the truth about hana. sap keynote speaker
DESCRIPTION
Presentation of the Puur C seminar about Hana, organized by CTAC on 24/06/14TRANSCRIPT
The Truth about HANAWhat’s really in it for your business
2
Keynote
The new SAP User Experience
Paradigm enabled by HANA
Effective Data Analysis using HANA
Live
HANA Optimized Processes for
Finance and Retail
The Road(s) to HANA
Dr. Juergen HagedornVP Hana, SAP AG Walldorf
Use this title slide only with an image
SAP HANA – How a Ground-breaking Technology drives Business Innovation
Juergen Hagedorn, HANA Product & Development, June 2014
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 4
CPU
Modern Hardware and Software ArchitectureProvided Opportunities to Re-Design DBMS to Reduce Latency
STORAGE
MEMORY
CompressionPartitioningOLTP+OLAP
in column StoreInset Only on Delta
No Aggregate tables (Dynamic Aggregation)
Solid State Flash HDD
64bit address space 1 TB in current servers
Dramatic decline in price/performance
L3Cache
L3Cache
L3Cache
L3Cache
L3Cache
L3Cache
L3Cache
L3Cache
Multi-Core Architecture8 CPU x 10 Cores per blade
Massive parallel scaling with many blades
Logging and Backup
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 5
SAP HANA Innovation OverviewArchitecture Illustrations & HANA Offerings from SAP & Ecosystem
BusinessSuite
on HANA
Business Oneon HANA
Side-by-side scenarios
HANA RDS
HANA NewApps
HANA DB
CR
M
SC
M
SR
M
PLM
ER
P
VD
L
SAPBusiness Suite
BW
Apps
HANA DB
Apps
CRM customer Segmentation
COPA
Finance & Controlling
BW powered by HANA
Business Planning & Consolidation on HANA
Business Suite on HANA
HANA New Analytics
SAP HANA DB
Custom Data Mart/Any App
BOBJ BI
Visual Intelligence
Text & Predictive Analysis
Sales Analysis for Retail
Liquidity Risk Management
ERP Operational Reporting
Social Sentiment Intellignence
Sales Pipeline Analysis
Business One on HANA
SAP Business One Analytics on HANA
HANA New Analytics
Business Intelligence on demand
Sales & Operations Planning
Supplier InfoNet
Developer Access via Amazon Web Services (AWS)
SAP HANA One
SAP HANA Cloud
Smart Meter Analytics
Precision Retailing
Cash Forecasting
Standalone app from partners
AND MUCH MORE FROM SAP, ISVs and Start-ups
HA
NA
OF
FE
RIN
GS
HANA DB
SAPBusiness One
HANAAccelerators
BW onHANA
HANAPlatform(Datamart)
HANAApps for Suite
(incl. Reporting & Analytics)
Cloudon HANA
Any DB
HANA DB
BWSAP
BusinessSuite
Any DB
Client
SAP Business
Suite
HANA DB
Any DB
HANA DB
Client
OD/SF Solutions
Any DB HANA DB
SAP Business
Suite
& Any App
Data Mart
SAP BOBJ BI, VI
AR
CH
ITE
CT
UR
AL
IL
LU
ST
RA
TIO
NS
Any DB
HANA DB
AppsSAP Business
Suite
Integrated scenariosNew
Frontiers
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 6
Some “Big Data” Numbers
The Twitter phenomenon
■ ~140 million active users
■ ~500 million Tweets a day, more than 1 billion every 3 days
■ ~130GB / day (280Byte/Tweet)
The Facebook Explosion
■ ~1B active million users, ~400 million log in every day
■ ~700 Billion minutes a month are spent on Facebook
■ ~35 million users update their status every day, ~60 million status updates per day
NASDAQ, largest US electronic stock market
■ ~14,000 transactions per second
■ ~7.5 million quote updates, ~4.2 million trade reports per day
■ ~2.6 million orders / day, ~2.3 billion shares per day
Customer Data
Automobiles
Machine Data
Smart Meter
40.000Exabytes
2020
Point of Sale
Mobile
Structured Data
Click Stream
Social Network
Location-based Data
Text Data
IMHO, it’s great!
