Intro to next step in Technology, Big Data. Basic understanding plus common jargon. How they integrate and makes sense for Business enablement.

1. ASUG/SAP SERIES – Big Data/Hadoop/HANA
Why Big Data ?
Why it can fit into your Business and Technology Roadmap
What it can do to Enable your Business!
John Choate – PMMS SIG Chair
Bill Klinke – PMMS Program Chair
David Burdett – Strategic Technology Advisor, SAP

2. The New and Ever Changing Landscape
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3. Open Source Big Data – CONFUSED????
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4. The 5 Part Series
 Webinar 1: Why Big Data matters, how it can fit into your Business and
Technology Roadmap, and how it can enable your business!
 Webinar 2: How Big Data technologies provide Solutions for Big Data
problems
 Webinar 3: Using Hadoop in an SAP Landscape with HANA
 Webinar 4: Leveraging Hadoop with SAP HANA smart data access
 Webinar 5: Using SAP Data Services with Hadoop and SAP HANA
Resources …
Webinar Registration
1. Go to www.saphana.com
2. Search “ASUG Big Data Webinar”
3. Registration links in blog …
Big Data, Hadoop and Hana – How they Integrate and How they Enable your Business!
Info on SAP and Big Data – go to www.sapbigdata.com
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5. BIG DATA DEFINED
UNDERSTANDING BIG DATA
BIG DATA JARGON
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6. Multiple Definitions of Big Data*
 The Original Big Data – Big Data as the three Vs: Volume, Velocity, and
Variety
 Big Data as Technology – Fast rise of open source technologies such as
Hadoop and other NoSQL ways of storing and manipulating data
 Big Data as Data Distinctions – Interactions are data collected from people,
e.g. web page clicks; Observations are data collected automatically
 Big Data as Signals – In the ‘new world,’ companies can use new signal data
to anticipate what’s going to happen in “Real Time”, and intervene
 Big Data as Opportunity – Explore new opportunities for Business via
Technology enablers
 Big Data as Metaphor – Creating the planet’s nervous system. Read the The
Human Face of Big Data by Rick Smolan and you will understand
 Big Data as New Term for Old Stuff – BI or analytics in the past have been
rebranded in a leap to jump onto the big data bandwagon
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* http://timoelliott.com/blog/2013/07/7-definitions-of-big-data-you-should-know-about.html

7. Big Data Simplified
Definition
• “Big data” is high-volume, -
velocity and -variety
information assets that
demand cost-effective,
innovative forms of
information processing for
enhanced insight and
decision making
Gartner
Three Key Parts
• Part One: 3V’s – Volume,
Velocity, Variety
• Part Two: Cost-Effective,
Innovative Forms of
Information Processing
• Part Three: Enhanced
insight for “Real Time”
decision making
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8. The 7 Key Drivers Behind the Big Data Movement? *
Business
1. Opportunity to enable innovative new business models
2. Potential for new insights that drive competitive advantage
Technical
1. Data collected and stored continues to grow exponentially
2. Data is increasingly everywhere and in many formats
3. Traditional solutions are failing under new requirements
Financial
1. Cost of data systems, as a percentage of IT spend, continues
to grow
2. Cost advantages of commodity hardware & open source
software
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* http://hortonworks.com/blog/7-key-drivers-for-the-big-data-market/

9. Todays Key Challenges in Big Data
Information Strategy
1. Which investments will deliver most business value and ROI?
2. Governance – New expectations for data quality and management
3. Talent – How will you assemble the right teams and align skills?
Data Analytics
1. Data Capture & Retention – What data should be kept and why
2. Behavioral Analytics – Understanding and leveraging customer behavior
3. Predictive Analytics – Using new data types (sentiment, clickstream,
video, image and text) to predict future events
Enterprise Information Management
1. User expectations – Making “Big Data” accessible for the end user in
“real-time”
2. Costs – How to provide access to big data in a rapid and cost-effective
way to support better decision-making?
3. Tools – Have you identified the processes, tools and technologies you
need to support big data in your enterprise?
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10. 10
BIG DATA DEFINED
UNDERSTANDING BIG DATA
BIG DATA JARGON

11. How did we get here?
1990 20152000 2005 2010
DATABASE
(CIRCA 1980)
ANALYTICS
(CIRCA 1980)
PREDICTIVE ANALYTICS
(CIRCA 1980)
SEMANTIC ANALYTICS
(CIRCA 1980)
REAL TIME
1,000,000+
SOLD
WWW
3,000,000
people had access to internet
worldwide
B2B / B2C
MOBILE
More people have mobile
phones than electricity or safe
drinking water
Facebook: 1 billion users; 600 mobile users; more than
42 million pages and 9 million apps
Youtube: 4 billion views per day
Google+: 400 million registered users
Skype: 250 million monthly connected users
SOCIAL
BIG DATA
PERSONAL COMPUTER
AND CLIENT SERVER
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2013

12. How big is Big Data?
1.8
IN 2011, THE AMOUNT
OF DATA SURPASSED
ZETTABYTES
90% OF THE DATA IN THE WORLD TODAY
has been created in the last two years alone!
Today we measure available data in
zettabytes (1 trillion gigabytes)
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Eight 32GB iPads per person alive in the world

