Learn about the challenges of big data, common use cases and the SAP BI Solutions for big data

1. BI in the Era of Big Data
JC Raveneau
March 2014

2. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
2
Companies are missing new signals

3. Big Data Today
GE engines in 2013
“
”
“These engines generate 1Tb of data per aircraft per day”
Jeff Immelt – CEO GE
Keynote for Minds + Machines 2012 talking about the new LEAP engine

4. Primary Big Data Platform Scenarios
Providing insight from machines, assets,
and devices for better real-time decisions,
predictions, and operational performance
Machine Data Insight
Omnichannel Data
Insight
M2M Sensors
Mobile IoT
Processes Assets
Unstructured Multi-media
Real-time
Voluminous Data Geospatial
Enterprise Data
Social
Providing insight from high volume and high
variety data for real-time analytics &
actionable intelligence

5. Big Data Examples
Instantly predict market trends and customer needs
Predict how market price volatility will impact your production plans
See changes in demand or supply across your entire Supply Chain immediately
Monitor and analyze all deviations and quality issues in your production process
Provide exactly the right offers and service levels to every customer
Have a continuously-updated window into future sales, showing changes in real time
Understand what your customers and potential customers are saying about you, right now
Predict cash flows to manage collections, risk and short-term borrowing in real time
5

6. BIG DATA GIVES SHOPPERS FASHION ADVICE TO FIT THEIR STYLE

7. 7
©2013 SAP AG or an SAP affiliate company. All rights reserved.
REAL-TIME OFFERS. INCREASE REVENUE WITH OFFERS BASED ON RECENT USER BEHAVIOUR

8. 8
©2013 SAP AG or an SAP affiliate company. All rights reserved.
LISTEN. TAP INTO THE STREAMING VOICES OF PEOPLE, PROCESSES, AND THINGS

9. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
9
SAP Sentiment Intelligence
http://www.youtube.com/watch?v=ERcy0YyHmts&feature=youtu.be&t=30s
Value Proposition
•Understand the local demand for products and services
•Evaluate impact of marketing campaigns and events
•Get early warning of product defects and shortfalls
•Channel and market-specific customer concerns and delights
Result
•Creation of promotional campaigns to shape customer demand
•Intelligence about new product development, design, cross-sell , bundling and product introduction
•Selection, localization, allocation, distribution, and pricing of merchandise in all commerce channels

10. Infrastructure / Platform

11. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
11
11
Cobbling Disparate Tools together is NOT the Answer!
David Feinleib. The Big Data Landscape

12. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
12
SAP HANA Platform for Big Data
Applications
Analytics
Landscape management & orchestration
HANA In Memory
Modeling & lifecycle management
HADOOP SAP IQ
Roles, security, governance, compliance, audits
Analyze
& Apply
Accelerate
Acquire
Transactional
Planning & Simulation
Graph
Analytical
SAP Industry & LoB Apps
Partner & Custom Apps
Spatial
Consume
Process
ESP
Extended Storage (IQ)
Tiered Storage (Hot-warm-cold)
Smart Data Access
Text, Social Media Processing
Visualizations
Predictive
Mobile
Replication Framework
Data Services
IM / MDW
Business Intelligence

13. Big Data is Strategic to SAP
13

14. Current Solutions
SAP HANA as a Big Data Platform

15. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
15
Instant Result and Infinite Storage with SAP HANA
Value Proposition
One enterprise-class platform for Big Data applications and Analytics
Real-time like never before
Federated: bring all data together under one model
Near-line and infinite storage with Sybase IQ and Hadoop
Use Cases
Real-time analysis and dashboards on transactional data or event streams (Customer testimonial)
Analyze data from different systems (ex: Optimize genome analysis with HANA, R and Hadoop at MKI)
Compute statistical models on large volumes (ex: Detect critical signals from 100 PBs of data in eBay EDW)

16. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
16
HANA and SMART Data Access
Access remote information from SAP HANA using smart data virtualization techniques
Leverage HANA Predictive engines
Load high-value data from Hadoop rapidly into SAP HANA for real-time analysis
Remote caching & optimized performances
Combine unstructured and structured data for insights never seen before

17. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
17
Analytics on HANA
Benefits
Simple IT landscape
ONE place for data modeling
ONE platform
Lower cost of ownership
Native access to HANA dimensional models and predictive capabilities
Add details
HANA Tables & SMART DATA Access
Information Models
Direct access
Dashboarding and Apps: Design Studio
Agile Visualization Lumira, Explorer
SAP HANA
Reporting:
Crystal Reports
Advanced Analytics Analysis, Predictive

18. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
18
Analytics with HANA
Benefits
Supercharge an existing SAP BusinessObjects footprint
Speed and richness of HANA models
Real-time & CEP
Large volumes
Familiar tools and semantic layer
Short time-to-value
No additional training required
HANA Tables & SMART DATA Access
Information
Models
SAP HANA
UNIVERSE
Dashboarding and Apps: Dashboards
Reporting:
Web Intelligence
Crystal Reports

19. SAP HANA: Text Analysis for Big Data
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 Text & Sentiment Analysis
Search
Analyze
Predict
19

20. SAP ESP: Streaming Big Data
20
Analyse and act on events as they happen – by relying on real-time event-driven analytics. With our award-winning complex event processing (CEP) platform, you can develop and deploy business-critical applications that give you the agility you need to make quick, profitable decisions.
Process and analyse multiple streams of high-speed, high-volume complex event data in real time Get actionable information from event streams and generate alerts for events needing quick action Initiate automatic responses to changing conditions based on one or a combination of events Develop applications quickly for fast ROI with the high-performance CEP engine

21. SAP HANA: Predictive & Machine Learning
SAP HANA platform converges Database, Data Processing and Application Platform capabilities & provides Libraries for predictive, planning, text, spatial, and business analytics so businesses can operate in real-time.
Provide Business Analysts with sophisticated algorithms to take the next step in understanding their business and modeling outcomes.
Perform statistical analysis on your data to understand trends and detect outliers in your business.
Build models and apply to scenarios to forecast potential future outcomes
Combine, manipulate and enrich data to apply it to your business scenarios. Self-service visualizations and analytics to tell your story
21

22. Current Solutions
SAP BusinessObjects solutions on Hadoop

23. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
23
Stand Alone Big Data Analytics
Value Proposition
Expand your BI Platform to Big Data
Immediate and familiar access via the semantic layer
Enable all BI clients
Leverage the modeling power of the Universe
Use Cases
Anything SQL-Like.

24. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
24
The BI Portfolio and Hadoop
Universe access to Apache Hadoop & EMR Hive supported via JDBC drivers
Enables Hadoop access to all BI Clients in the suite
Crystal Reports 2013 offers additional direct connectivity to Apache Hive JDBC and Simba HIVE ODBC
SAP Lumira 1.13+ offers direct connectivity to HIVE via the Apache JDBC driver
See the PAM for version details
Via HIVE 0.10 with Lumira 1.13
Crystal Reports via JDBC & ODBC

25. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
25
Access functionality in BI 4
Hive is seen as a relational database
A Universe is built using HiveQL language
Ability to:
Retrieve data in the report of server memory and run local calculations
Push calculations down to the HIVE engine
Build multi-source universes (federation between HIVE and other sources)

26. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
26
CURRENT SOLUTIONS OVERVIEW
Data Integration
Log Files
Text Data Sources
Structured Data Sources
SAP HANA Platform
SAP BusinessObjects BI
SAP Sources
Non-SAP
Trans 1
Non-SAP
Trans 2
BI Universe
Available with DS 4.1
SAP HANA smart data access
Available with SAP HANA SPS6
Available with BI 4.0 FP3*
Hadoop
* BI 4.0 FP3 for single-source universe
BI 4.0 FP5 for multi-source universe
SAP Lumira Desktop
Via HIVE 0.10 with Lumira 1.13

27. ©2013 SAP AG or an SAP affiliate company. All rights reserved.
27
Roadmap
Build on the Big Data Platform
Leverage SQL-Like Access
Self-Service Big Data
Thanks to in-memory, predictive, federation and more, SAP HANA offer un-preceded opportunities for big data analytics.
SQL-like access via *DBC drivers offer opportunities to embrace emerging big data sources with existing investments.
The variety of big data also means new formats, new paradigms and new opportunities.
We’ll keep driving innovation end- to-end, from data to analytics in order to help customers get the most value out of their big data
We’ll selectively extend the support to big data sources based on their technical maturity and market demand
Our research projects are driven by the objective to mine big data for more value, quicker and at a lower cost

28. 28
http://www.sapbigdata.com/analytics/ http://www.sapbusinessobjectsbi.com
For More Information
Contact information:
JC Raveneau
Sr. Director, Big Data Analytics