1. IBM Power Systems
La nueva generación de sistemas diseñados para el dato y optimizados para Cloud
Juan Manuel Alcudia

2. Power Systems with POWER8 are built with open innovation to put data to work across the enterprise
Designed for big data
First server processor generation optimized for big data & analytics with POWER8 innovative design
Open innovation platform
Delivering the world’s first open server ecosystem revolutionizing the way IT is developed & delivered
Superior cloud economics
Superior cloud price/performance advantages & security to move data-centric applications to the cloud
Power Systems are enhanced with new capabilities so clients are better equipped for Cloud, Analytics & Mobile workloads as well as handling complex, mission critical applications with confidence. 2 2

3. Our Journey and Commitment to Power Systems
May
September
February
April
August
October
Watson Engagement Advisor
5 Power Systems
Linux Centers
around the world
Power development cloud
OpenPOWER Foundation open for business
IBM Innovation Centers fuel Linux on Power
Enterprise systems
2013
2014
August
September
April
April
August
Key Message: Shifts in the marketplace resulted in a change to our strategy. We’ve been on a journey to reposition Power Systems and have been changing the perceptions of Power.  As part of that, we’ve been making investments during the last 12 months.
• We’ve made a number of strategic investments and clients have responded favorably.
We continue to be the ideal platform for IBM Watson; we’ve helped form the OpenPOWER Foundation and are helping to guide its rapid expansion; we announced a new set of scale-out Power Systems; and we are growing our presence in cloud in a big way – with a focus on hybrid.
Clients have been waiting for an alternative to x86, and this is what we’re delivering with the new scale-out systems
Scale-up Systems are coming soon.
Inspur to develop system solutions using OpenPOWER innovations
OpenPOWER Foundation announced
$1 billion Linux on Power investment
POWER8:
3+ years, $2.5 billion R&D investment with hundreds of patents
Ubuntu
supports IBM Power Systems for simpler Linux migration

4. Power Systems with POWER8 are built with open innovation to put data to work across the enterprise
Designed for big data
New solutions for Hadoop, NoSQL and Elastic Storage Enhanced Scale-Out Systems with up to 2 TB / system New POWER8 Scalable enterprise systems
Open innovation platform
First solution from OpenPower – S824L with NVIDIA GPU
Expanded Linux Support – IFLs and new Distributions
Superior cloud economics
Simplified Hybrid Cloud Management built on OpenStack
Enhanced virtualization management for PowerVM and PowerKVM
Power Enterprise Pools for private clouds and easier migration / integration with POWER8

5. Clients are rapidly expanding their data and analytics focus to enhance business opportunities
Map Reduce Implementations
Relational Databases
NoSQL Databases
Instant insight from real-time operational data
Simplified transactions
and reporting
Reduced tuning and indexing
Analytics capability for multiple data types, often used in mobile and social workloads
Scalability and flexibility for different data store models
A scalable data architecture
A parallel and distributed 
programming model
Open source community innovation (Apache Hadoop)
Systems built with POWER8 deliver
2:1 Core Performance,
Memory Bandwidth &
Memory Capacity
DB2 BLU
Oracle in-memory
SAP HANA
Reduced complexity, space (>12x) and cost with CAPI attached Flash
Redis, Cloudant,
Mongo DB,
Cassandra
4x Lower Storage requirements
High performance, data centric design with GPFS & Compression
NoSQL:
Column or Distributed Data Store: Tuple of column name, value, timestamp
Document: Designed for storing, retrieving and managing document-oriented information
Key-value or Associative Array: Collection of (unique) key, value pairs
Graph: Structure with nodes, edges and properties to represent and store data

