developing and deploying applications on the sap hana platform

Developing and Deploying Analytic

and Transactional Applications on the

SAP HANA Platform

Vitaliy @Sygyzmundovych Rudnytskiy, SAP

SAPinsider HANA2015 Nice, June 2015

@SAPDevs #SAPHANA

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 1

Let’s start with…

- … introduction :)

- Vitaliy Rudnytskiy

@Sygyzmundovych

- SAP’s Developer Relations team

- 12 years as a BI Technology Consultant

- SAP Mentor 2010-2014

- Self-proclaimed King of Data Geeks

- Based in Wrocław


Agenda

10 Introduction()

20 SELECT "Key_Features" FROM SAP.HANA

30 Top Reasons -> Choose("SAP HANA")

40 SELECT Flexible_Choices FROM SAP.HANA

50 Wrap_Up()


Custom Applications Are Key to Modern IT

Organizations seek to provide

innovative technology and

capabilities where it helps them

compete and impact the

business, while accepting more

standardized packaged solutions

in areas that do not necessarily

require differentiating capabilities.

IDC

IT-developed applications have

become the primary driver for

growth and differentiation for

enterprises. The building of these

custom agile applications is

becoming a hallmark of the new

digital enterprise. Accenture

Vision, 2014

Forrester Research: Don’t Just Maintain Business Applications, Raise Business Responsiveness, 2014

“

”

Packaged

Applications

26% App

Maintenance

49%

Custom

Applications

25%

Business Software Spending*


SAP HANA: In-Memory Platform for All Applications

JSON R Open Connectivity MDX SQL

Consumer-grade

experience

Application Services

Database Services

Integration Services

Social Network

Data

Geospatial

Data

SAP HANA Platform

Machine

Data

Text

Data

Structured

Data

For Cloud and On-Premise

Open Interfaces

In-Memory

OLTP & OLAP

All Data – one copy

Embedded Libraries


Typical Application

Architecture

HANA as a Fast Data

Engine

HANA as an

Integrated Platform

Architectural Options to Use SAP HANA Platform Each Layer Takes Care of Partial Tasks of an Application

Data Ingestion

Business Logic

Presentation logic

Data Process

Data Storage DB

Client

Application

Server Application

Server Application

Server

DB

Application

Server

Client

SAP HANA

In-Memory

Platform

Client

SAP HANA

In-Memory

Platform

Development,

crowd source

… the project

is great

Development,

crowd source

… the project

is great

Development,

crowd source

… the project

is great


Innovation Previously Unfeasible Mitsui Knowledge Industry – Cancer Cell Genomic Analysis

Goal: transform comprehensive patient

care to fight against cancer

Reduce the time to detect variant DNA

Support personalized patient

therapeutics

DNA results 216x faster – in 20 minutes

or less

Streamline process of providing

individualized cancer drug

recommendation


Developer Licenses to Get Started

Use Develop Learn

Trials/Sandboxes Free, time-limited

development environments

Developer Licenses Full development

(free license,

hosting costs may occure)

Commercial

Licenses For Customers and Partners

Free

Charge


SAP Developer Center: http://developers.sap.com

• One-Stop Shop for SAP Developers

• Structured by developer topics, including SAP HANA

• Guided developer experience

• Access to developer editions of SAP platforms and tools

• Integrated with SAP.com and SCN migrating towards 1DX

http://developers.sap.com


Helping you to get started with new SAP technologies

SAP CodeJam is a 5 to 6 hours hands-on coding and

networking event where attendees share their

knowledge and collaboratively develop with SAP

technologies, platforms and tools in a fun and casual

environment.

The events are developer community focused and

supported by SAP, exploring technologies available

through the SAP Developer Center.

