. Simple text
• Sometimes it’s better to be clear on the report about the
message you want to send
• Sometimes simple numbers and text tell a clear story

9. Tables
• Human readable
• Start at the top, read left to right
• Filled with text
• Can contain visual queues to help the viewer
• Try not to overload them
• Avoid being comprehensive
• Avoid in live presentations, too dense
• People will argue about every little number and miss the main
message

10. Table Tips
• Keep it to a few columns and rows
• Avoid heavy borders
• Most recent data or largest values on top
• This is typically what people care about the most

11. Heatmap
• Right-click on the amount
value and choose
Conditional formatting
• Choose a color for lowest,
medium, and highest
amounts
• Allows you to easily pick
out the highest and lowest
values

12. The need for graphs
• Graphs allow us to interpret data
very quickly
• Graphs allow quick summarization
of large amounts of data
• You only need to master a few of
them to be a good data storyteller
• Humans take about 13 milliseconds
to process an image
• 60,000 times faster than processing
text
• Humans retain images in their
brain far easier than text
• Falls into four categories
• Line
• Bar
• Points
• Area

13. Scatterplot
• Good for showing the
relationship between two values

14. Adding a trend line
• Change from scatter
chart to line chart
• Set stroke width to
0 on the line (to
make the line
disappear)
• Turn on Show
Markers and then
chose a marker
shape of a dot
• Trend line is in the
analysis section

15. Line graphs: This time with lines
• Used to plot continuous data
• Points are physically connected
via the line
• Continuous data is often days,
months, etc

16. Line graphs for comparison

17. Bars
• Very useful and should be relied
upon
• Most viewers know how to view
them
• Easy to read

18. Bar chart tips
• Should always start base
zero
• If not, it looks like lying
when comparing
• Keep axis notation on left,
where easily read
• Great for comparing values
in categories
• Great for seeing the impact
of a before/after decision

19. Bar chart: Choose sort order

20. Stacked Bar Charts
• Easy Comparison • Hard Comparison

21. Horizontal vs Vertical?
Choose which one is easier to read

22. Waterfall
• Used to pull apart things that
have happened
• Show a starting point along with
the increases or decreases
• Here is a breakdown of a
massive hiring effort
• Of course, waterfalls can go
down, too. This chart is a good
method for representing this

23. Area graphs
• Humans have trouble reading
them without training
• A lot of effort for not a lot of
value

24. Ribbon Chart
• Needs some training to use
• Quickly discover which data
category has the highest rank
(largest value).
• Effective at showing rank
change
• The highest value always
displayed on top

25. Bullet Graph instead of Gauges
Bullet graphs are denser. They allow a categorization of data. Couple them
with sparklines and the tell a fuller story

26. Spark lines can be very powerful
• https://learn.microsoft.com/en-us/power-bi/create-reports/power-bi-
sparklines-tables
• Tiny lines that add context to values in a table or matrix
• Can be very powerful when combined with bullet graphs

27. Visuals to be avoided
• Pie
• 3-D
• Donut Chart
• Secondary Y-axis
• Too many bars in a bar chart

28. Storytelling vs Monitoring
• Storytelling is convincing
someone of an idea, decision,
problem, solution, or to gain
agreement on any topic
• Monitoring is insuring the health
of a process, organization, team,
product, assembly line, or any
other topic
Now we will talk about generic report and
dashboard design that will help with monitoring

29. Visualization: Bad Dashboard
Space wasted
with gauges
3-D Visuals
Colors and
gradients with
no meaning
Values have no
comparisons
to indicate
good or bad
values
Donut charts
are hard to
read and
compare
categories
Data is not
actionable

30. Stephen Few Design Ideas
• “The main problem with dashboards today is they don’t say enough,
and what they do say, they don’t say very well.” – Stephen Few
• A good dashboard must:
• Offer meaningful comparisons
• Display data that is timely and reliable
• Express data in a manner that assesses performance
• Displays all pertinent information in a single screen
• Offers the next action

31. Power BI -Visualization: Stephen Few
No gauges,
very dense
information
No 3-D visuals
Greyscale is
dominant
Color is used
to catch
attention
Values
comparisons
against goals
No donut
charts or loud
visuals for no
reason
Data is
actionable.
Red dot is
warning to
take action
Small title and
legend with a run as
date and a help
button for more info

32. Another Stephen Few Example

33. Meaningful Comparisons

34. Display data that is timely and reliable
• Usually daily is enough
• Inter-day data often is incomplete
• Not showing shipping until the end of the day
• Cancellations and ordering mistakes
• People rush to put in their order before FedEx or UPS pick up inventory
• People do their banking after hours
• Data should be in a data platform where data pipelines can be tested,
monitored, and more easily changed

35. Express data in a manner that assesses performance
• Spark lines that mark improvement or degrading performance
• Vs Prior period (usually month is enough unless seasonality requires a
13 rolling month comparison)
• Vs Goal

36. Displays all pertinent information in a single screen
• Dense
• No horizontal scrolling
• Few multiple tabs
• Avoid comprehensiveness
• Give enough information to inspire action
• Reporting is not intended to be data exploration. We have better ad
hoc tools for that
• Answering questions is overrated. Inspiring action is where its at!

37. Offers the next action
• Hyperlinks
• Bookmarks
• Drillthroughs and drilldowns
• Embedded in a wider application
• Phone numbers and email address links
• Alerting

38. Nature walk in San Diego and Seattle

39. Power BI - Visualization: Use color sparingly.
In nature, colors do two things:
1) Entice
2) Warn
So let’s use them sparingly..
WARNING: POISON FROG!

40. Power BI - Visualization: Cynthia Brewer

41. No need for a large report title on the top
• Logos change
• Logos waste space
• Everyone already knows what company
they work for
• Company colors are tiring
• And they change too

42. No need for a background image
• Again, boring is more usable and less tiring
• Good for infographics, not good for daily usage
• Users will focus on the choices of color and not on the data

43. Power BI: Tips for Visualization
• Make the most important information the biggest
• Put it in the upper-left corner

44. Power BI: Use bookmarks to clear filters

45. Power BI: Use bookmarks to create a portal
• https://www.blue-granite.com/blog/create-an-app-like-experience-
in-power-bi-with-bookmarks

46. Power BI: Use bookmarks for pagination
• https://community.powerbi.com/t5/Data-Stories-Gallery/Pagination-
in-Power-BI-Reports-utilizing-Bookmarking/td-p/325702

47. Power BI: Contests
https://powerbi.microsoft.com/en-us/blog/tag/contest/

48. Help tab
• Technical stake holder
• Last date updated
• Any comments or wiki thoughts
• Definitions
• Business stake holder: who to call if you want to change the report
• Subscription information
• Items slated to change in the future
• Version number
• Security information
• Who to contact if you need access
• Date the underlying data was last updated

49. Recommended books

50. • /ikeellis
• @ike_ellis
• www.ikeellis.com
• youtube.com/IkeEllisOnTheMic
• Founder of San Diego Power BI
UserGroup
• Founder of the San Diego Software
Architecture Group
• Co-chair of San Diego Data
Engineering Meetup
• MVP since 2011
• Author of Developing Azure
Solutions, Power BI MVP Book
• Speaker at PASS Summit, SQLBits,
DevIntersections, TechEd, Craft,
Microsoft Data & AI Conference
Ike Ellis
General Manager
Data & AI Practice Solliance