6. IBM Data Engine for Analytics
IBM IOD 2011
10/13/2017 5:09 AM
10/13/2017
IBM Data Engine for Analytics
A Customized Infrastructure Solution with Integrated Software
Rapid Deployment Flexibility Efficiency
Actionable Insights: preloaded Big Insights plus other analytic applications
Grid infrastructure Services (Platform computing)
POWER8 Systems: 2X Performance
Optional Compression and Encryption
High Performance, Scalable Networking
IBM Elastic Storage Server
1 copy of data versus 3
Scalable file system
Big Data & Analytics Software
Infrastructure Services
POWER8
Servers
GZIP
Compression
Scalable Networking
Scale Out Cluster File System
Elastic Storage Server
Elastic Storage Server 6

7. IBM IOD 2011
10/13/2017
10/13/2017 5:09 AM
IBM Data Engine for NoSQL Reduce complexity and cost of NoSQL solutions
Power CAPI-attached Flash model for NoSQL regains infrastructure control and reigns in the cost to deliver services.
Today’s NoSQL in memory (x86)
Differentiated NoSQL
(POWER8 + CAPI Flash)
WWW
WWW
10Gb Uplink
Load Balancer
10Gb Uplink
POWER8 Server
500GB Cache
Node
500GB Cache
Node
500GB Cache
Node
Flash Array w/ up
to 40TB
500GB Cache
Node
500GB Cache
Node
“Today we are going to show you a revolutionary technology that we think is going to change the way services are consumed on the cloud.”
“We all know the prevalence of NoSQLs and there seems to be flavors for every task at hand. For example, if you need large massive data storage there is hadoop. If you need lightning quick response time there is in memory redis. However, there deosn’t seem to be a way to combine the lightning quickness with massive capacity. Well, today we have a technology in out POWER 8 Systems that introduces a new tier of memory. This new tier lets our POWER 8 System perform like they are stacked with TBs of memory.”
Infrastructure Attributes
192 threads in 4U Server drawer
40 TB of memory based Flash per 4U Drawer
Shared Memory & Cache for dynamic tuning
Elimination of I/O and Network Overhead
Cluster solution in a box
Infrastructure Requirements
Large Distributed (Scale out)
Large Memory per node
Networking Bandwidth Needs
Load Balancing
Backup Nodes 7

8. 4Q ANNOUNCE: CAPI “Developer Kit” for early adopters
An invitation to innovate
Introducing the CAPI Developer Kit
CAPI card and Support documentation will be made available for early adopters
who wish to innovate custom logic / accelerator logic on an FPGA attached via CAPI
This will be an offering from OpenPOWER member Nallatech
FPGA
IBM Supplied POWER Service Layer
AFU
Open space for
Customization and
innovation
Can be plugged into an
Existing Capi enabled
Tuleta system

9. Scale-out Systems built with POWER8
Portfolio is complemented by a full commitment to support an open stack of software
Ubuntu, SUSE, RedHat, PowerKVM, and Open Stack
New Capabilities (4Q2014)
2 TB memory option in S824
Linux SUSE SLES12 (LE) enabling easier application portability
S824L w/ NVidia GPU acceleration
Mixed Endian VM support of a single PowerKVM host
NEBS option for Telco
S812L
S822L
S822
S814
S824L
S824
1-socket, 2U
Linux only
2-socket, 2U
Up to 24 cores
1 TB memory
9 PCI Gen3 slot
PowerVM & PowerKVM
NEBs option
Up to 20 cores
9 PCIe Gen 3
AIX & Linux
PowerVM
1-socket, 4U
Up to 8 cores
512 GB memory
7 PCIe Gen 3
AIX, IBM i, Linux
4 core/P05 for IBM i
2-socket, 4U
Linux
NVidia GPU
Annc/GA in 4Q14
11 PCIe Gen 3
2 TB memory option

10. IBM and NVIDIA deliver new acceleration capabilities for analytics, big data, and Java
Runs pattern extraction analytic workloads 8x faster
Provides new acceleration capability for analytics, big data, Java, and other technical computing workloads
Delivers faster results and lower energy costs by accelerating processor intensive applications
Power System S824L
Up to 24 POWER8 cores
Up to 1 TB of memory
Up to 2 NVIDIA K40 GPU Accelerators
Ubuntu Linux running bare metal

