This document serves as a user guide for IBM's Watson Analytics, a cloud-based self-service analytics solution that simplifies data preparation, predictive analysis, and visualization for business professionals. It emphasizes features like natural language processing for user-friendly queries, automated data handling, and a unified analytics experience aimed at empowering users without technical expertise. The guide outlines key functionalities, including creating dashboards, generating predictive insights, and utilizing templates for various business scenarios.

1. An User Guide of

2.  A Self service, Cloud based
analytics solution.
 Automates data preparation,
predictive analysis and visual story
telling for professionals.
 Enable to navigate through data
and understand the patterns to
make better decisions.
 Powered by IBM’s Watson
cognitive computing technology.

3. • Compared to Watson, Other tools are -(i) too complex,
(ii) hard to access, and (iii) require the skill set of a data
scientist. Reason is clear because these analytical tools
are not developed keeping business users in mind but
technical people to develop customized solutions for end
users.• Watson Analytics also removes a lot of the barriers for
business professionals around usability, getting and cleansing
data, learning different analytical techniques and the cost..
Watson is more portable.
• WA uses natural language to make interaction with
powerful, predictive analytics easier with the ability to
understand key questions, such as: What are the key
drivers of my product sales? Which benefits drive
employee retention the most?

4. 1. Self-service
2. Natural Language
3. Single Business Analytics Experience
4. Stories

5. 1. Self-service: As a business user you can be completely
self-enabled to conceive a need, to get the data, to analyze it,
and to communicate the results all by yourself. Watson
Analytics features the use of predictive analytics to surface
key relevant facts and uncover unforeseen patterns and
relationships. This process sparks new questions and better
insight, directing users to parts of their business that matter
most.
2. Natural Language – Watson Analytics speaks the
language of business and people by enabling someone to
simply type in what they would like to see. WA produces
results that explain why things happened and what's likely to
happen, all in familiar business terms. And as business
professionals interact with the results,

6. 3. Single Business Analytics Experience – Unlike today’s
separate analytics tools designed for different kinds of
analysis and data tasks, Watson Analytics is a seamless,
unified experience that brings together a set of self-service
enterprise data and analytics capabilities on the cloud.
4. Stories: The stories are like templates to start you off on
your analytics process. It could be things like campaign
management for a marketing person; win-loss analysis for
sales; employer retention for HR. These are pre-created
examples that you can use just to learn what you might do, or
use as a template for your own analysis if your business
problem is similar.

7. IBM Watson Analytics sets powerful analytics capabilities free so
practically anyone can use them. Automated data preparation,
predictive analytics, reporting, dashboards, visualization and
collaboration capabilities, enable you to take control of your own
analysis. You can then take the appropriate action to address a
problem or seize an opportunity, all without asking IT or a data expert
for help.
1. Get better data. Data access, refinement, management and analysis
are automated and available from the cloud.
2. Get answers. Ask questions in the terms of your business, whether
you're in marketing, sales, HR, finance or operations.
3. Understand your business. Automated intelligence enables you to
draw conclusions based on what has happened and why.
4. Tell a story. Visualizations help you create clear and compelling
infographics to prove your point confidently.
5. Think ahead. Statistical analysis, correlations and predictions help
you see what is likely to happen and what you can do about it.

8. Before you start working in IBM Watson Analytics, there
are some basic concepts and information to be aware of.
Web browsers
IBM Watson Analytics supports Apple Safari, Google
Chrome, Microsoft Internet Explorer, and Mozilla Firefox.
Navigating to the Welcome page and to other capabilities
Logging off
There is no explicit logoff. To log off, close your web
browser window.
Saving your work
Predictions and views are automatically saved when you
create or change them. Explorations must be manually
saved.
Deleting an asset
You can delete data sets, predictions, explorations, or
views from the Welcome page.

