Did you know that THIS MORNING there is more data in the world than EVER BEFORE?! By 2018, 40% of enterprise architecture teams will be distinguished as leaders by their primary focus on applying disruptive technologies and the power of Big Data to drive business innovation.

1. Professor Lili Saghafi
Big Data and Integration with BI
May 3 rd , 2017
@Lili_PLS
UCLA , CA

2. What Is Big Data?
•I mean really…
Did you know that THIS MORNING
there is more data in the world
than EVER BEFORE?!

3. Big Data Architectures = Digital
Business
• By 2018, 40% of enterprise architecture teams will be
distinguished as leaders by their primary focus on applying
disruptive technologies to drive business innovation.
• By 2018, 40% of enterprise architecture teams will be
responsible for advancing the organization's digital business
strategy.
• By 2018, the new economics of connections will drive
organizations to increase investments in connected physical
assets and systems by 30%.
• By 2018, 20% of enterprise architects will use business
ecosystem modeling to identify and predict business
moments.
Source: Gartner, Predicts 2016: Five Key Trends Driving
Enterprise Architecture Into the Future

4. “Computers are useless.
- Pablo Picasso
They can only give you
answers.”
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5. IT IS THE TIME TO THINK
differently
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6. Since 2008, the number of things connected to the Internet has exceed the number
of people on earth
Internet of Things
2003 2010 2015
* Berg Insights (2011)
By 2020 there will be 50 billion*
Definition: The output of sensors and devices used to measure and record the events and situations in the physical world is
e-generated data. As sensors proliferate and data volumes grow, traditional technology cannot handle volume, type and speed – hence the need for SAP HANA.

7. IoT is relevant to all of us
THE INTERNET OF THINGS
Healthcare
& Life Science Transportation
Industrial
Consumer
& Home
Energy
Buildings
IT &
Networks
Security/
Public Safety
Retail
Tracking Human, Animal, Postal, Food /
Health, Packaging, Baggage
Jeeps, Cars,
Ambulances
Breakdown,
Lone Worker
Tanks, Fighter Jets
Battlefield Comms
Homeland Security,
Fire
Environ, Monitor, etc.
POS Terminals
Tags
Cash Registers
Vending Machines
Signs, etc.
Servers
Storage
PCs, Routers
Switches
PBXs, etc.
Vehicles, Lights, Ships
Planes, Signage
Tolls, etc.
Assembly / Packaging,
Vessels / Tanks, etc.Motors, Drives,
Converting Fabrication
Pumps, Valves, Vats,
Conveyors, Pipelines
MRI, PDAs
Implants, Surgical
Equipment
Pumps, Motors
Telemedicine,
etc.
Digital Cameras
Power Systems, MD
Dishwashers eReaders
Desktop Computers
Washers / Dryers
Meters, Lights, TVs, MP3
Game Consoles, Lighting
Alarms, etc.
Turbines
Windmills
UPS
Batteries
Generators
Meters, Drills
Fuel Cells, etc.
Alternative
Solar, Wind,
Co-Generation,
Electrochemical
HVAC
Transport
Fire & Safety
Lighting
Security
Access, etc.
Beecham Research

8. By what tool it connects?
•BIG DATA
'Big Data' is a term used to describe collection of data
that is huge in size and yet growing exponentially with
time.
Typical sizes are being in the range of multiple
zettabyte.
1021 bytes equals to 1 zettabyte or one billion
terabytes forms a zettabyte.

9. HUGE
•BIG DATA
• From fridges that scan and order to supliers
To Toilets that generate data about the user, urine
sample, ….
All is about data & IoT

10. “Bad news — the scale is
threatening to cut off our
access to the fridge…’

11. IoT Stands For…. The Internet of
Toilets?!

12. For anyone
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13. Mobile users

14. 2017 Data
7.5 Billion (2017) The current world
population is 7.5 billion as of May 2017
according to the most recent United
Nations estimates elaborated by
Worldometers.
Number of global mobile subscribers to surpass five
billion this year ( 2017) , world Bank data

15. Mobile
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16. New Technologies easing our path to
success
• We have possibilities
like Augmented
Corporate Reality
(proof of concept only)
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17. Quantum Processor , next generation
of computing
http://research.ibm.com/ibm-
q/quantum-primer/
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18. Analytics and BIG DATA Changing the World
Digital Transformation
Digital Business
Internal

19. 19

20. New Technology = Business
Opportunity

21. Digital is moving to the core of
business strategy

22. Digital Business
But only 25% have a plan in place, and less than 15% are
funding and executing a digital transformation plan.
– Digitalist Magazine, 2015
”
“90% of CEOs believe the digital economy will have a major
impact on their industry.

