The document discusses the potential of in-memory databases and real-time analytics using SAP's HANA platform. It provides examples of how HANA has allowed companies like Yodobashi and Mitsui Knowledge Industry to gain real-time insights from massive amounts of data and enable more personalized and faster decisions. The document also outlines how HANA aims to converge database, data processing, and application capabilities to power next-generation applications.

1. Big Data in Real-Time
Uğur CANDAN
SAP Turkey - Chief Operating Officer
@ugurcandan
ugurcandan.net

2. Youtube
in-memory database
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22. Technology today requires tradeoff
A breakthrough in today’s information processing architecture is needed
DEEP
Complex & interactive questions
on granular data
OR
HIGH SPEED
Fast response-time,
interactivity
DEEP
Complex & interactive questions
on granular data
HIGH SPEED
BROAD
Fast response-time,
interactivity
Big data,
many data types
SIMPLE
No data preparation,
no pre-aggregates,
no tuning
© 2011 SAP AG. All rights reserved.
REAL -TIME
Recent data, preferably realtime
SIMPLE
No data preparation,
no pre-aggregates,
no tuning
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23. SAP HANA Platform – More than just a database
Any Apps
SAP Business Suite
Any App Server
Supports
any Device
and BW ABAP App Server
SQL
MDX
R
JSON
Open Connectivity
SAP HANA Platform
SQL, SQLScript, JavaScript
Spatial
Search
Text Mining
Stored Procedure
& Data Models
Application & UI
Services
Business Function
Library
Predictive
Analysis Library
Database
Services
Planning Engine
Rules Engine
Integration Services
Transaction
Unstructured
Machine
HADOOP
Real-time
Locations
Other Apps
SAP HANA Platform Converges Database, Data Processing and Application Platform
Capabilities & Provides Libraries for Predictive, Planning, Text, Spatial, and Business
Analytics to enable business to operate in real-time.
© 2011 SAP AG. All rights reserved.
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24. Dünyanın en büyük in-memory veritabanı sistemi – Santa Clara, CA
250 HANA sunucusu | 250TB Ana Bellek | 10,000 x86 Core
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25. Breakthrough solutions from startups & ISVs
A single platform powering next generation of applications
nexvisionix
DRIVING ADOPTION
RECENT PROJECTS

Platform to imagine new generation of applications

Industry solutions - Healthcare, Capital Markets

Simple consumption model – lowering barriers to entry

Consumer and enterprise applications

Rapid commercialization of innovation

www.startups.saphana.com (700+ Startups & ISVs)
© 2011 SAP AG. All rights reserved.
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26. Predictive Analytics & Machine Learning
Transforming the Future with Insight Today
Hadoop/ Sybase IQ,
Sybase ASE, Teradata
SAP HANA
KNN
classification
Regression
Main Memory
C4.5
decision tree
K-means
Virtual Tables
SQL Script
Optimized Query Plan
Spatial, Machine,
Text Analysis
Real-time data
PAL
R-scripts
ABC
classification
Weighted score
tables
Associate
analysis:
market basket
R-Engine
Spatial Data
Unstructured
HANA Studio/AFM,
Apps & Tools
Accelerate predictive analysis and
scoring with in-database algorithms
delivered out-of-the-box.
Adapt the models frequently
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Execute R commands as part of
overall query plan by transferring
intermediate DB tables directly to R
as vector-oriented data structures
Predictive analytics across multiple
data types and sources.
(e.g.: Unstructured Text, Geospatial,
Hadoop)
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27. Innovation Previously Infeasible
Predict and analyzes game player behavior in real-time
Real-time insights, analysis,
and consumer engagement
for increased revenue and
decreased churn
© 2011 SAP AG. All rights reserved.
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28. Simplicity Previously Unachievable
eBay Early Signal Detection System powered by Predictive Analytics
Automated signal
detection system to
proactively respond to
real-time market
dynamics
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29. Product: Agile Datamart
Yodobashi - POS Data Analizi
Business Challenges
250 million POS
 Lack of real-time insights into POS data make it difficult to create effective,
tailored sales promotions and marketing campaigns
sales order line items
 Need shorter response time for customer segmentation to plan sales
campaigns
10-12 minute
Technical Challenges
sales campaign
planning (not
possible before)
 Inability to process big data (billions) POS records quickly because of high
latency and static reporting
 Shop floor staff not able to access relevant information on-the-fly, with iPad
Benefits
100,000x faster
sales analysis – from
3 days to 2-3
seconds
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 Real-time insights into POS data improve customer satisfaction and
merchandising
 Dynamic personalized offerings while customer is at store or on web site
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30. 12,000 Staff with
3,200 pure scientist,
650,000 patients/year,
1,4 B€ revenue
500,000 data
points from each
cancer patient.
Instant patient data
analysis during
treatment

31. Mitsui Knowledge Industry
Healthcare industry – Cancer cell genomic analysis
408,000x faster
than traditional diskbased systems in
technical PoC
216x faster DNA
analysis results from 2,5 days to 20
minutes
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32. Thank you