Más contenido relacionado La actualidad más candente (16) Similar a #asksap Analytics Innovations Community Call: SAP BW/4HANA - the Big Data Warehouse for the Digital Enterprise (20) Más de SAP Analytics (13) #asksap Analytics Innovations Community Call: SAP BW/4HANA - the Big Data Warehouse for the Digital Enterprise2. 2© 2017 SAP SE or an SAP affiliate company. All rights reserved.
• Quarterly series for the Analytics community
hosted by SAP
• An opportunity for you to direct the discussion, get
your questions answered, and end the session
with some useful advice
• Live and interactive 90 minutes
• Connect on topics before, during, and after the
call via Twitter using #askSAP
#askSAP Analytics Innovations Community Call Series
3. 3© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Legal Disclaimer
The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the
permission of SAP. This presentation is not subject to your license agreement or any other service or subscription
agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any related
presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation
and SAP's strategy and possible future developments, products and or platforms directions and functionality are all
subject to change and may be changed by SAP at any time for any reason without notice. The information in this
document is not a commitment, promise or legal obligation to deliver any material, code or functionality. This document
is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties
of merchantability, fitness for a particular purpose, or non-infringement. This document is for informational purposes
and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document,
except if such damages were caused by SAP´s willful misconduct or gross negligence.
All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ
materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements,
which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
4. 4© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Today’s Speakers
Eric
Leicht
Enterprise Data
Warehousing Architect
J.J. Keller
Andy
Bitterer
Chief Evangelist,
Analytics
SAP
Glen
Leslie
Analytics Architect
SAP
Vamsi
Paladugu
Director, Data and
Analytics
Katerra
Marc
Hartz
Lead Product Manager,
Big Data
SAP
The Changing
Landscape of
Data Warehousing
SAP BW/4HANA
Vision and Strategy
Katerra
Case Study
SAP Data Hub
and
SAP BW/4HANA
6. 6© 2017 SAP SE or an SAP affiliate company. All rights reserved.
SAP customers’ core ask to
Bill McDermott, CEO of SAP:
“What do I need to
do today to stay
ahead tomorrow?”
7. 7© 2017 SAP SE or an SAP affiliate company. All rights reserved.
New Technologies and Expectations Disrupt Business-as-Usual
Scientific Processing
OLAP and OLTP
Together
Data Mining & Prediction
Unstructured Data
Planning Extensions
Geospatial Processing
Hierarchy Processing
Graph Processing
No SQL Processing
Massive Scale Out
Time Series
Real Time, In-memory
Different Locations:
Cloud, data lakes
Additional Types:
Behavioral data, IoT
Higher Volumes:
40% growth YoY
Predictive
Streaming
S/4HANA
Better Performance:
Real-time results
Greater Scope:
Predictive, agile
analytics
Fast time-to-value
8. 8© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Key Business Challenges for the Digital Enterprise
• Time and cost
intensive
• Discord between
Business and IT
• Process and
data silos
• Misaligned &
competing KPIs
• Antiquated UI
and applications
• Business drives
Shadow IT
Slow to deliver
insights or deal with
larger/faster data
9. 9© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Easier access to
information for all users
Reduce development
efforts
Simplicity Openness Modern Interface High Performance
New UX for all users Leverage huge amounts
of data in real time without
compromise
SAP BW/4HANA Design Principles and Values
11. 11© 2017 SAP SE or an SAP affiliate company. All rights reserved.
• Reduce Data
Integration Cost
• Reduce ETL Spend
• Reduce On-prem
Infrastructure Cost
• Speed up change requests
• Reduce Implementation
Time
• Reduce Development
Spend
Simplicity Openness Modern Interface High Performance
• Improve Business User
Productivity
• Reduce Shadow Analytics
• Improve User Adoption
• Reduce Data Handling
Wait Time
• Improve decision-
automation
SAP BW/4HANA Design Principles and Values
12. 12© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Simplicity: Faster Response Through Enhanced Agility and Flexibility
Simplified models
• Number of Modeling (and
DataSource) object types
reduced from 10 to 4
• Field or InfoObject based
Modeling
• Support for external, structured
and unstructured data
Simplified data flows
• Report at any layer with
speed and flexibility
• Virtually combine data
across layers
• Business and service level
driven
Simplified data tiering
• Consistent approach for hot, warm
and cold data
• Allocate temperature by partition
• Distribute data automatically
between hot, warm and cold
storage
13. 13© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Openness: Enabling Broader Business Insights
Open to all data types via simplified
data connectivity architecture
• Dedicated Big Data Source System
• Replicate data in real-time
• Access data virtually
• Load data using optimized processing
Open to tight integration with
SAP native DW approach
Integrated tools for managing mixed
scenarios end-to-end
Leverage advantages of both
approaches
Highly flexible implementation
Open to flexible deployment
On-prem or cloud-based
SAP HANA Enterprise Cloud or
AWS, Azure,
Highly flexible implementation
14. 14© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Modern Interface: Faster to Learn, Easier to Use
Modern Analytics
Simplified
Modeling & Admin
15. 15© 2017 SAP SE or an SAP affiliate company. All rights reserved.