23. “What does digital
business mean for
your company and
industry?”
What IS Digital Business?
CEOs
Cloud
computing?
Social media?
E-commerce?
Customer self-
service?
Online, web-based
business?
Enterprise use of
digital era
technology?
Customer
intimacy?
Multi-channel?

24. Digital Business
“Digital business is the
creation of new business
designs by blurring the
digital and physical
worlds”

25. 25

26. 26

27. Algorithms Are Taking Over

28. Retired United States Air Force Colonel Gene Lee
“I was surprised at how aware and reactive it was. It seemed to
be aware of my intentions and reacting instantly to my changes
in flight and missile deployment. It knew how to defeat the shot
I was taking. It moved instantly between defensive and
offensive actions as needed.”

29. Running Gone Digital
“The fitness brands of the future will not just make physical
products, but will be embedded in the consumer journey in
ways that will help keep people motivated and maximize
their enjoyment of sport.
By putting together a digital fitness platform and world class
physical products, we can build a new kind of fitness brand”

30. 30

31. 31
• Better
personalization
across different
channels
• Better targeting
and marketing
execution
• Real-time
recommendations

33. Transform to BI, interfaces

36. 36
Falls account for half of all hospital
admissions over 65: $54.9 billion of
expenses by 2020

37. These are all BigData
• Bigdata is the latest buzzword in the IT industry.
Apache’s hadoop is a leading big data platform used
by IT giants yahoo, facebook & google.
• Sap hana is in memory data processing device to deal
with big data in with ibm computers.
• 'Big data' is also a data but with a huge size.
• The challenges involved in its storage and processing.
• Such a data is so large and complex that none of the
traditional data management tools are able to store
it or process it efficiently.
• BIG DATA is everywhere

39. The importance of BIG DATA
• BIG Data can transform the product/ decisions/ CRM of a business
• 3 Industrial Revolution, the third one is IT
• First industrialization
• Second was electricity
• Third is IT
• 1.7 Billion Network Users
• 25 Billion Web Enabled Device
• number of social media users worldwide In 2018, it is
estimated that there will be around 2.67 billion social
media users around the globe, up from 2.34 billion in
2016.
• During past 18 hours the data that has been created is more than
the history of human being until 2017
• There will be more MOBILE device than people in 2020.

40. Strategic

41. New York Stock Exchange
• The New York Stock Exchange generates about one
terabyte of new trade data per day.

42. Social Media BIG
DATA

43. Social Media
• Statistic shows that 500+terabytes of new data gets
ingested into the databases of social media
site Facebook, every day.
• This data is mainly generated in terms of photo and
video uploads, message exchanges, putting comments
etc.

45. Number of social media users
worldwide from 2010 to 2020 (in
billions)

46. Jet engine
• Single Jet engine can generate 10+terabytes of
data in 30 minutes of a flight time.
• With many thousand flights per day, generation
of data reaches up to many Petabytes.

48. What can we do with BIG DATA ?

49. Connected Cars

50. What can we do with BIG DATA ?

51. It makes
Live
Business

52. What can we do with BIG DATA ?

53. Customer 365
What can we do with BIG DATA ?

54. Sensors Enable New Processes
and Applications
Weissbeerger Beverage Analytics

55. Transport For London

56. Networked Crane Safety

57. What can we do with BIG DATA?
Predictive Maintenance

60. SAP Maintenance
Maintenance
Last checked: 28/9/09
Relative performance: +10%
More details
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61. Filter by: Maintenance History
Tower Pipe 3
Last Maintenance: 2 Weeks
E 0.1km
Photo by Thomas Hawk, Flickr
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62. 10km
De NHM kijker
Eerste Romeinse
nederzetting: “Oppidum
Batavorum”
Jaartal: 12 voor Chr.
Afstand: 300 meter
0.3

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

64. 10km
De NHM kijker
Eerste Romeinse
nederzetting: “Oppidum
Batavorum”
Jaartal: 12 voor Chr.
Afstand: 300 meter
0.3

65. 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

66. 66
What can we do with BIG
DATA?Predictive Maintenance

67. How does the Big data from your generated comments can interpret
?Just like in business .
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68. Text Analytics
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69. Customer feedback

70. Stepping Up…
Chief Innovation Officers
Chief Infrastructure Officers

71. WHAT IF IT DID MORE THAN
JUST “KEEP
THE LIGHTS ON”?
WHAT IF IT WAS
THE CATALYST FOR
INNOVATION?
WHAT IF THE IT DEPARTMENT
LED THE TRANSITION TO
DIGITAL TRANSFORMATION?

