IBM Watson Analytics is a user-friendly analytics tool designed for business professionals, enabling self-service data preparation and predictive analytics without requiring specialized skills. It addresses the complexity and accessibility issues of traditional analytics tools by incorporating natural language processing and providing a unified analytics experience. The platform allows users to analyze data collaboratively and derive actionable insights, making it ideal for various business applications across different industries.

1. Time for bring your own analytics
SHEETAL SHARMA
Intern at IBM innovation Centre

2. Watson Analytics
What is Watson Analytics?
Why Watson Analytics?
Features of Watson Analytics

3. What is Watson Analytics
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.

4. Why Watson Analytics
Analysts say only a small fraction of
business professionals use analytics tools as
part of their decision making today
primarily because the 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.

5. Why Watson Analytics
“The purpose of Watson Analytics is to reinvent that
whole analytical experience and to help a
businessperson, not a specialist, but to help a
businessperson inform their decisions with better
information and better insight.

6. Why Watson Analytics
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. 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?
Which deals are most likely to close?

7. Key Innovation Features
These are the four WA key innovations that enable
business users to unlock the value of analytics at the
same time reduce the skills required to engage in
advanced analytic –
1 Self-service
2 Natural Language Dialogue
3 Single Business Analytics Experience
4 Stories

8. 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.

9. Natural Language Dialogue
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, they can fine-tune questions to get
to the heart of the matter.

10. 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. Business
professionals identify their problem, and
Watson Analytics can help them source the
data, cleanse and refine it, discover insights,
predict outcomes, visualize results, create
reports or dashboards, and collaborate with
others.

11. 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.

12. Business Case
 There are three TEXTILE companies.
1 Being Human
 Other two are
2 Printo
3 Style
There are 15 clients of each company.
This clients are same for every company.
 By WATSON ANALYTICS we can compare this 3 companies in
respect to all fields of the data set.

13. Contains of data table
Industry
Client Type
Permanent
New Clients
Clients
Dens Suits Permanent Clients
Eastern Comp
Fashion Notes
Best Go
Aviator Ride
SamSun
Rio
Capssy
Kids Style
Stylo
Express Mastro
My Salfy
AntaZone
Jumbo Kids
Joys
Fabrics
Cotton
Wool
Silk
Jute
Synthetic
Total Expense
Total Supply(in lacs)
Power & Fuel Cost(in lacs)
Employee Cost(in lacs)
Selling and Admin Expenses(in lacs)
Other Manufacturing Expenses(in lacs)
Total income
Net Sales
Other Income
Stock Adjustments
Profit By Per Client
New Clients

16. Front Page of Watson Analytics

17. Sign up for the new user

18. Sign in Page

19. Load the Data or Connect to Source

20. Drop the file or tap to browse

21. Click on your data set, three options Exploration
, Prediction, View

22. Data , Data set & Data Quality
 When you load data into IBM® Watson Analytics, it becomes
available for analysis as a data set.
 Watson Analytics assesses your data set for interestingness
and quality. It then determines what you might want to analyze.
 A data set is a collection of data from external sources that is in
the form of a table of rows and columns.
1. Adding a new data set
You can add data that is in a .csv or Microsoft Excel file. If a
Microsoft Excel file contains several worksheets, the first
worksheet is added as a data set.
2. Cleaning your data to improve its quality
IBM Watson Analytics can provide better predictions and
explorations if the quality of your data is high. If the quality of
your data is low, the accuracy of the analyses in your
explorations and predictions is less reliable. You can improve
the quality of your data.
3. Optimizing the quality and usage of your data
When a data set is loaded, IBM Watson Analytics reads the
data and assesses it for data quality. If the data quality score is
low, you can improve its quality and usage so that your
predictions and explorations are more accurate.

23. Some Starting points for Exploration

24. Add a new tap

25. Chart
Clients
Filters

26. Visualization Type

27. Breakdown of-----

28. Total Supply by 3 Companies
Present by
3 different
colors
Pin the
exploration
by click on
the symbol

29. Other options
Add new
column
Change
the data
type

30. Change the data type

31. Select Stock Adjustment Expenses

32. Type is number

33. Change by Time Interval

35. Add Filter

36. Choose any
Field

37. Calculation , Data group & Hierarchy

38. Calculations
Name
1st field 2nd
field
Add more
operators

39. Mathematical
Functions

40. Changes perform by add num & text
Silk increment by 56

41. Create Group
Group
name
Select
Column

42. Choose fields which want to include in
group

43. Selected clients
6 Clients
select in
permanent
group

44. Hierarchy-shows root & node relationship

45. Here Client is root &supply is leaf node

46. Profit by per client
Pin the
exploration

47. Area Chart-visualization option

48. Column insert
Insert a
column

49. Prediction

50. Name

51. properties

52. Workbook property

53. Up to 5 targets add

54. Field Properties

55. Versions

56. Data Quality

57. Click here
highly
predictive
strength

58. Overall net sales shows in chart

59. Values shows in Detail

60. Statistical Detail

61. Top Field Associations

62. My Pins

63. Change or add the target

64. View all-show all the influences

65. View-Create a Dashboard

66. Create a dashboard
Name of
data set
Dashboard
types

67. Write the query

68. Profit by per client

69. Insert in dashboard

70. Supply by industries

71. Compare b/w incomes of companies

72. Dashboard Properties

73. Create the Slide Show(BETA)
In pins we
store the
different
Fields ,so
drag any
to plan
board

74. Drag

75. Full Screen mode
Full
Screen
mode
option

78. Conclusion
 Watson Analytics is the software which is
provide many features with easy use.
 Here in textile business by this analytics I
easily see and understand all the queries.
 It shows relations b/w fields and also
shows the information which Is helpful for
future planning of business and as well as
profit.
 Most wonderful that if ones you know about
it then in future you no need of any
specialist . you can do your work your self.

79. References
 vmanoria.blogspot.com/
 watson.analytics.ibmcloud.com