RFID
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 7
Cobbling Disparate Tools together is NOT the Answer!
7
Integrated Platform
Disparate Tools
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 8
Supports any Device
Any AppsAny App Server
SAP Business Suite and BW ABAP App Server
JSONR Open ConnectivityMDXSQL
Other AppsLocationsReal-timeHADOOPMachineUnstructuredTransaction
SAP HANA PlatformSQL, SQLScript, JavaScript
Integration Services
Spatial
Business Function Library
Search Text Mining
Predictive Analysis Library
DatabaseServices
Stored Procedure & Data Models
Planning Engine Rules Engine
Application & UI Services
SAP HANA Platform – More than just a database
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.
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 9
Data Federation
Transactions + Analytics
Teradata
HadoopSQL Server
Oracle
IQ
SAP HANAVirtual TablesHANA Tables Remote object
catalog
Remote Object(Table/View)
SAP HANA
DB catalog
Column Tables
Row Tables
Virtual Table
Remote Data Source
Key Element: “Virtual Table”Ad-hoc access to remote data sources
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 10
In-Database Predictive Analytics with R integration
In-Memory + In-Database predictive analytics with SAP HANA
In-memory processing engine
SQL engine
Text engine
Calculation engine
Script-node R-node
R engine
Application function modeler
Spatial engine
SAP HANA Studio
C4.5decision tree
Weighted score tables
Regression
ABC classification
KNN classification
K-means
Associate analysis:
market basket
Predictive analysis libraries (PAL)
Accelerated predictive analysis and scoring with native in-database algorithms delivered ready to use
Graphical modeling
SAP HANA studio – Application function modeler for app developers; prebuilt commonly used business and predictive algorithms to facilitate faster and easier development
R integration
Execution of R scripts via high- performing parallelized connection; R scripts embedded as part of overall query plan
11© 2014 SAP AG or an SAP affiliate company. All rights reserved.
USER
MI
New Analytical Viewpoints
Guided Analytics
HarmonizedCategories
HarmonizedTime
Extrapolation
D
E
A
B
C
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 12Source: SAP AG
Margin?Changes & Reasons?
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 13
Business Questions
• Which markets work with prices and trade terms more than other ones?
• Which trade terms are focused on?
• Is there a link to success?
Assumptions
• Pricing levers are known (List Prices, Trade Terms, etc.)
• Patterns for successful pricing strategies can be found among markets
• Those patterns can be transferred to other markets
Expected benefits
• Margin optimization through target oriented pricing strategy
Trade Term Elasticity
Marketing Price
List Price
Net Price
Target
Margin
Trade Terms
List PriceDistribution
Net PriceDistribution
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 14
Sensor Data Apps – Pirelli Cyber Fleet – Platform
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 15
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 16
Connected Cars Sample Scenario
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 17
Architecture Overview
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 18
Bill ofMaterial
CO-PC Standard Costs
COGS & Margin Analysis
Product Cost Forecast and Simulation:A driver-based approach powered by SAP HANA
Sales Volumes, Deductions, …
Purchase Prices & SpendDrivers: Commodities, FX, Inflation, …
Key Features:
• P&L and Margin forecast based on Cost Drivers and Planned Sales Volumes
• Procurement Spend forecast based onPlanned Sales Volumes
• Complete Forecast andAd-hoc Simulationsfor entire Company
• SAP Hana ensures Online Reaction Times
19© 2014 SAP AG or an SAP affiliate company. All rights reserved.
CANCERPATIENTSRECEIVE TREATMENT OPTIMIZEDTO THEIR DNA
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 20
Health Care Partners
21© 2014 SAP AG or an SAP affiliate company. All rights reserved.
© 2014 SAP AG or an SAP affiliate company. All rights reserved.
Thank you
Contact information:
Juergen HagedornSAP AG