For more details on the CodeJam program or the

multiple topics we offer, check out our page here:

http://scn.sap.com/docs/DOC-37775





openSAP Cources: http://open.sap.com

Keeping pace with the rapidly developing world of information technology is a need

that SAP helps to fill with openSAP

openSAP is developed and provided by SAP in cooperation with the Hasso Plattner

Institute

openSAP works according to the principle of "Massive Open Online Courses" (MOOC),

but is not the replacement for formal SAP Education or SAP certification

Some recent courses:

Software Development on SAP HANA (Delta SPS 09)

Build Your Own SAP Fiori App in the Cloud

ABAP Development for SAP HANA

SELECT "Key_Features" FROM SAP.HANA

Key SAP HANA Features for Application Development


SAP HANA Components for Application Development

SQL JSON .NET J/ODBC OData HTML5 MDX XML/A R


Database Services


Graph

Data

Geospatial

Data

SAP HANA Platform

Machine

Data

Text

Data

Structured

Data

For Cloud and On-Premise


SAP HANA XS Engine Native SAP HANA Application Fully Leveraging In-Memory Computing

SAP HANA

Client

Applications running on SAP HANA XS Engine that:

Provide powerful search services and built-in web server to

access static content stored in SAP HANA repository

Optimize database connector to access in-memory data faster

Support attractive and dynamic HTML5 UI via OData services

or by writing native application-specific code that runs in SAP

HANA context

Application development following a layered

approach

UI rendering completely in the client (browser, mobile apps)

Server-side procedural logic in JavaScript

All artifacts stored in the SAP HANA repository

Presentation

logic

Control flow

logic

Calculation logic Data

XS


Sample of some cool ideas from the community

„A Simple Door Monitoring System with HANA XS and Raspberry Pi”

by Ferry Gunawan

http://scn.sap.com/community/developer-center/hana/blog/2014/07/09/build-a-door-sensor-with-raspberry-pi-and-hana





















SAP HANA Smart Data Streaming

• Capture, filter, analyze, and act on

millions of events per second in real time

• Capture high value data in HANA and

direct other data into Hadoop

• Stream live information to operational

dashboards

• Perform continuous queries using

declarative (CCL) or model-driven

approaches

Incoming

streams

Stream

(push)

SAP HANA

Streaming

Service



„HANA Smart Data Streaming in Action” by Eric Du

http://scn.sap.com/community/developer-center/hana/blog/2015/03/17/hana-smart-data-streaming-in-action
















SAP HANA Predictive Analysis

1 Predictive Analysis Libraries (PAL)

Accelerate predictive analysis and

scoring with native, in-database

algorithms delivered out-of-the-box

Graphical Modeling

Pre-built commonly utilized business &

predictive algorithms to facilitate a faster

and easier development

2 R Integration

Execute R scripts via high performing

parallelized connection. Embed R

scripts as part of overall query plan.

Client Tools

SAP Predictive Analysis,

SAP InfiniteInsight,

BI clients: SAP Lumira

Partner Tools: SAS

SAP Industry &

LoB Applications

Demand Signal Management, Fraud

Management, Audience Discovery &

Targeting, over 20 other Apps

New Custom

Built

Applications

In-Memory Processing Engine

SQL Engine Text Engine

Calculation Engine

PAL1 R-Scripts2

Association Analysis

Cluster Analysis

Classification

Analysis

Time Series Analysis

Outlier Detection

Link Prediction

Data Preparation

…

R-Engine


SAP HANA In-Memory Predictive Analytics Predictive Analysis Library (PAL) – Algorithms Supported

Association Analysis • Apriori

• Apriori Lite

• FP-Growth

• KORD – Top K Rule Discovery

Classification Analysis • CART

• C4.5 Decision Tree Analysis

• CHAID Decision Tree Analysis

• K Nearest Neighbour

• Logistic Regression

• Neural Network

• Naïve Bayes

• Support Vector Machine

Regression • Multiple Linear Regression

• Polynomial Regression

• Exponential Regression

• Bi-Variate Geometric Regression

• Bi-Variate Logarithmic Regression

Probability Distribution • Distribution Fit

• Cumulative Distribution Function

• Quantile Function

Outlier Detection • Inter-Quartile Range Test (Tukey’s

Test)

• Variance Test

• Anomaly Detection

Link Prediction • Common Neighbors

• Jaccard’s Coefficient

• Adamic/Adar

• Katzβ

Data Preparation • Sampling

- Random Distribution Sampling*

• Binning

• Scaling

• Partitioning

• Principal Component Analysis (PCA)

Statistic Functions

(Univariate) • Mean, Median, Variance,

Standard Deviation

• Kurtosis

• Skewness

Statistic Functions

(Multi-variate) • Covariance Matrix

• Pearson Correlations Matrix

• Chi-squared Tests:

- Test of Quality of Fit

- Test of Independence

• F-test (variance equal test)

Other • Weighted Scores Table

• Substitute Missing Values

Cluster Analysis • ABC Classification

• DBSCAN

• K-Means

• K-Medoid Clustering

• K-Medians

• Kohonen Self-Organized Maps

• Agglomerate Hierarchical

• Affinity Propagation

Time Series Analysis • Single Exponential Smoothing

• Double Exponential Smoothing

• Triple Exponential Smoothing

• Forecast Smoothing

• ARIMA

• Brown’s Exponential Smoothing

• Croton Method

• Forecast Accuracy Measure

• Linear Regression with Damped

Trend and Seasonal Adjust



„Predicting My Next Twitter Follower with SAP HANA PAL” by Lucas Sparvieri

http://scn.sap.com/community/developer-center/hana/blog/2013/09/02/predicting-my-next-twitter-follower-with-sap-

hana-pal

*PAL – Predictive Analysis Library

http://scn.sap.com/community/developer-center/hana/blog/2013/09/02/predicting-my-next-twitter-follower-with-sap-hana-pal




















Spatial Processing with SAP HANA Gain Competitive Advantage by Uncovering New Insights with Native Spatial

Processing

Real-time Spatial

Processing

High-performance algorithms

analyze massive amounts of

spatial data in real time

Mobility Visualization Analytics HTML5 GIS Applications

Spatial Analytics

Optimization

Columnar storage architecture

eliminates need to create spatial

indexes, tessellation, or other

optimization techniques

Geo-content & services

Maps, geo-content, and

geospatial services open

integration for seamless

application development

Spatial Data Types &

Functions

Store, process, manipulate,

share, and retrieve spatial data

directly in the database

SAP HANA Spatial Processing

Business Data + Spatial Data + Real-time Data

Geo – Services

- Geocoding

- Base maps

Geo – Content

- Political

Boundaries

- POIs

- Roads

Columnar

Spatial

Processing

- Clustering

Calc Model/

Views

- Joins

- Views

Spatial

Functions

- Area

- Distance

- Within

Spatial Data

Types

- Points

- Lines

- Polygons

Transaction

Data Unstructured

Data

Location

Data

Machine

Data


Examples of some cool ideas from the community

„Experiences with SAP HANA Geo-Spatial Features” by Trinoy Hazarika

http://scn.sap.com/community/developer-center/hana/blog/2014/02/25/experiences-with-sap-hana-geo-spatial-

features-part-1

http://scn.sap.com/community/developer-center/hana/blog/2014/02/25/experiences-with-sap-hana-geo-spatial-features-part-1




















SAP HANA Text Analytic

Native full-text and fuzzy search

Exploit full-text search capabilities for exact, freestyle, linguistic, fuzzy, and synonym-based search and ranking

Info Access Toolkit

Rapid development of search-enabled applications through API and reusable UI building blocks

File Filtering

Unlock text from binary documents

Ability to extract and process unstructured text data from various file formats (txt, html, xml, pdf, doc, ppt, xls, rtf, msg)

Load binary, flat, and other documents directly into HANA for native text search and analysis

Native Text Analysis

Give structure to unstructured textual content

Expose linguistic markup for text mining uses

Classify entities (people, companies, things, etc.)

Identify domain facts (sentiments, topics, requests, etc.)

Supports up to 31 languages for linguistic mark-up and extraction dictionary and 11 languages for predefined core extractions

SAP HANA

Information

Access Services Suggestion Search Metadata

Column

Store Tables

Metadata Search Model

Search

Engine

Search

Fuzzy Ranking

Snippets

Text

Processor

Linguistic

Processing

HANA Apps

Applications and Analytics leveraging

Text Search & Text Analysis

capabilities

Search UI configured with

Info Access toolkit running

natively on SAP HANA



„Detecting World Cup GOAL using Twitter and SAP HANA” by Stevanic Artana

http://scn.sap.com/community/developer-center/hana/blog/2014/07/03/goal-detection-using-twitter-and-sap-hana

















