To overcome IT Challenge , which is: Product Cycle Shorten , Unpredictability, Need to replan faster, Predication Future, Respond to Market, Focus from PROCESS to People, Data Doubles every 18 Months Hyper Connected People in Real Time interacting in an unstructured way, We use the capability of Analytic and big data with Predictive Analytic

1. Information Technology Conference for Academia and Professional
( ITC-AP 2013)

2. Why Analytic ?
• 71 million Indian population of face book
users , 16,314,838 (2011) Delhi, Population
• 80 million LinkedIn users from India
• 4 billion mobile phones users in the world

3. Why Analytic ?
• A CEO’s 500 emails a day
• Creates new jobs (Uses Crowdsourcing to
Organize Inboxes Email Valet
• https://sites.google.com/site/professorlilisaghafi/classroom-
news/stanfordresearchprojectusescrowdsourcingtoorganizeinboxes
• HR can use this data to create new jobs

4. • Just add Analytic to
almost anything see
what is happening

5. Just add Analytic

7. Analytic Result for toothbrush

8. Nicke’s Analytic

9. EmailValet
• EmailValet, a graduate research project at
Stanford, finds
– remote assistants through the crowdsourcing-for-hire
Web site oDesk,
– then allows them to read a user’s messages and
create a to-do list from the information they’ve read.
– Like some valet keys that allow parking attendants to
open car doors and start the engine but prevent them
from getting into the glove compartment or the trunk,
• EmailValet lets users select what kinds of e-mails
their assistants can read.

10. BIG DATA
• Migration to Delhi from the rest of India
continues (as of 2013), contributing more to
the rise of Delhi's population than the birth
rate, which is declining.
• The Population of Delhi is growing at a rapid
rate in last 20 years.

11. What is the use of these data?
• These Data can change the product of a
business
• 3 Industrial Revolution, the third one is IT
– First industrialization
– Second was electricity
– Third is IT

12. Future Jobs

13. Smarter Jobs

14. smarter software
• Everything in the factories of the future will be run by
smarter software.
• Digitisation in manufacturing will have a disruptive
effect every bit as big as in other industries that have
gone digital, such as office equipment, telecoms,
photography, music, publishing and films.
• And the effects will not be confined to large
manufacturers; indeed, they will need to watch out
because much of what is coming will empower small
and medium-sized firms and individual entrepreneurs.
• Launching novel products will become easier and
cheaper.

15. "Third Industrial Revolution is IT"
• How the Internet, Green Electricity, and 3-D Printing
change the future
• Jeremy Rifkin, Writer and Economist
– Internet technology and
– renewable energy are
– merging to create a powerful "Third Industrial Revolution."
• He asks us to imagine hundreds of millions of people
producing their own green energy in their homes,
offices, and factories, and sharing it with each other in
an "energy internet," just like we now create and share
information online.

16. Real Time Enterprise management
• Though not particularly well defined, generally
accepted goals of an RTE include:
– Reduced response times for partners and customers
– Increased transparency, for example sharing or
reporting information across an enterprise instead of
keeping it within individual departments
– Increased automation, including communications,
accounting, supply chains and reporting
– Increased competitiveness
– Reduced costs

17. RTE
• The importance of RTE in different industry
like;
• Flight corporations
• Healthcare

18. Big Data & BI
• 1 Billion Network Users
• 15 Billion Web Enabled Device
• Data doubling every 18 months , during past
18 hours the data that has been created is
more than the history of human being until
2003
• There more MOBILE device than people.

19. Data Quality
Data Integration
Data Warehousing
Master Data Mgt
Meta Data Mgt
Business Intelligence
Top-to-bottom
visibility required

20. Mobiles +Cloud + Social + Big Data =
Better Run The World
• Cancer Solution
• Detection Of Fraud , 80% of Fraud can be
prevented
• Producing Education through Web , Combine
Mobile + Cloud can be great for teaching

21. Applications for Data Stewards

22. “Computers are useless.
- Pablo Picasso
They can only give
you
answers.”

