The document presents SAP HANA as a powerful analytics platform for real-time data processing and business intelligence. It outlines the platform's capabilities, including in-memory storage, advanced analytics, and integration with various data sources, while emphasizing agility and speed in business operations. Additionally, it addresses the challenges faced in traditional data management and the transformative potential of adopting SAP HANA for enhanced decision-making and operational efficiency.

1. HANA as an Analytics Platform
Stefan Lotz
SAP Senior Pre-Sales, Platform Solution Group

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C’est quoi HANA?
SAP HANA PLATFORM
ON-PREMISE | CLOUD | HYBRID
Web Server JavaScript
Fiori UX Graphic
Modeler
Data Virtualization ELT &
Replication
Application Services Integration Services
Columnar
OLTP+OLAP
Multi-
Core/Paralleliza
tion
Advanced
Compression
Multi-
tenancy
Multi-Tier
Storage
Spatial Graph Predictive Search
Text
Analytics
Planning Data
Enrichment
Series
Data
Function
Libraries
ALM
Processing Services
Database Services
Hadoop
Integration
Streaming
(CEP)
Application Lifecycle
Management
High Availability /
Disaster Recovery
Open
Standards
Data
Modeling
Remote Data
Sync

3. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 3
What are the 5 V’s of Big Data? (examen )
Volume
Velocity
Variety
Value
Veracity

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Disruptive Forces are Changing the Speed of Business
Faster business requires business agility
MORE DATA
DATA IS GETTING BIG
SPEED OF BUSINESS
HAS RADICALLY
INCREASED
LESS TIME
The Economist
Tax in Brazil: Nothing is Certain
26
268 hours
tax payments a year
Brazilian companies need to make
Brazilian ranked most time-
consuming tax regime in the
world.
“ “requiring of prep work

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What if you could…
Use data analytics to increase agility of your business
Financial
performance &
risk control
Business
Optimization
Customer
Service &
Engagement
Analytics
Market Share
SKILLS
BUSINESS NEEDS
POWERFUL IT
Big Data
Digitization
Internet of Things
DATA
Social
Data Scientists
Business Analysts
Age of Customer
Data-driven culture
Digital Disruptors
In-memory | Cloud | Mobile | Cheap Processing Power

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Reality of today’s analytics landscape
Rear-view mirror, fragmented, slow, complex and expensive
OLTP
Real-time posting
into transactional
system
Aggregation
Batch transfer to
Data Warehouse
Reporting challenges
Large volumes
High impact
“Real-life”
business
transaction
Analysis &
insight
Actions
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Transactional
System
OLAP
Data Marts
Days*75 Minutes***24-hour cycle**
Discover Harvest Filter Integrate Augment Analyze Act
Limited flexibility due
to predefined data
structures
Long query run times
Loss of detail
Long wait times for
reports
Data Temperature
*Real-Time Data, BI, and Analytics: TDWI survey | ** Avg. Data Refresh Frequency | *** Avg. Response time based on Aberdeen Group, 2011

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Agile Insights…..Beyond the Warehouse
Real-time technologies making BI and analytics more actionable
Real-Time Agile Insights
No Aggregation / No Data Staging
“Real-life”
business
transaction
Analysis &
insight
Actions
Knowledge
influences Action
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Analytical
Opportunities
Discover Integrate, Cleanse
& Enrich
Analyze Distribute Embed Act
Real-time
loading into
SAP HANA
• Scan & Filter
• Predictive
Analysis
• Text Analysis
• Spatial
Processing
• Sentiment
Intelligence
• Graph
Processing
• Integrate into
business
processes
• Dashboard
• Alerts
• Reports
• Events
Data Temperature

8. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 8
SAP HANA-powered Agile BI & Advanced Analytics
A game changer for every industry and application area
Risk
Analysis
SocialOperations Maintenance
Fraud Mgmt &
Risk Analysis
Routing &
Optimization
APPLICATION AREAS
INDUSTRIES
Life SciencesTransportation &
logistics
Financial &
Insurance Services Telecommunications
Retail &
Consumer Products
SAP HANA
Customer
Churn
Supply
Chain
Situation
Intelligence
Operationalize Data
Pipeline
Capturing data as it is
created or updated
Make Agile BI Real
Bring simple, instant access to
business users
Run Deeper
Analytics
Perform advanced analytics to
uncover nonobvious insights or
predict future outcomes
Get Instant Insights
Perform fast, interactive
queries

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Operationalize Data Pipeline
Low latency data capture and cleansing
• Real-time replication and bulk data movement
with smart data integration
• Native data transformation, cleansing and
wrangling capabilities with smart data quality
• Federate multiple data stores as local virtual
tables using smart data access
• Capture, filter, analyze and act on streaming
data with smart data streaming
SAP Data
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Third Party Data
Native Real-time Data
Replication
SAPHANA
Native Transformations
& Cleansing
Streaming Data
Native Streaming
Processing
IBM DB2,
Netezza,
Oracle,
Teradata,
More
Columnar
In-memory
SAP HANA PLATFORM
Calculation
Engine
Virtual Tables
BI / Analytics / Apps
Stephen Burr
University of Kentucky
“
We’re no longer in the business of Data
Movement – now we’re in the business of
better decisions.
using information
“to make

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Get Instant Insights
Perform fast, interactive queries
• Industry-best scanning filtering because entire model
& data is in-memory
• Columnar storage enables high compression, self-
indexing and high-performance analytics
• MPP architecture enables processing of parallel
queries to efficiently scale out across server nodes
• Insert-only store prevents locking while running
queries during data ingestion
• Unified stack removes data silos and gridlocks
SAPHANA
SAP Data
1010100
1010110
1001110
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Third Party Data
Calculation
Engine
Column
Storage
SAP HANA PLATFORM
In-memory
MPP
Multi-core
Virtual Data
Model
Delta
store
No
Indexes
ACIDAcid-
compliant
Low latency data capture & cleansing
BI / Analytics / Apps
ROLAP
Engine
Streaming Data
Santiago José Reig Lamberti
Head of Business Intelligence B2B, TUI Travel PLC
“
Now that we’re running SAP HANA on Cisco
UCS, we have gone from analyzing millions
of records in hours, to the flexibility to
in seconds.
analyze hundreds of millions
“
of records