SAP HANA Graph Engine

• Manage property graphs within flexible, in-memory

columnar store – faster queries and less storage

• Combine graph with advanced analytics – text,

predictive, geospatial – in a single transaction

• Offer GEM language to traverse and manipulate

graphs

• No duplication of data to create graphs

SAP HANA

Graph Engine



http://www.btw-2013.de/proceedings/The%20Graph%20Story%20of%20the%20SAP%20HANA%20Database.pdf

http://www.btw-2013.de/proceedings/The Graph Story of the SAP HANA Database.pdf





Application

Leverage remote database’s unique processing capabilities by pushing processing to remote database; monitors and

collects query execution data to further optimize remote query processing

Compensate missing functionality in remote database with SAP HANA capabilities

Accelerate application development across various processing models and data forms with common modeling and

development environment

Merge Results

SELECT

from DB(x)

SELECT

from DB(y)

SELECT

from HIVE

Application

One SQL Script

SAP HANA

Virtual Tables

Supported DBs as of SP6: HANA, Sybase ASE, IQ Hadoop/HIVE, Teradata

Data-Type Mapping & Compensate

Missing Functions in DB

Modeling

Environment

Modeling

Environment

Modeling

Environment

Modeling and

Development Environment

Rapid Data Provisioning with Data Virtualization


Examples of some cool ideas from the community

„HADOOP HDFS Explorer built with HANA XS and SAPUI5” by Aron MacDonald

http://scn.sap.com/community/developer-center/hana/blog/2014/07/03/hadoop-hdfs-explorer-built-with-hana-xs-and-

sapui5

http://scn.sap.com/community/developer-center/hana/blog/2014/07/03/hadoop-hdfs-explorer-built-with-hana-xs-and-sapui5




















SAP HANA with SAP Lumira Server Applications That Need Easy Ways to Implement Advanced Analytics

Native – SAP HANA XS application

with Installation using SAP HANA

Lifecycle Manager (LCM)

Robust with SAP HANA load

balancing, failover, backup, recovery

built-in

Secure – Identity and access

management based on SAP HANA

platform and users

Lumira Datasets

(real-time or static)

Lumira Stories

SAP

Lumira

SAP HANA

1. Build Lumira Data Sets/Views

(Stored in SAP HANA)

2. Build Story (Stored in SAP HANA)

3. Visualize (uses Lumira Datasets/

Views and Stories stored inside SAP

HANA)

Faster results from real-time transactional data

1 2

3

Top Reasons -> Choose("SAP HANA")

What Do Those Features Mean for You to Choose SAP HANA

Platform?


Storage Storage

CPU

Memory

CPU

Memory

Sub-Second Response, No Matter How Complex

Process data and application logic in parallel (MPP), using all cores in a multi-core architecture, by effectively partitioning data

Avoid unnecessary compensation (e.g., buffering, data duplication) during application execution by running application using the SAP

HANA application services (built-in web server)

Eliminate disk I/O by keeping all data in memory using column store and by significantly compressing data

Access data faster using any column as index and by accessing only relevant columns via dictionary-encoded column store

CPU

Memory

Bottleneck

Data Hard Disk: 10,000,000ns*/SSD: 200,000ns*

Disk Storage

Log

60ns*

L1 Cache

L2 Cache

L3 Cache

1.5ns*

4ns*

15ns*

Core 1 Core N

Any Column as Index

Parallelized Query

Query Compressed Data

Log

Copy into memory

Code

DB App Data

(DB + App) SAP HANA

Scan

3.2 billion integers/sec/core

Aggregate

12.5 million integers/sec/core

Ingest

1.5 million records/sec/node


Real-Time Applications, Zero Latency

Run both transactional and analytical applications on one single data model

– Database tables designed to support simultaneous high volume/high speed transactional and analytical processing

without compromising data consistency (ACID compliance)

Aggregate on-the-fly with no pre-materialization on key figures, including current transactions, using column store and

parallel aggregation and the optimization for outer joins, distributed joins

Any delay of availability of transactional data for reporting or analytics has a major impact on business workflow; for

example, period closing. SAP HANA can report (e.g., P&L) while we make adjustments, which is important for the

consolidation.