SAP BW/4HANA Content
Difference to classic SAP BW content
• Uses new SAP BW/4HANA features
• Follows the LSA++ architecture
• Delivered Content offers more flexibility
in data acquisition and reporting
• Makes use of the consolidated
InfoObjects
• Provides higher level of detail
(line items, …)
See public slide deck for latest updates
Business Area
16. 16© 2017 SAP SE or an SAP affiliate company. All rights reserved.
• No aggregates or roll-up processes
• No performance specific objects
• Fewer indices
• Faster loading and processing
• Significant performance gain through
push-down of operations/calculations
High Performance: Fast Insight to Action
Data Modeling
Process
Orchestration
SAP BW/4HANA
OLAP
Data Management
Planning
PushdownSAP HANA
17. 17© 2017 SAP SE or an SAP affiliate company. All rights reserved.
SAP Big Data Warehouse Solution
SAP HANA Platform
Enterprise Edition
Advanced Analytics – Spatial, Predictive, Text, Graph, Streaming,
Series, etc.
SAP BW/4HANA
Streaming Analytics, SDI, Active-Active
Business Content
Virtualized LDM
Customers’ Business Content
Analytics, BI, Planning, Predictive
All Sources
ColumnarML
EA Designer
Consolidation Vora, IQ, DT
NLS, Nodes, DWF
Data Hub
18. 18© 2017 SAP SE or an SAP affiliate company. All rights reserved.
SAP Vora and SAP BW/4HANA: Unique Big Data Integration
BW/4HANA
Transactional
• Schema on write
• Governed
• High quality
• Terra bytes
Hadoop
Data Lake
• Schema on read
• Largely ungoverned
• Mixed quality
• Peta bytes
Copy?
Copy?
Virtual
View
SAP Vora
Virtual
View
• Very fast OLAP against Hadoop
• Connecting transactional data and Big Data in both directions
• Graph, text, hierarchies for Big Data in memory
• Runs inside Spark
19. 19© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Natively integrate SAP S/4HANA embedded analytics models
in SAP BW/4HANA
Best practice: The amount of data persisted in the Embedded BW
should not exceed 20% of the overall data volume of the system
SAP BW/4HANA Complements SAP S/4HANA
SAP HANA PLATFORM
SAP S/4HANA
SAP Analytics
Embedded Analytics Strategic Analytics
SAP BW/4HANA
The Embedded BW in SAP S/4HANA is used to support
certain business processes only, e.g. integrated
financial planning processes (aka BPC Optimized)
Embedded BW is not recommended for building an
Enterprise Data Warehouse, considering:
– Upgrades and patches
– Resource allocation and capacity planning
– System Management, Workload Management and
Monitoring
– Backup & Recovery
– Lifecycle management
– High Availability & Disaster Recovery
– Security
– Production support systems ("Break fix systems") and
Quality assurance system
20. 20© 2017 SAP SE or an SAP affiliate company. All rights reserved.
New system
BW on AnyDB
BW/4HANA
+ BW/4HANA
Starter Add-on
New Installation
System Consolidation
BW on HANA
BW on AnyDBBW on any DB
Easy Conversion to SAP BW/4HANA
BW on any DB
BW on any DB
Remote Conversion
In-Place Conversion
21. 21© 2017 SAP SE or an SAP affiliate company. All rights reserved.
One Year On – Success!
