Treemaps are a data visualization technique that arranges hierarchical data into a two-dimensional map, where each cell's size corresponds to a variable such as the object's importance or volume of data. The document discusses using treemaps to visualize server performance exceptions detected by BMC monitoring software. It proposes arranging servers in treemaps grouped by location or exception type, with cell color indicating capacity, importance or exception severity/volume. Treemaps could help analysts more efficiently browse exceptions across large server groups compared to traditional heatmaps or sorted lists. Research is needed to determine optimal variable mappings and address challenges like lengthy node labels and accessibility.

1. drive
Using Treemaps to
Visualize Performance
Exceptions
Len Conte
Len_conte@bmc.com
781-663-4870
John Dozier
April 13, 2005

2. Agenda
› Background
› Heatmaps vs. Treemaps
› Treemaps – Taxonomy, Advantages/Disadvantages, Examples
› BMC – Use Cases
› Research Questions

3. Data
Visualization - Goals
Organize the patterns inherent in data to make the
complex clear.
Exploit the dynamic, interactive, medium of graphical
displays to devise external aids to enhance cognitive
abilities.

4. Data Visualization Tools
› Heatmaps
 Collection of cells representing objects
»cells are color coded
»each cell same size
 Collective color pattern of cells make portions of the map appear “cool”
or “hot”
› Treemaps
 Collection of cells representing nodes in a hierarchy
»cells are color coded
»each cell variable size - proportional to some variable in the hierarchy
 Originally designed to replace directory trees

5. Heatmap - Stock Closing
www.screening.nasdaq.com/heatmaps/heatmap_100.asp
Cell based
•each cell = a stock
•cell color = % change in price
•every cell is the same size
Note: cells sorted in descending order

6. Treemap
www.smartmoney.com
cell group = market
segment
cell = a stock
cell color = % change in
price
cell size = market
capitalization of the stock

7. November 30 th ,1998
A bad day on the
Wall Street

8. Ben Schneiderman –
University Maryland
http://www.cs.umd.edu/~ben/

9. Treemaps –Taxonomy
www.hivegroup.com
Map
filter
legend
prompt -variable
Cell group
Cell group label
Cell/node
Color, size, location
Cell label
Details

10. Treemaps –Styles
www.hivegroup.com
Slice & Dice
Squarified

11. Advantages - Amplifying
Cognition
• 100-1000s of objects
displayed on a single
screen
• Compress a hierarchy
into a single screen -
bird’s eye view
• Multi-variant – size,
color, location
• Reduced search –
picking out the best
and the worst
• Filtering – user control
• Details on demand –
drill down, tooltips
• Pattern recognition
within a blocks of cells
• Pattern recognition
across maps of various
time slices

12. Disadvantages –Amplifying
Cognition
www.Peets.com
• “ Don’t make me think”
mapping size of cells and
color of cells to variables
• Volatile data can make
the display re-map
• Perceptual differences
arise when area
comparisons are made
between nodes of
differing heights and
widths
• Small weighted nodes
can drop off the display
or become illegible
•Textual labels are
needed for context…for
small cells this is
problematic
•508 issues – conveying
the meaning of patterns

16. BMC Software
› Software monitors the availability of 100’s -1000’s of servers
 Users are IT Operators
 Operational duties
› Software monitors the performance of 100’s -1000’s of servers
 Users are IT Performance Analysts, Capacity Planners
 Planning and management duties

17. Current - Heatmap

18. Project :
Performance Exceptions
Monitoring & Escalation (PERE)
Use Cases:
› System detects a performance exception and pro-actively
notifies analyst
› User ad hoc browses the system to see what servers are
having performance problems

19. Browsing for exceptions
Currently

20. Browsing using Treemaps

21. Browsing using Treemaps

23. Browsing for exceptions
Currently

24. Some Design Decisions
Group by :
› Server grouping (location, department, server type, application)
› Exception question/detector
› Server importance to the business
Cell = server, any infrastructure object
Cell color
› Capacity of the server
› Importance of the server to the business (impact)
› Volume of exceptions
› Severity of the exceptions
Cell size
› Capacity of the server
› Volume of exceptions
› Severity of exceptions
Filter
› Time
› Grouping
› Severity
› Volume

25. Research Issues/Problems
› Determining optimal Out of the Box variables
› Learning curve Reducing initial color/size de-coding
› Efficiency of use – faster or slower than sorting a list (multiple
sorts), or heatmaps.
› Labels – node labels can be very long
› Time based analysis
 Comparing performance shift to shift, week to week
 Small multiple - calendar
› 508 Accessibility issues
 Color schemes
 Tabular alternative
› Preserving the order cells – enable comparisons across time

26. Small Multiiples – by Week
Week 1
Monday Tuesday Wed Thursday Friday Sat Sun

27. Small Multiples –
Shifts by Week
Monday Tuesday Wed Thursday Friday Sat Sun
Shift 1 8:00 AM – 4:00 PM
Shift 2 4:59 PM – 12:00 AM
Shift 3 12:01 AM – 7:59 AM

28. Small Multiples –
Month - February
Monday Tuesday Wed Thursday Friday Sat Sun

29. Questions?