The shorter response times enable users to increase the use of the system

Traditional: OLTP and

OLAP Separate

6 Hours 12:00:00 AM

OLTP + OLAP in

SAP HANA

10:00:00 AM 10:00:01 AM Immediate

Current Data 24-hour Old Data

Aggregate

ETL SAP HANA

6:00:00 AM


Embed sentiment fact extraction in same SQL

Embed geospatial in same SQL

Embed fuzzy text search in same SQL

CREATE FULLTEXT INDEX i1 ON PSA_TRANSACTION( AMOUNT, TRAN_DATE, POST_DATE, DESCRIPTION, CATEGORY_TEXT ) FUZZY SEARCH INDEX ON SYNC; SELECT SCORE() AS SCR, * FROM "SYSTEM"."PSA_TRANSACTION" WHERE CONTAINS (*, 'Sarvice', fuzzy) ORDER BY SCR DESC;

Click-

stream

Customer

Data

Connected

Vehicles Smart

Meter

Point of

Sale Mobile Structured

Data Text Data RFID Machine

Data

Support advanced text analytics

Analyze text in all columns of table and text

inside binary files with advanced text

analytic capabilities such as automatically

detecting 31 languages; fuzzy, linguistic,

synonymous search using SQL.

Structure unstructured data

Use advanced text analytics, such as

sentiment fact extraction, to structure

unstructured data

Analyze streaming data from integrated

ESP in combination with data in HANA

Process geospatial data

Social

Network

SAP HANA

Any Data

SQL

Geospatial

Data

Process Any Data, in Any Combination, Instantaneously

with SQL


“ It is only a matter of scaling the hardware – there are no other variables or unknowns.

SAP HANA: Re-Thinking Information Processing for Genomic and Medical Data, Prof. Dr. Hasso Plattner, 2013

”

Multi-core/

parallelization

No disk Partitioning Distributed

computing

Scale Up Scale Out

With the power of mathematics and distributed computing, SAP HANA can predictably complete any

information processing tasks, however complex, within a given time-window

• Need new IMC benchmark: introduces new capability, such as

no aggregation or no indices, which needs new benchmark

design

• No pre-aggregated result: The test addresses the load-then-

query ability without using any pre-caching results

Extreme Linear Scalability

Across Multi-Nodes Query processing time (in seconds)

Query 1 Single customer and

material for one month

Query 2 Range of customers and

material for one month

Query 3 Year-over-Year trending

report for Top 100

customers for 5 years

SALES AND DISTRIBUTION REPORTS

Linear Scalability to Meet Any Time Window


ODBC, JDBC

SAP HANA

Easily migrate your applications

(e.g., Java, PHP, .NET) using JDBC,

ODBC, and OData/JSON

Build new web applications with any

open source HTML5/JS libraries,

Server Side JavaScript

Easy to bring data into HANA

– Import data in CSV, Excel, or

Binary formats. Load Geospatial

files in shapefile, CSV, Binary,

WKT, and WKB file formats.

– Reuse current data sources with

Data Virtualization

– Replicate real-time data from

multiple sources into SAP HANA

for comprehensive data analysis

Open Cloud Partner Program

allows you to select the best SAP

HANA cloud deployment option from

several partners

App Services

(Web Server)

DB Services

Browser/Mobile

Web JS Lib Data Viz Lib

Web App Server

http(s),OData/JSON

ODBO

Third Party

&

Custom Application

HTTP(S), OData, XML/A

ODBC, JDBC, ADBC, ODBO

MDX, SQL

SQL Script

Any HTML5/JS Library

Stored Procedure Virtual Tables

Import

Real-time Replication

CSV, Binary, shapefile,

WKT, and WKB files

Bring Your Own Code to an Open Platform


Browser/Mobile

Web App Server

DB Server

SQL

Stored

Procedures

http(s)

Web JS Lib Data Viz Lib + + HTML5/JS

Libraries

Browser/Mobile

http(s), OData/JSON http(s)

OLAP Predictive Text Mining

BRM

DB Server DB-oriented Logic

Text Mining

Predictive

SQL Scripts

R Integration

Decision Tables

SAP HANA App Logic App Logic App Logic

App Logic App Logic App Logic App Logic App Logic App Logic

App Logic App Logic App Logic

Aggregate

+ + + Flexible Table:

Push-down code: Replace application logic in multiple places with reusable DB logic written in SQL Script, consumed through

OData

Efficient execution with built-in application services: Significantly improve application performance by running applications using