9. Business Scenario
Tell your story with : Watson Analytics

14. Click on Add Drop your file here

15. Explore the disk partition and then click on your .csv file

17. By clicking on Filter, can
explore only either :
1. Data sets
2. Explorations
3. Predictions
4. Views
5. Tutorials and samples

18. Either:
1. Alphabetically
2. Based on
modification

20. Click on Data Set you want to
explore further and select
exploration option.

21. OR
Click on Explore option,
visible at Welcome Page.

22. Exploration window
appears:
1. You can search
Data Set, want to
explore.
2. Either choose from
list given below
with name, data
quality and date
along with data set.
3. Then Click on that
data set.

23. 1. Type your query in
natural language to
explore data set.
2. Create new
Exploration.
3. Also some starting
points given for
reference .

24. •Type your query in search box
It somehow suggests all related
questions, choose one you desire
to refine.
•Below it shows the all solutions
based on the relevancy (very
relevant OR somewhat relevant).
•Click one you want to explore
further.

25. Graph (Tree map)
appear that shows
profits (sums) against
the catering name.

26. 1. Adding Row as Client type results the records of caterings according to client type (fig 1st)

27. 1. Adding Column as City results the tree map drawn for catering name along with cities also.

28. For changing the
visualization, available
types are:
1. Grid
2. Area
3. Bar
4. Bubble
5. Line
6. Pie
E.g.:
1. Pie chart

29. Visualization Type:
Pie Chart

30. Visualization Type:
Grid

31. Visualization Type:
Area

33. LINE CHART:

35. Tree map Heated by catering name according to number of records , such as by clicking
Indore city, shows transport expense (sum) and catering name (=1 record ) appears.

36. 1. Click on Actions option
at bottom.
2. Columns and create a
new column option
appear.
3. Also the Calculation,
data group and
hierarchy options
available.
4. Click on first option
Calculation.

37. 1. Calculation window
appears.
2. Name first box (it can not
be empty) in order to
create a new field.
3. For instance we name it
as total expense.
4. On the right hand side
,perform the calculation
over existing
columns.(shown in image)
5. Click Done.

38. Total expense
column created.

39. 1. Click on Bar at bottom
, it shows the whole
data table.
2. By clicking on, one of
the field small window
appear to set
condition and other
actions.
3. Click on dotted bar.

40. 1. Small window appear.
2. change the type from
number to other.

42. 1. Click on aggregation
option.
2. Small window appear.
3. change the aggregation
from sum to other listed
options.

43. Click on one of the field,
you want to tear down
into the different group.

44. Click on data group
option.
small window appear.
E.g. for Brand field, out
of the four brands we
select 3 brands and left
the takeaway.

45. Name the new
group as grp1
and click ok.
New field as grp1
will now can be
used for all other
actions to
perform in WA.

46. When Click on
Hierarchy option, a
small window appear.
Name it as hr1 for
instance.
Click on Add level.

47. Select one of
the field .

48. Click on Add
level.

49. Click on Done.

50. Select column as hr1
in hierarchy.
Breakdown of profit
by client type tree
map appear.

59. Click On predict option
available on welcome
page .

60. 2. Select your data
set, want to further
predict.
1. Prediction
Window appears.

61. 1. Name your
workbook.
2. Select the
target(s) to
predict.
3. Create prediction.

62. Top predictors of
profit associated
with one field
appears as a Bull
eye chart.

63. Top predictors of
profit associated
with two fields
appears as a Bull
eye chart.

64. Top predictors of
profit associated
with combination
of fields appears as
a Bull eye chart.

65. 1. Click on View All
2. Different Influences
of profit appears as
heat map charts.

66. 1. Click on Edit.
2. Change Current
targets by adding new
target.
3. Click on Accept.

68. Such as: Top
predictors of Brand
associated with two
fields as a Bull eye
chart.

69. 1. Click on Heat map.
2. Main insight and
Details of
corresponding Heat
map appears.
3. Such as : Client
type influences with
predictive strength
of 100% are city
and equipment
expenses.
can also Pin chart

70. Click on Details for
Heat map
corresponding to
different cities.

71. 1. Click On Top field
associations.
2. Top field associations
window appears.