11. The OpenPOWER Foundation creates a pipeline of continued innovation and extends POWER8 capabilities
Opening the architecture and innovating across the full hardware & software stack
Driving an expansion of enterprise-class hardware and software
Building a complete sever ecosystem delivering maximum client flexibility
Launched last year ... The OpenPOWER Foundation is an open development community collaborating together to leverage POWER's open architecture for broad industry innovation. There are currently 57 members with membership continuing to grow globally with latest additions from Australia, Europe, India, Brazil and a continued strong interest from China with 11 members.

12. Focus on ecosystem presence
RIVALRY
Work with Universities
Commercial Developers
OpenPOWER & Open Source Initiatives
Regional Ecosystem Expansion
Growing POWER8 Ecosystem
Double the number of Academic Initiative universities by 2015 (over 100 new schools in 2014)
Drive University Challenge in fall semester 2014
OpenPOWER technology creates greater choice for customers
Open and collaborative development model
60+ members & growing
Over 800 Linux ISVs; ecosystem communities, 100K+ developers (i.e. Ubuntu, Zend, Opscode, etc)
Partner with SWG to grow Linux capabilities for targeted workloads
Build and promote ‘Virtual Appliance’ Reference configurations
Create new GTM constructs for on-premise and cloud deployment
-- Ecosystem has multiple elements: ISVs, middleware, universities, and there are key regional dynamics to consider
-- OpenPOWER has created a rapidly expanding ecosystem, with partners at all levels in the stack
-- Seeing strong growth in ecosystem around Power 12
© 2014 International Business Machines Corporation

13. New Enterprise POWER8-based Systems for the Most Demanding Data Environments
Tackle your largest workloads with massive performance and scalability (up to 192 cores and 1,024 threads; 16 TB; 1,000 VMs)
Operate with more flexibility and efficiency
Maximize availability and serviceability
Instantly respond to the dynamic, changing needs of today’s business
Deploy new workloads faster and at lower cost with Power IFLs and Usage / Utility based pricing for Elastic COD
CLIENT VALUE
Increased system scale
Increased performance per-core
Up to 20 VMs per-core
Enterprise RAS
Increased energy efficiency
Elastic Capacity on Demand
Share resources in Power Enterprise Pool
* Initial GA supports 2 nodes, 64 cores, 8 TB with MES to 3 or 4 nodes in 2015

14. Designed for the most demand data workloads with the agility to handle today’s dynamic business environment
Combining the architectural strengths of Power 795
with the modularity & efficiencies of Power 770/780
High performance compute nodes
Fastest processor in the industry
Up to 48-cores* and 4 TB per node
Modular structure delivers efficiency and flexibility
Flexible growth up to 4 compute nodes *
Improved space and energy efficiency
System design for High Availability and Serviceabilty
Isolated, fully redundant System Control Unit
Enhanced Serviceability
Enhanced memory and system reliability
Economic efficiency with Capacity on Demand flexibility and IFLs
Elastic Capacity on Demand
Mobile Capacity for Power Enterprise Pools
Enhanced Serviceability: Slide rails and Blind Swap I/O adapters
*All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only. 14 14

15. POWER8 Enterprise Systems
192 cores*
1 – 4 node*, 4-16S* (12c)
Up to 16 TB Memory
Power E880
9119-MHE
128* 4.35 GHz
1 – 4 node*, 4-16S (8c)
Up to 16 TB Memory
GHz
1 – 2 node, 4 - 8S (10c)
Up to 8TB* Memory
Power E870
9119-MME
4 GHz
1 – 2 node, 8S (8c)
Up to 8TB* Memory
1 E880 with 3 or 4 nodes, 96 or 128 cores, respectively, will GA in 2Q 2015.
*Statement of Direction. All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