SAP HANA application services (built-in web server) to avoid multiple layers of buffering and to reduce data transfers and

processing logic

Optimized and open: Built-in SAPUI5 libraries with open integration to third-party libraries for both desktop and mobile user

experience

Dynamic Schema: Dynamically add up to 64,000 columns with SQL Insert or Update statements without altering schema

+

App Services

(Web Server) Procedural App Logic

OData Java Script

Standard Table:

Transformative Power, Simplified Programming


Apps

SQL Script (Optimized Query Plan)

Unstructured

PAL R-scripts R Engine

“ The HANA platform at Cisco has been used to deliver near real-time insights to our execs, and the integration with R will allow us to

combine the predictive algorithms in R with this near-real-time data from HANA. The net impact is that we will be able to take the

capability, which takes weeks and months to put together, and deliver just in time as the business is changing.

Piyush Bhargava, Distinguished Engineer IT, Cisco Systems (video)

”

“See” the Future Accurately in Real-Time

Accelerate predictive analysis and scoring with in-database algorithms delivered out-of-the-box. Adapt the models

frequently.

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)

C4.5 decision tree

Weighted score

tables

Regression

KNN classification

K-means ABC classification

Associate analysis:

market basket

Apps

Virtual Tables

OLAP Unstructured

Predictive

Logic

R

Logic

Pre Process Pre Process Pre Process

Geospatial

https://www.youtube.com/watch?feature=player_embedded&v=HLg9L-2bkec


$

$

$

$

$

$

Web Application Server

Enterprise Search

Business Rule Management

Predictive Analytics

Planning

Geospatial

Data Warehouse Appliance

ETL

Event Processing

Multiple Databases

“ Pointing to Glass' Law (sourced to Roger Sessions of ObjectWatch), which states that “for every 25 percent increase in functionality of a

system, there is a 100 percent increase in the complexity of that system,” Gartner emphasizes the ability of an enterprise to get the most

out of IT money spent.

Gartner

”

Text Analytics/Mining/Unstructured Data

Development/Modeling Tools

Life

cycle

Mg

mt/A

dm

in/M

on

ito

rin

g T

oo

ls

Simplify development, modeling, and administration

environments with Eclipse-based tool

Reduce TCO: consolidating heterogeneous servers and

data into SAP HANA servers to reduce the TCO for the

system, backups, time for backups, and maintenance

Avoid hidden costs due to data quality, synchronization,

and latency

Higher productivity: remove unnecessary tasks to get

significantly higher productivity and help users focus on

working on the material

Un

ifie

d D

eve

lopm

ent/

Mo

de

ling

/

Ad

min

/Mo

nito

ring

with

Eclip

se

-

base

d to

ol

SAP

HANA

Database Cache

Data Warehouses

De-Layer, De-Clutter. Consolidate!

SELECT Flexible_Choices

FROM SAP.HANA

ORDER BY 1 ASC


SAP HANA Appliance

On-Premise

SAP HANA One (Premium)

Public Cloud

SAP HANA Enterprise Cloud

Managed Private Cloud

Limited Scale Any Scale Elastic Scale

SAP

HANA

SAP

HANA

Choose hardware (Intel

x86-based architecture)

from hardware vendors

HP, IBM, Fujitsu, Cisco,

Dell, NEC, Hitachi,

Huawei, and VCE as of

July 2013

Scale as required

Real-time platform, infrastructure,

and fully managed services from

SAP or from our trusted partners

Bring your existing licenses to run

all SAP HANA applications

Mission-critical, global, 24x7

operations

Start using SAP HANA right away

Managed by Amazon Web

Services (AWS), Korea

Telecom, Portugal Telekom,

and VMware

60.5 GB instance size,

allowing for 30 GB of data

HANA One:

– 99¢ per hour. Pay as you use.

Community Support.