23. Information
Strategy
Management
Finance
Business Process
Best
practice
Collaboration
Knowledge
Management
Implement New Strategy Integrate AcquisitionLaunch Product
Intelligence = Information + PEOPLE

24. IT Challenge
• Product Cycle Shorten
• Unpredictability
• Need to replan faster
• Predication Future
• Respond to Market
• Focus from PROCESS to People
• Data Doubles every 18 Months
• Hyper Connected People in Real Time
interacting in an unstructured way

25. Big Data Example
• Cricket match and how they collect data and
social interaction and selling in real time to
area of interest

26. SAP & Big Data
• 65000 Employee
• 2010 Hasso Plattner introduced HANA
• From R1 41, years ago
• To R3
• To HANA = OLTP , OLAP can run IN-Memory
database and create the next generation
business platform

29. SAP ON SUITE
• SAP HANA, the in-memory data platform for
real-time business, is a game changer for
companies big and small.
• It analyzes huge amounts of data in
milliseconds, not hours.
• Watch how SAP HANA provides immediate
results and business benefits for the mid-size
Koehler Paper Group, based in Southern
Germany. (Jan. 2013)

30. SAP HANA &
WORKING
SIMPLER FASTER SMARTER
• No need for multi databases
• Run in memory
• Uses 5% of energy of disk
• No need faster storage
• Less than 24 months payback time
• www.suiteonhana.com
• Ferrero chocolate
• XCentric

31. Simple

35. Feedback from BI Users
“Are your BI applications easy to use?”
Source Forrester: August 2008 Global BI And Data Management Online Survey
Base: 82 IT decision-makers

36. © SAP 2008 / Page 36
Ease of Use is The #1 Barrier to Deployment
Top Roadblocks to BI Success
Challenge Rank
Complexity of BI tools and interfaces 1
Cost of BI software and per-user licenses 2
Difficulty accessing relevant, timely, or reliable data 3
Insufficient IT staffing or excessive software requirements
for IT support
4
Difficulty identifying applications or decisions that can be
supported by BI
5
Lack of appropriate BI technical expertise within IT 6
Lack of support from executives or business management 7
Poor planning or management of BI programs 8
Lack of BI technology standards and best practices 9
Lack of training for end users 10
1. Doug Henschen, InformationWeek, “BI Efforts Take Flight”, Oct 13, 2008

37. Intuitive Interfaces

42. BI is too S L O W
0% 10% 20% 30% 40% 50%
Current platform is a legacy we must phase out
Can't support data modeling we need
Poorly suited to real-time or on demand workloads
Cost of scaling up is too expensive
Can't scale to large data volumes
Inadequate data load speed
Can't support advanced analytics
Poor query response
Source: P. Russom. Next Generation Data Warehouse Platforms, TDWI Best Practices Report, 4Q 2009
What problems will eventually drive you to replace your current primary
data warehouse platform?

43. Go FasterColumn databases
Hardware Acceleration
In-Memory Processing
Lower Memory Costs

44. Mobile

45. Adobe Flash Dashboards on Android

46. 10km
De NHM kijker
Eerste Romeinse
nederzetting: “Oppidum
Batavorum”
Jaartal: 12 voor Chr.
Afstand: 300 meter
0.3

47. Filter by: Branch
Highstreet
Operations +23%
NE 0.1km

48. SAP Maintenance
Maintenance
Last checked: 28/9/09
Relative performance: +10%
More details

49. Filter by: Maintenance History
Tower Pipe 3
Last Maintenance: 2 Weeks
E 0.1km
Photo by Thomas Hawk, Flickr

50. 10km
De NHM kijker
Eerste Romeinse
nederzetting: “Oppidum
Batavorum”
Jaartal: 12 voor Chr.
Afstand: 300 meter
0.3