16. Accelerating Availability of POWER8 Enterprise Systems
192 cores*
1 – 4 node, 4-16S (12c)*
Up to 16 TB Memory
GA = 4Q14
Power E880
9119-MHE
128* 4.35 GHz
1 – 4 node*, 4-16S (8c)
Up to 16 TB Memory
64-cores
8 TB
GHz
1 – 2 node, 4 - 8S (10c)
Up to 8TB* Memory
Power E870
9119-MME
4 GHz
1 – 2 node, 4-8S (8c)
Up to 8TB* Memory
1 E880 with 3 or 4 nodes, 96 or 128 cores, respectively, will GA in 2Q 2015.
*Statement of Direction. All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

17. POWER8 Enterprise Systems
1H15
SOD : 192 cores*
1 – 4 node, 4-16S (12c)*
Up to 16 TB Memory
Power E880
9119-MHE
GHz
1 – 4 node**, 4-16S (8c)
Up to 16 TB** Memory
64-cores
8 TB
Expand to 128 cores
GHz
1 – 2 node, 4 - 8S (10c)
Up to 8TB* Memory
Power E870
9119-MME
GHz
1 – 2 node, 4-8S (8c)
Up to 8TB* Memory
1 E880 with 3 or 4 nodes, 96 or 128 cores, respectively, will GA in 2Q 2015.
*Statement of Direction. All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

18. Power E870 & E880 servers Power E870 Power E880
Increased performance and scale
Built-in PowerVM Enterprise Edition
Enterprise RAS
System Control Unit (2U)
Built-in Active Memory Mirroring for Hypervisor
More performance per-watt
8 PCIe adapter slots per node
Up to 4 PCIe I/O drawers per Node*
Share resources in Power Enterprise Pool
Medium Software tier
24x7 Warranty
8 to GHz
8 to GHz
256 to 4TB Memory (8TB SOD*)
1 or 2 nodes (5U) per system
8 to GHz
Up to 192 cores* in 2015
256 to 16TB Memory
1 to 4 nodes (5U) per system
Built-in initial Elastic CoD days
*Statement of Direction to support up to 8TB memory on E870 and up to 4 PCIe I/O Expansion Drawers per node on Power E870 & E880 in 2015.
Initial GA in 4Q14 supports 4TB maximum on E870 and 0 or 2 PCIe I/O drawers per node on E870 & E880.