72. Technology Priorities for 2016 and
beyond
Rank Technology Trend
1 BI/Analytics
2 Cloud
3 Mobile
4 Digitalization / Digital Marketing
5 Infrastructure & Data Center
6 ERP
7 Security
8 Industry-Specific Applications
9 Customer Relationships
10 Networking, Voice, and Data Comms
Gartner: 2016
Nine out of
eleven years
2006-2016
ANALYTICS
#1

73. Analytics
Takes Over
The World…

74. Live
Business
Live Business

75. Digital Transformation with
Analytics
New
Customer
Experiences
New
Value Creation
Models
New
Business
Models

76. We Need Both of These…

77. Categories Of 'Big Data'
Big data' could be found in three forms:
• Structured
• Unstructured
•Semi-structured

78. Structured
• Any data that can be stored, accessed and processed in
the form of fixed format is termed as a 'structured' data.
• Data stored in a relational database management system
is one example of a 'structured' data. What can we do
with it ?

79. Un-structured Data
• Any data with unknown form or the structure is
classified as unstructured data.
• Huge in size and challenging to work with
• a heterogeneous data source containing a combination
of simple text files, images, videos etc.
• Example : Output returned by 'Google Search‘
• What can we do with it ?

80. Semi-structured
• Semi-structured data can contain both the forms
of data.
• We can see semi-structured data as a structured in
form but it is actually not defined with e.g. a table
definition in relational DBMS.
• Example of semi-structured data is a data
represented in XML file.
• What can we do with it ?
• Personal data stored in a XML file-
<rec><name>John Smith </name><sex>Male</sex><age>35</age></rec>
<rec><name>Jane Brown </name><sex>Female</sex><age>41</age></rec>
<rec><name>Mary White</name><sex> Female</sex><age>29</age></rec>

81. Characteristics Of 'Big Data'
• Volume – The name 'Big Data' itself is related to a size
which is enormous.
• Variety – The next aspect of 'Big Data' is its Variety which
refers to heterogeneous sources and the nature of data,
both structured and unstructured.
• Velocity – refers to the speed of generation of data.
• Variability – This refers to the inconsistency which can
be shown by the data at times, process of being able to
handle and manage the data effectively.

82. Benefits of Big Data Processing
• Businesses can utilize outside
intelligence while taking decisions
•Improved customer service
•Early identification of risk to the
product/services, if any
•Better operational efficiency

83. Simple
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84. 'Big Data' technologies
• 'Big Data' technologies can be used for
creating staging area or landing zone for new data
before identifying what data should be moved to
the data warehouse.
• Cleaning data before it goes to Datawarehouses
• Use of a sandbox

85. Sandboxing / Data Extensions

86. The challenge
•Big Data Ingestion
•Big Data Transformation
•Big Data Analytics
•Big Data Solutions

87. BIG DATA RUNS

88. SAP Social Network Analyzer Prototype
http://sna-demo.ondemand.com

89. Five Next Gen BI Technologies
• Search and Exploration
• Acceleration
• Mobile
• Networked
• Self Service

90. Bridging the Gap
Corporate
Local

91. Next Generation On-Demand BI
More than 230,000 subscribers and growing

92. Information
Strategy
Management
Finance
Business Process
Best
practice
Collaboration
Knowledge
Management
Implement New Strategy Integrate AcquisitionLaunch Product
Intelligence = Information + PEOPLE
BIG DATA
BI
DATA Process
Mining

93. “Modern BI”
BIG DATA Self-service
data preparation
Structured/Unstructured
Internal/External
Batch/Streaming
Integration, blending
Cleansing, augmentation
Agile modeling
BI DB
Columnar
In-memory
Self-service
data analysis
Data discovery
Visual exploration
Dashboards/storytelling
Agile Iteration
Optional
Data warehouse
Semantic layers
OLAP Cubes

94. An
Example
“Target
Big Data
Architect
ure”
ETL
Ingestion
Extracting data
from source
systems and
making it
available for up-
stream
consumption
Sources
Existing and new data sets
from external and internal
sources
Big Data Platform (Data Lake)
Core technology set enabling very high volume
computation and storage for raw data and ready to use
processed data.
Relational
Traditional RDBMS
Performance Clusters
Fit-for-purpose clusters targeting real-time and near-real
time use cases providing faster storage and access to
data
Real-time Streaming
Real-time ingestion of data, enabling event processing and visualization
Data
Services &
Interface
Layers
ETL and APIs that
allow data to be
extracted from
the data
platforms and be
further analyzed ,
visualized or
exported
Exploratory
Analytics
New and existing applications
to support data discovery and
advanced analytics
Application
Consumption
Dashboards, reporting and
web services to expose the
underlying data to external
users
Data Management and Governance
Centralized user management for proper authentication and authorization, meta data management.
InMemory/Appliance
EDW
Trad sources
Customer
Mobile value chain
Fixed value chain
Network probes
Machine Logs
Interaction logs
Social media
Others
Event stream Processing
APIs
Connectors
ODBC
Informatica
BusinessObjects
Customer facing
services
SAS
Others
SAS Visual Analytics
SAS EG/EM
New Analytical Tools
Existing New
Ready to use
(Hadoop)
Raw data
(Hadoop)
Black box
Semantic
Layer
Splunk
Splunk