51. SAP Augmented Corporate Reality
(proof of concept only)

53. Data Quality
Data Integration
Data Warehousing
Master Data Mgt
Meta Data Mgt
Business Intelligence
Top-to-bottom
visibility required

54. Applications for Data Stewards

61. Text Analytics

62. CUSTOMER FEEDBACK

63. CUSTOMER FEEDBACK

64. Predictive Forecasting
• Ebay based on previous purchase
• Burberry Store , personalized business IPAD
and sensors

65. Store 23
Current sales: $15k
SE 0.1km
Filter by: Store Performance

66. • Zone of entrance
• Augmented reality
• From real-time data for mangers to zone the
products properly based on the behaviour of
customes

67. How Augmented Explorer Works
1 2
3
Define the points of interest and associated
data and load them into BusinessObjects
Explorer
Calculate direction and distance to POIs
(Point of Interests) , based on the users’
GPS location and compass
Display appropriate
information on the mobile
device
Any source of corporate or
personal data
BI OnDemand

68. Intelligent Airports
• "Improving the passenger experience" is the
number one driver of IT investment by the
majority (59%) of the world's airports.“
• 10% customers have smart phone
• Traffic in the airport can be controlled by
tracing these sensors on smartphones
• Placement of boots and retailers

69. City of Boston BAR citizen Insight
• ‘Boston About Results’ App Puts City’s
Performance Review in Your Hands

70. Analytic
• Predict Market Trends
• Predict market volatility
• We see change in demand supply across your
entire Supply Chain Immediately
• Monitor and analyse deviation & Quality Issues
• Provide Right Offers
• Update window onto future sales , in real time
• Understand what customer say about you
• Predict cash flow
• Think Big, Think different

71. "Think outside the box"
• too close to the detail, focusing only on one section.
What does this tell us? It only tells us what we allow
ourselves to think it tells us - perhaps it opens up the
possibilities of thought? For info. These simple
paragraphs can be aligned to "thinking outside the
box" and "big picture thinking." "Think outside the
box" is a commonly heard phrase that suggests looking
at a problem from a different perspective, and without
and preconceived views. "Big picture thinking" which
refers to being able to looking at the wider context
rather than focus on a specific area.

72. Think Big

73. Think Different

74. Things changed
• More mobile device than people
• In the morning you Rollover to mobile than
your spouse

75. Evolution of REPORT
writing
Standard
Report
Adhoc report
OLAP
Visualization

76. BI Spectrum
SAP Predictive Analysis
Application
Load Data from the
source
Dashboard
& Score card
Exploration
&
Visualization
Predictive
Modeling

77. PA softwares you instal
in 3 minutes and run in
5 minutes
REPORTING
DASHBOARD
SELFSERVICE

78. • Customer choice of bank
– Salary
– Promotion
– Location
• Forecasting Anomalies
• Challenges
• Trend
• Key influencers
Why PA?

79. • PA stand alone
• PA+ HANA
Application

80. • Lots of Data
• Lots of report
• View
• Unreliability of data
When and Why you may
need Analytic ?

81. • BI & Analytic
• Data warehouse
• Enterprise content management (ECM)
Core Analytic Capability

82. Data Quality
Data Integration
Data Warehousing
Master Data Mgt
Meta Data Mgt
Business Intelligence
Top-to-bottom
visibility required

83. Analytic
• Advanced Analytics: Unlocking the Power of
Insight

84. Visual Intelligence
• With Visual Intelligence, you can:
– Deliver faster time to insight in a repeatable, self-
service way
– Maximize business knowledge with a combination of
big picture insights and granular details
– Accelerate decision making with immediate, fact-
based answers to complex business questions
– Increase self-service data usage without adding to
your IT department's workload
– Visualize any amount of data in real time, using in
memory processing

85. Business Intelligence

86. Thank you for being great
audience
Any
Question?
87 Professor Lili Saghafi5/1/2013

87. 5/1/2013 88Professor Lili Saghafi