19. More Scalability than an other 8-socket systems
(best Intel Xeon and best Oracle SPARC)
SAP SD Standard Application Benchmark Results, 2-Tier: SD Benchmark Users
SAP enhancement package 5 for SAP ERP 6.0
Source: http//
1.6X more users than Ivybridge-EX v2
~ 2X more users than Oracle T5-8
with 1/3 less cores!
Fujitsu PQ 2800E
Intel E v2,
120c/240t
Oracle T5-8 T5
128c/1024t
IBM x3950 X6
Intel E v2
IBM Power E870
POWER8
80c/640t
128c
120c
80c
IBM Power System E870 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 80 cores / 640 threads, POWER8; 4.19GHz, 2048GB memory, 79,750 SD benchmark users, running AIX® 7.1 and DB2® 10.5, dialog response: 0.97 seconds, line items/hour:8,722,000, dialog steps/hour: 26,166,000 SAPS: 436,100 database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source:
IBM System x3950 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and DB2® 10, dialog response: 0.85 seconds, line items/hour: 5,421,670, dialog steps/hour: 16,265,000 SAPS: 271,080; database response time (dialog/update): sec / sec, CPU utilization: 98%, Certification #:  Results valid as of 10/3/14.  Source:
Fujitsu PRIMEQUEST 2800E on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and SQL Server 12, dialog response: 0.97 seconds, line items/hour: 5,193,670, dialog steps/hour: 15,581,000 SAPS: 259,680; database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source:
(5) Oracle SPARC Server T5-8 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors/128 cores/1024 threads, SPARC T5; GHz, 2,048 GB memory; 40,000 SD benchmark users, running Solaris® 11 and Oracle 11g; Certification # Results valid as of 10/3/14. Source:
SAP and all SAP logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries. All other product and service names mentioned are the trademarks of their respective
IBM Power System E870 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 80 cores / 640 threads, POWER8; 4.19GHz, 2048GB memory, 79,750 SD benchmark users, running AIX® 7.1 and DB2® 10.5, dialog response: 0.97 seconds, line items/hour:8,722,000, dialog steps/hour: 26,166,000 SAPS: 436,100 database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source:
IBM System x3950 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and DB2® 10, dialog response: 0.85 seconds, line items/hour: 5,421,670, dialog steps/hour: 16,265,000 SAPS: 271,080; database response time (dialog/update): sec / sec, CPU utilization: 98%, Certification #:  Results valid as of 10/3/14.  Source:
Fujitsu PRIMEQUEST 2800E on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors / 120 cores / 240 threads, Intel Xeon Processor E v2; 2.80GHz, 1024GB memory, 49,000 SD benchmark users, running Windows Server 2012 Standard Edition and SQL Server 12, dialog response: 0.97 seconds, line items/hour: 5,193,670, dialog steps/hour: 15,581,000 SAPS: 259,680; database response time (dialog/update): sec / sec, CPU utilization: 99%, Certification #:  Results valid as of 10/3/14.  Source:
(5) Oracle SPARC Server T5-8 on the two-tier SAP SD standard application benchmark running SAP enhancement package 5 for the SAP ERP 6.0 application; 8 processors/128 cores/1024 threads, SPARC T5; GHz, 2,048 GB memory; 40,000 SD benchmark users, running Solaris® 11 and Oracle 11g; Certification # Results valid as of 10/3/14. Source:
SAP and all SAP logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries. All other product and service names mentioned are the trademarks of their respective companies.

20. Superior cloud economics: simplified virtualization & cloud management

21. Superior Cloud economics: Simplified virtualization and hybrid cloud management
Cloud Manager with OpenStack
Extended capability to enable customization & quicker deployment of OpenStack-based cloud solutions
Management across heterogeneous systems, on premises and off premises
Simplified virtual IO administration
Risk reduction by using templates for repeatable deployment of workloads
VM restart accelerates workload recovery
Run any combination of Linux distros via Mixed Endian VM support on a single PowerKVM host
Improve performance using PCI passthru for dedicated I/O
Better availability through PCIe hot plug support
Expanding device and OS support
Import existing KVM VMs
Simplified maintenance with one click system evacuation
Increase scaling by 100% to 20 hosts; 2000 VMs
*All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only. 21

22. Clients are asking for:
IBM Delivers the most powerful foundation for private and public cloud infrastructure
Clients are asking for:
Extreme flexibility, instant response
Higher Availability
Economic Efficiency
Investment Protection
POWER7+
Designed to eliminate planned and unplanned downtime for the most demanding workloads
Shift resources to support planned maintenance
Active – Active for efficient HA / DR
Seamless transition to new technology
Easily manage the changing workload demands of today’s dynamic, real time business environment.
Elastic Capacity on Demand
Move virtual processor and memory resources to address new demands without physically reconfiguring the data center
Leadership IT Efficiency Combining the economic efficiency of Elastic Cloud pricing with systems designed for 80-90% utilization
Usage and utility based pricing
Minimize excess capacity required to manage availability and contingency for dynamic business environments
Ready for the Future Seamlessly integrate next generation technology in your Power Enterprise Pool
Inactive resources are used for processor and memory sparing
Inactive resources can be used for free trials of new applications
Inactive resources can be used with temporary activations for emergency backup
Power E880
Power 780
Power E880 22 22 22