95. Sustainability Performance Management

96. Suite
Applications
S/4HANA
Icon
Analytics
C4A
BOBJ
ExtensionsApplications
IoT
HANA Cloud Platform
(Micro-) Services
IoT
Platform
Identity Management
Business Network
CEC
Platform
HANA
any DB Hadoop
Vora
DistributedComputing
Platform
SAP Platform for Digital Transformation

97. The Journey so far..
HANA & Hadoop Integration to use
BIG DATA
• In memory Data
processing ( SAP HANA)
• HADOOP Platform ,
HADOOP is a framework
used to develop data
processing applications
which are executed in a
distributed computing
environment.

98. BIG Data tiering

99. Advanced Analytics

100. Big Data
Discovery =
Big Data
Data Discovery
Data Science
Gartner Strategic Planning Assumption:
By 2017, Big Data Discovery Will Evolve Into a Distinct Market Category

101. Big Data Discovery
• Volume, velocity, or
variety of data
• Potential business impact
• Difficult to implement
• Potentially expensive
• Lack of skills available
• Ease of use
• Agility and flexibility
• Time-to-results
• Installed user base
• Complexity of analysis
• Potential impact
• Range of tools
• Smart algorithms
• Difficult to implement
• Slow and complex
• Narrow focus of analysis
• Limited depth of
information exploration
• Low complexity of
analysis
BIG
DATA
DATA
SCIENCE
DATA
DISCOVERY

102. Big Data Discovery
• Simpler to use than data science
• Accessible to a wider range of users
• Broad range of data manipulation features
• Able to handle new types of data sources
• With adequate performance for big data
BIG DATA
DISCOVERY

103. Potential impact
per user
Potential user
base
The Rise of the Citizen Data Scientist?
Business
analyst
Data scientist
Citizen data
scientist

104. SAP’s Opportunity
Big Data
Discovery
SAP HANA
SAP IQ
Vora / Spark /
Hadoop
SAP Predictive
Analytics 3.0
SAP Lumira

105. Not Just a Data Store – A Platform
Example : Hadoop
• Far more than a batch-driven data store
• Many still have an out of date view
• ”Data at Rest and Data in Motion”
• But still not for “transactions” any time soon
• Still maturing, still a lot of work, but has proved enterprise
value
• In particular, overcame biggest security & auditing concerns – Kerberos
integration, encryption, tokenization, Apache Ranger…
• Low capital costs to try things out (but don’t underestimate time /
training / expertise needed)
• Considered the heart of “digital transformation” in some
large organizations…
• ...At least by the team implementing Hadoop! (but there’s typically a
large ”traditional IT” modernization effort going on at the same time)

106. Result of All This: Data Complexity For
The Foreseeable Future
Data
Warehouse
Hybrid
Transaction/An
alytical
Processing
Hadoop,
MongoDB,
Spark, etc Personal
Data / BI
Where does data arrive?
When does it need to move?
Where does modeling happen?
What can users do themselves?
What governance is required?
Big Data Architectures got complicated
What we would like — consistent, seamless solution
Data
Feeds

108. Five Next Gen BI Technologies
• Search and Exploration
• Acceleration
• Mobile
• Networked
• Self Service

109. New Devices, New Opportunities

110. Applications for Data Stewards

111. 115
Design
Thinking
Understand
Ideate
Prototype
Test
Build
Deliver

112. BIG DATA+ Business Intelligence

113. Wrap-up

114. 7 Key Points to Take Home
• Business Intelligence and Analytics over BIG DATA is more
strategic than ever
• Analytics over BIG DATA now creates processes instead of just
being generated by them
• New trends in analytics over BIG DATA means new
approaches are required
• Companies should invest in more self-service BIG DATA
analytics for business users
• Companies should invest in more flexible information
architectures
• Start preparing now for the artificial intelligence future

115. Thank You!
Professor Lili Saghafi
Proflilisaghafi@gmail.com @Lili_PLS

116. References
• Https://www.Sap.Com/canada/index.Html
• SAP lumira
• Https://powerbi.Microsoft.Com/en-us/
• Microsoft power BI
• SAP crystal dashboard design
• Https://www.Sap.Com/products/crystal-dashboard-design.Html
• Business value of simplified IT SAP HANA
• Digital business & business analytics, Timo Elliot
http://timoelliott.Com/blog/
• https://sites.google.com/site/professorlilisaghafi/home
• https://quantumexperience.ng.bluemix.net/qx/community
• https://quantumcomputingjournal.wordpress.com/