750+
Customers
250+
Active
Projects
Record
Adoption
Rate
26. 26© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Define data driven processes across
complex enterprise landscapes
• Access on-premises, cloud, or hybrid data
sources –SAP or non-SAP (Amazon, Hadoop)
• Leverage robust enterprise integration
capabilities
• Connect easily to SAP data management and
application solutions as data sources
• Connect to SAP and non-SAP applications
and analytic solutions as endpoints
SAP Data Hub Overview
Security&Access
SAP Data Hub
SAP Data Hub Modeler Self Service Data Prep SAP Data Hub Cockpit
Apps & Data Stores Analytics Data Science
• Enterprise Apps: DWH,
IoT, CRM, ERP, MDM
• On-Prem data stores
• Cloud/Hybrid stores
• Dashboards
• Ad Hoc Reporting
• Self Services
• ML / R / L / SPARK
• Predictive Analytics
• Advanced Big Data
Analytics
On-Premise Cloud Hybrid
• SAP HANA & SAP BW
• 3rd Party
• Cloud object storage
• Cloud Hadoop
• Cloud/On Prem Hadoop
Such as Such as Such as
User Experience
Data Discovery &
Governance
Data Pipelines &
Orchestration
Data Ingestion &
On-Boarding
Distributed Processing
based on SAP VORA
SAP HANA
In-Memory, Modeling, Virtualization
Hadoop, Object Storages
Persistency's, Cluster Stores
SAP Data Services, SAP LT Replication Server
ETL, Batch, Data Integration, Replication
Streaming & Ingestion
KAFKA, Open Source Technologies
Extensions&
MicroServices
Optimized Engines
(Graph, Time Series…)
27. 27© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Enterprise Systems
Data Discovery &
Pipelines
Orchestration &
Monitoring
Ingestion & Integration
Hadoop
Cloud Storages
ML, Predictive,…
Processing
Runtime
based on
SAP
Vora
Distributed Data Systems
SAP
HANASAP BW/4HANA
SAP S/4HANA
Enterprise App
SAP Data Hub
Unifying Data Silos
28. 28© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Establish a Big Data Warehouse
• Build a modern, open and hybrid DWH offering
for any data
• SAP BW/4HANA as modern and simplified
core data warehouse solution
• Implement and execute high volume
transformations on Big Data Clusters Data
Lake
• Leverage Big Data landscapes for data
onboarding and ingestion for various types of
data and files
• SAP Data Hub as orchestration and refinery
application to address end to end processes
Big Data
(Data Lake, Data Swamp)
High Volume Transformations
SAP BW/4HANA
Data Management
Process
Management
OLAP
Data Modeling
SAP DATA HUB
Data Ingestion & Onboarding
ORCHESTRATION COCKPITPIPELINES
DBs
ERP,
CRM…
Massive Data Store
O N-PREMISE | CLO UD | HYBRID
SAP Data Hub and SAP BW/4HANA
29. 29© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Hadoop, S3, GCP, Azure
SAP Data Hub –
Runtime
Component Overview
SAP BW/4HANA
SAP Data Hub application
Kafka Files
Data Pipelines &
Flows
SAP Vora
Streams Videos Images
CompositeProvider
Advanced
DSO
S/4HANA
RDBMS
Structured
Data
OpenODS View
SDA / SDI
.csv
.parquet
Meta Data
Repository
Process
Chains
Meta Data
(Hive, Atlas..)
Meta Data
Catalog
Analytics Model
Ingestion
Big Data
Processing
Integration
Refined Data
SAP Data Services
Data Flows
30. 30© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Data Warehousing with Social Media
Hadoop
(HDFS)
SAP
HANA
SAPDataHub
Console
3rdParty
SAPPA/Spark
Scala/Python
SAPAnalyticsCloud
STREAM
COPY
BATCH
JOIN
FILTER
CLEANSE
LOCK-UP
SCRIPT
MASK
ANYMONIZE
PARSE
Store & Process
LOAD
EXTRACT
FEDERATE
TRANSFORM
Master
Data
Master
Data
MODELING
Combine refined big data with enterprise
data and corporate master data
Extract or federate data into
SAP BW/4HANA
Ingest Data into S3 as Landing Zone for data
Orchestrate and schedule all related processes
Implement transformations and data pipelines
Harmonize data structures and look up of
reference data
Execute operations on large data volumes
SAP
VORA
Example Scenario
SAPBW/4HANA
OrchestrateAccess
33. 33© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Find out more about SAP BW/4HANA
http://www.sap.com/products/bw4hana-data-warehousing.html
Try SAP BW/4HANA
https://www.sap.com/products/bw4hana-data-warehousing.trial.html
Learn more with the SAP BW/4HANA Community
https://www.sap.com/community/topic/bw4hana.html
Take the OpenSAP MOOC dedicated to SAP BW/4HANA free of charge
https://open.sap.com/courses/bw4h1
Read the Forrester Wave report ”Big Data Warehouse”
https://reprints.forrester.com/#/assets/2/308/'RES136478'/reports
Download the BARC Research report ”BI & Analytics with SAP BW/4HANA”
https://www.sap.com/documents/2017/09/fa01b74e-d67c-0010-82c7-eda71af511fa.html
Find Out More – Key Resources
34. 34© 2017 SAP SE or an SAP affiliate company. All rights reserved.
Introducing the #askSAP Live Chat Series
When: November 8, 2017,
8:00am Pacific Time
Speakers:
Byron Banks, VP of Product
Marketing, SAP
Timo Elliott, Global Innovation
Evangelist, SAP
When: January 10, 2017,
8:00am Pacific Time
Speakers:
Olivier Duvelleroy, General
Manager of Enterprise BI, SAP
Andreas Bitterer, Chief Analytics
Evangelist EMEA, SAP
When: December 14, 2017,
8:00am Pacific Time
Speakers:
Jayne Landry, VP of SAP Hybrid
Analytics & SAP Leonardo
Blair Wheadon, General
Manager of Data Discovery, SAP
www.facebook.com/sapanalytics
35. 35© 2017 SAP SE or an SAP affiliate company. All rights reserved.
New data reality force new thinking and acting
SAP BW/4HANA is THE innovation code line
Bridge between IT and the Business
Big Data scenarios with SAP Vora and SAP Data Hub
Natural companion to SAP S/4HANA
Versatile conversion paths from SAP BW 7.0 onwards
Strong market momentum
7 Key Points to Take Home