72. 1. Click on one of Top
field associations.
2. Window appears
with Overview , Main
insight and Details
tabs .
3. Such as for City and
Client type that are
strongly associated.

73. 1. Click on Action
option on top.
2. Workbook,Field,Data
Representation and
versions options
appears.

74. 1. Click on data quality
option.
2. For gloris.csv ,Data
quality score is 94
(High quality).
3. Data quality by fields
also showed for
particular field
observation.
4. Such as: for Brand,
no missing values
and categories are 4.

75. 1. Click on Field
properties option .
2. For gloris.csv, all fields
of data listed at left
side.
3. Select one of the field.
Also can sort them on
basis of Role, Label and
interestingness.
4. Such as: for City the Bar
chart of different cities
and its Role as input
appear.

76. 1. Click on Field properties
show more option.
2. It shows the
measurement level of
field.
3. Option to assign the
values of field as missing
values showed below the
measurement level
option.
4. Below missing values,
option to assign the
values of field as Label
showed also.

77. All pinned
Predictions
Can be seen
in My pins
option on
the very top

79. Click on Assemble option
Present at welcome page to
create a new Dashboard to
tell your story in more
systematic way.

80. 1. Name your view
2. Select a template
3. For instance, we choose
Single page form
dashboard.
4. Choose one of the
Layout .
5. Click Create.

81. Drag the Exploration,
charts or predictions
from saved pins at My
Pins to the Layout by
cursor.

82. OR search in the given box
above for desired result.

83. Use the data set you
indented to use.

84. 1. click on Action option
on top.
2. Color palettes and Bar
Color options are available
in visualization details .
3. Select one of the
palette.

85. 1. Name your view
2. Select a template
3. For instance, we choose
Tabbed form dashboard.
4. Choose one of the
Layout .
5. Click Create.

86. Drag the Exploration,
charts or predictions
from saved pins at My
Pins to the Layout by
cursor.
OR
Search in search box for
indented result and adjust
them at layout
accordingly.

87. 1. Change Themes by
clicking on Action option
on top.
2. Default , Light and Dark
themes appear.
3. Select one of the
theme. E.g. we choose
Light theme.

88. 1. Name your view
2. Select a template
3. For instance, we choose
Infographics form
dashboard.
4. Choose one of the
Layout .
5. Click Create.

89. Drag the Exploration,
charts or predictions
from saved pins at My
Pins to the Layout by
cursor.
OR
Search in search box for
indented result and adjust
them at layout
accordingly.

90. 1. Name your view
2. Create your Story.
3. Choose one of Slide
show Layout.
4. Click Create.

91. Drag the Exploration,
charts or predictions
from saved pins at My
Pins to the Scenes by
cursor.
OR
Search in search box for
indented result and adjust
them at layout
accordingly.

92. Can see the slide show in
full screen mode.
Play the slideshow
Play the slideshow

93. 1. Here with help of Watson Analytics , we can predict the driving factors
of our Business .
For instance profit of Catering business influenced with Equipment
Expenses, City and number of clients more compare to other factors ;
Such as for city Delhi and Mumbai the profit of company is highest.
2. We have concluded the strong correlation between the fields of data
set such :
City and Client type are strongly correlated, also profit and
organization revenue are also positively correlated.
3. Analysis of Data Set provides the useful information Such as: Top
Clients by profit are
politicians , Top Brand is Takeaway by profit gain.
4. Top catering is Neon by profit gain and for Equipment Expenses Lorra
company is lowest ranked.
5. Data Quality of Data set can also be observed such in regards to

94. 1. AnalyticsZone from IBM : http://www.ibm.com/analytics/watson-analytics/
2. Business Analytics Blog by Vikas Manoria
3. Forbes.com for Watson Analytics Beta