HANA One Premium:

– USD 75,000 per year including

SAP Enterprise Support

SAP

HANA

Choose and Change Deployment Options Any Time


SAP Cloud powered by SAP HANA Overview Product Portfolio

Customer Systems

SAP HANA

SAP HANA Enterprise Cloud SAP HANA Cloud Platform Line-of-Business

Apps

(On-Premise) Private Cloud (Managed) Public Cloud

Managed-Cloud-as-a-Service Platform-as-a-Service Software-as-a-Service

People Customer

SAP Business Suite

SAP Business Warehouse

SAP HANA Datamart …

Build Extend Run

applications Finance Supplier

Custom infrastructure and

maintenance

New

Apps

Collaboration

People

SAP Jam Soccer

Health

Consumer

Startups

Business

Ariba

Commerce

Hybris

Any

DB

Integration

leads to new and innovative business processes

Wrap_Up()


SAP HANA Delivers Results for Business Today

1,700+ startups

from 57 countries building

applications on SAP HANA

509% ROI from

building new application

at University of Kentucky

Forrester reports 37%

cost savings for applications

running a single system for

OLAP and OLTP

Simple financial

application reduces data

footprint by up to 37x

3,000 software & tech

partners; 4,000 service partners

200+ Custom-built

applications or PoCs

running on SAP HANA

platform


SAP Startups Focus

http://startups.saphana.com

http://startups.saphana.com/

http://startups.saphana.com/


Endless Possibilities Build Real-Time Modern Applications to Transform Your Business

Ad hoc

Reporting

Application

Dynamically

aggregate data at

any granularity

without pre-

configuration

Planning &

Optimization

Application

MONTH

S M T W T F S

Run real-time

planning or

optimization to find

the best solutions

Hybrid Data

Analytic

Application

change

Course seminar

learn

evaluation

knowledge

discussion

creativity

scale

develop learner

critique

Process or analyze

multiple types of

data, such as

geospatial, text, or

graph data

Internet-of-Things

Application

Network-embedded

devices or sensors to

connect and change

the world

Predictive

Application

Predict the future

based on deep

analysis of history

data


Database Services


SAP HANA Platform


SAP HANA In-Memory Platform Ideal Platform for Next-Generation “Smart” Applications

HTTP(S), OData,

XML/A

ODBC, JDBC,

ODBO

SQL, MDX

Easier

Consumption:

Easier

Development:

JavaScript, HTML5

Connect any

programming

language

App/web services

Decision table

Easier

Processing:

NLP, Predictive,

R-Integration

Spatial processing,

ad hoc OLAP views

Data virtualization

Easier

Ingestion:

Replication,

streaming,

ETL/ELT

Integration,

data cleansing

Personalized

recommendation with

machine learning,

predictive, and rules

Natural

language

processing

Process any variety/

volume (e.g.,

unstructured)

Respond within

predictable time

windows

Key capabilities required for next-generation “Smart” applications:

SAP HANA is a high-speed processing platform to enable:


Learn

SAP HANA Academy

SAP Open Courses

SAP Developer Network

SAP App Development Partner Center

Try

SAP HANA Developer Edition

SAP HANA Cloud Platform

SAP Idea Incubator

SAP HANA One

Experience

SAP HANA Customer Stories

SAP HANA Use Case Map

SAP Customer Journey iPad App

SAP HANA Use Case Repository

Where to Find More Information

http://www.saphana.com/community/hana-academy

http://open.sap.com/

http://scn.sap.com/

https://www.sapappsdevelopmentpartnercenter.com/en/build/hana-cloud-platform/


http://hcp.sap.com/developers

http://incubator.saphana.com/

http://www.saphana.com/community/about-hana/cloud-options/sap-hana-one

http://www.saphana.com/community/learn/customer-stories

http://www.saphana.com/docs/DOC-4812

https://itunes.apple.com/us/app/sap-customer-journey/id614545647?mt=8

http://www.saphana.com/community/implement

57 © 2015 SAP SE or an SAP affiliate company. All rights reserved.

Open Leverage existing investments with an open platform

6

Speed Sub-second response, no matter how complex

1

Real-Time Real-time applications, zero latency

2

Any Data Process any data, in any combination, instantaneously

with SQL

3

Any Source Rapid data provisioning with data virtualization

4

Consolidation De-layer, de-clutter. Consolidate!

9

Simplicity Transformative power, simplified programming

7

Prediction “See” the future accurately in real time

8

Predictable Completion Linear scalability to meet any time window

5

Choice Choose and change deployment options any time

10

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

Thank("you")!

Vitaliy Rudnytskiy

SAP Developer Center

http://developers.sap.com

http://twitter.com/sygyzmundovych

http://scn.sap.com/people/vitaliy.rudnytskiy

http://about.me/witalij









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