13. Social Media Growth 2013*
Mobile phones increased 60.3% to 818.4m in last two years
Facebook has 665m daily active users
Twitter has 228m monthly active users – 44% growth
YouTube hours watched – doubled to 6B hours watched
Google+ has 395m monthly active users – grew 33%
LinkedIn has 200m users
* http://growingsocialmedia.com/social-media-statistics-and-facts-of-2013-infographic/
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14. The Internet of Things
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Key contributor to growth of Big Data
• Sensor data
• RFID
• Telematics
• Devices connected to Internet expected to
grow 25 billion by 2015 & 50 billion by 2020

15. Many Types of Data
Mobile
CRM Data
Planning
Opportunities
Transactions
Customer
Sales Order
Things
Instant Messages
Demand
Inventory
Big Data
Sales Order
Things
MobileDemand
Big Data
CRM Data
CustomerPlanning
Transactions
Data comes in many different shapes and sizes
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16. SAP Data + Big Data = Better Value
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Mobile
CRM Data
Planning
Opportunities
Transactions
Customer
Sales Order
Things
Instant Messages
Demand
Inventory
Big Data
Sales
Order
Things
MobileDemand
Big Data
CRM Data
CustomerPlanning
Transactions
Non-SAP (Big) Data
SAP® Solutions
SAP HANA Data
warehouse/database
SAP Business Suite
Other
SAP
solutions
SAP Data
+
Combining SAP Data with “Big Data” provides
better business insights

17. Big Data and Competitive Advantage
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Utilize your data to gain a
competitive advantage!
Competitiveness of fact-finders vs. fumblers
Laggards Leaders
Fumblers
Fact-
finders
Fumblers
Fact-
finders
• Base decisions on the latest, granular
multi-structured data
• Make decisions on analytics rather than
intuition
• Frequently reassess forecasts and plans
• Utilize analytics to support a spectrum
of strategic, operational and tactical decision
making
• Rapidly evaluate alternative scenarios
Leading businesses can outpace the competition
because they can:
n=1,002
Source: IDC‘s SAP HANA Market Assessment, August 2011

18. BIG DATA DEFINED
UNDERSTANDING BIG DATA
BIG DATA JARGON
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19. Demystifying Big Data
Demystifying Big Data Jargon
 Big Data – the six V’s
 Structured vs. Unstructured Data
 SQL vs. NoSQL
 Hadoop
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20. Demystifying Big Data – The Six V’s
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21. Demystifying Big Data – Structured vs. Unstructured
Structured Data
• Well-defined content
• Examples
– Customer data
– Sales data
– Sensor data
• Easily understood
• Stored in an RDBMS
Unstructured Data
• Structure not obvious
• Examples:
– Images
– Video
– Natural language text
• Process data to understand
• RDBMS not a good fit
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Semi-Structured Data
Combination of both, e.g. email, social media feeds

22. Demystifying Big Data – SQL vs. NoSQL
SQL Databases
• Structured data only
• Scalable
• High Data Consistency
• Define structure first
• Systems of Record (SAP)
• Examples: DB2, Oracle
NoSQL Databases
• Structured or unstructured
• More scalable
• Eventual data consistency
• Define structure later
• Flexible Data Store
• Examples: Cassandra,
HBase, MongoDB
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23. Demystifying Big Data – Hadoop
• 10s to 1000s servers
• Open source SW
• Commodity HW
• Any type of data (NoSQL)
• Many ways to process
• Relatively slow
• Rapidly evolving
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Cluster of Commodity Servers
Hadoop
NameNode


10s to 1000s DataNode(s)
Hadoop
Computation Engines
Map-Reduce
Hive HBase Mahout
Pig Sqoop …
Data storage (Hadoop
Distributed File system)
Hadoop Software Architecture

24. The Challenge of Big Data
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Customer
IT Developer Analyst
LOB User
Data
Decision-Maker

25. Key Take Aways
 Big Data is having a big impact on business
 Leveraging Big Data provides new opportunities
 Better value from SAP Data + Big Data together
 Challenge is how to leverage Big Data for benefit
 Watch the rest of the series to find out more
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26. The 5 Part Series
 Webinar 1: Why Big Data matters, how it can fit into your Business and
Technology Roadmap, and how it can enable your business!
 Webinar 2: How Big Data technologies provide Solutions for Big Data
problems
 Webinar 3: Using Hadoop in an SAP Landscape with HANA
 Webinar 4: Leveraging Hadoop with SAP HANA smart data access
 Webinar 5: Using SAP Data Services with Hadoop and SAP HANA
Resources …
Webinar Registration
1. Go to www.saphana.com
2. Search “ASUG Big Data Webinar”
3. Registration links in blog …
Big Data, Hadoop and Hana – How they Integrate and How they Enable your Business!
Info on SAP and Big Data – go to www.sapbigdata.com
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27. Q & A
Questions ?
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28. THANK YOU FOR PARTICIPATING
For ongoing education on this area of focus,
visit ASUG.com
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