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Make Agile BI Real
Bring simple, instant access to business users
• On-the-fly-aggregation allows for self-service data modelling
• Flexible tables allows dynamic schema so there are no model
constraints
• Virtual data model simplifies modelling and eliminates need for
expensive tuning tasks like multiple indexes, aggregates and
materialized views
• Cloud-based offering allows for seamless on-demand capacity
• Open approach to access and connectivity with support for
JDBC/ODBC, SQL and MDX, and certified to work with all
best-of-breed BI both SAP and non-SAP
SAP Lumira/SAP
BI Portfolio
Certified
3rd Party BI
Vendors
SAPHANA
Low latency data capture & cleansing
SAP Data
1010100
1010110
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Third Party Data
Calculation
Engine
Columnar
In-memory
SAP HANA PLATFORM
On-the-fly-
aggregation
Flexible
table
Collapsed
stacks
SQL, MDX,
JDBC/ODBC
Streaming Data
Cloud-ready
Ron Grabyan
Manager of Data Warehousing Services, Southern California Edison
more than five times faster.
User self-service is a goal for SCE,
Reporting on the data warehouse has seen dramatic
improvements making it
Users will be able to get in and look at their data a lot faster.
“ “
and SAP HANA helps us to optimize user experience and alleviate
setup time.

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Virtual Data Model on SAP HANA
Plug-and-Play Access to Business Models and Business Logic
Information models
Data in HANA is managed with tables and/or
information models
Tables
• Columnar storage
• Storage of detailed operational “raw” data
Information models
• Logical views of the data that define useful business
models and logic on top of tables
– Analytic views
– Calculation views
• Created by the SAP HANA Studio, a database
management and modeling tool for SAP HANA
• Information models do not store data
SAP HANA
Tables
Dashboarding
& Apps
Design
Studio
Self-Service
Lumira,
Analysis,
Reporting
Crystal
Reports,
Web
Intelligence
Direct Access

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Limit Shadow IT
Empower your business analyst without taking away their BI & Data Mart agility
HANA Features

ANSI SQL-based

Native EIM

Simple

In-Memory Columnar

Native EIM/Virtual Data
Model

Flexible schema

Virtual Data Model

On-the-fly-aggregates
*TDWI Report: Real-Time Data, BI, and Analytics by Philip Russom, David Stodder and Fern Halper
0% 10% 20% 30% 40% 50%
Don't have all the data you need
Don't have the right data model,
relationships, attributes,…
Are too restrictive in their data
models
Don't allow you to clean,
integrate, or model the data
Take too long to get results
Are too complex, complicated,
cumbersome to use
Don't have good data quality
Are not intuitive
“Why do you use BI Applications, some or all of the time?*”
Reasons business users resort to homegrown BI Apps

14. © 2015 SAP SE or an SAP affiliate company. All rights reserved. 15
Run Deeper Analytics
Use advanced analytics to uncover nonobvious insights or predict future outcomes
• Reduce data-to-compute distance by leveraging in-
database analytics with native algorithms & functions
• Multi-engine support for
predictive, text, spatial & graph processing
• Support for heterogeneous data types structured &
unstructured data
• Big data-ready
• Hadoop integration
• Support for MapReduce via Hive and Spark integration
In-database
Columnar
In-memory
SAP HANA PLATFORM
SAPHANA
Low latency data
capture & cleansing
Predictive
Engine
Spatial
Engine
Text Analysis
Engine
Graph
Engine
Time
Series
Hadoop
Integration
SAP Data/Non-SAP Data
Predictive Geo-spatial Graph Text Analysis
We have built a custom application on SAP HANA that helps us identify
high-risk gas pipes in close proximity to residential buildings.
Pieter Den Hamer
Big Data BI Strategy Manager, Alliander
“
In the past, this analysis took three & a half hours
using our legacy database. Now with
allowing us to perform ad hoc asset management, reduce
potential outages and avoid catastrophic failures.
spatial processing in SAP HANA, we can answer the
same question in
two to three seconds,
“

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Operational Reporting
5 Types of Analytic Use-cases
HANA accelerates every use-case
OLTP
Operational
Data Store
Fast data movement
Fast query response time
Query & Analysis
Fast data movement
Fast query response time
Fast aggregates & View refresh
User & Data Scalability
OLTP
Warehouse
or Data Mart
Multi-dimensional OLAP
Fast, On-the-fly cube builds
Fast query & aggregate calculation
Fast Scenario Modeling (Updates)
User & data scalability
OLTP OLAP
OLTP
Planning & Forecasting
Planning
System
Fast plan re-computation
Fast forecasting (Updates)
Fast aggregations & reporting
User & data scalability
Unstructured Information
Discovery
Fast search index re-computation
Fast query & guided navigation
Warehouse
Unstructured
Analytics

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HANA as an Analytics Platform
The perfect marriage in an end-to-end stack
Analytics
Platform/Use
Cases
Enterprise
BI
Advanced
Visualization
High-
Performance
Data Mart
Advanced
Analytics
Agile BI
Platform
Optimized BI access
to business models
and business logic
in SAP HANA
Supported
for all use
cases
Many customer
successes in all
industries and
lines of business

17. © 2015 SAP SE or an SAP affiliate company. All rights reserved.
Merci!