23. Power Enterprise Pools: The most powerful foundation for a flexible, economically advantaged private and hybrid cloud IT infrastructure
Extreme flexibility to instantly respond to changing business demands
Simpler application workload balancing
Easily manage periodic workload spikes and bursting
High Availability
Reduced planned downtime due to system maintenance
Enhanced disaster recovery capabilities
Economic Efficiency
Operate at 80-90% utilization with flexible capacity
Minimize excess capacity required to manage availability or contingency for workload uncertainties
Usage and utility based pricing
Investment Protection and simplified technology transition to POWER8
Upgrade / Share / Move POWER7+ resources & software to POWER8
Transition applications to POWER8 with increased business flexibility
POWER7+
Mobile COD: move processor and memory resources amongst systems
Elastic COD: for periodic spikes in workload demand
OpenStack: for simplified Cloud and Virtualization Management
Designed to eliminate planned and unplanned downtime for the most demanding workloads
Shift resources to support planned maintenance
Active – Active for efficient HA / DR
Seamless transition to new technology
Easily manage the changing workload demands of today’s dynamic, real time business environment.
Elastic Capacity on Demand
Move virtual processor and memory resources to address new demands without physically reconfiguring the data center
Leadership IT Efficiency Combining the economic efficiency of Elastic Cloud pricing with systems designed for 80-90% utilization
Usage and utility based pricing
Minimize excess capacity required to manage availability and contingency for dynamic business environments
Ready for the Future Seamlessly integrate next generation technology in your Power Enterprise Pool
Inactive resources are used for processor and memory sparing
Inactive resources can be used for free trials of new applications
Inactive resources can be used with temporary activations for emergency backup
*All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only. 23 23 23

24. Deploy a Power Enterprise Pool today and your infrastructure is ready for the future
Today, Power Enterprise Pools provides
Simpler application workload balancing
Reduced planned downtime due to system maintenance
Enhanced disaster recovery capabilities
Flexible, efficient private cloud infrastructure
POWER7+
and tomorrow with POWER8…
Provides options for more granularity & flexibility when transitioning applications to POWER8
Tremendous asset/investment protection
Future enhancements planned* to improve automation for high availability and disaster recovery environments
with POWER8
*All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

25. Power Systems with POWER8 are built with open innovation to put data to work across the enterprise
Designed for big data
New solutions for Hadoop and NoSQL databases and Elastic Storage to simplify operations and reduce cost
New and enhanced Power Scale-Out Systems and solutions with up to 2 TB / system
Scalable enterprise systems for the most demanding data environments with leadership performance and scale, up to 16 TB / system and over 80% utilization
Open innovation platform
First solution from the OpenPower Foundation – S824L with NVIDIA GPU for technical computing and high performance analytics
Simplify operations and reduce costs by running new Linux workloads on POWER8- based IFLs
New Linux distributions & turbo charge LAMP solution stacks
Superior cloud economics
Simplified Hybrid Cloud Management with Cloud Manager for OpenStack for a single point of control
Enhanced virtualization management with expanded storage/networking and OS support and increased scalability
Power Enterprise Pools enable enhanced business flexibility and availability with the ability to migrate POWER7 Mobile COD to POWER8 systems

26. Infrastructure Matters: Open Innovation with open innovation to put data to work across the enterprise
Infrastructure Solutions & Expanding Ecosystem
Infrastructure System Software
Expanding choice, simplifying management, lowering costs
Customized infrastructure solutions delivering new, unprecedented value
IBM Data Engine for Analytics
IBM Data Engine for NoSQL
IBM S824L with Nvidia
IBM BLU Acceleration for Power Systems
Scale Out Systems
Enterprise Systems & Pools
Leadership performance and resiliency leveraging new, Open Innovation
Designed for the most demanding data environments with agility and efficiency
POWER7+
Power 780
Power E880
Midrange and Entry are one through four socket systems 26 26

27. Open innovation to put data to work36 21 21 21

28. BIG DATA & ANALYTICS Because the speed of business is money
Héctor Colmenares, IBM SW Core Database Competitive Sales Leader, IM SPGI

29. Tendencias del mercado Demanda de respuestas en real time es una necesidad.
Vivimos en la generación del “NOW”.
Los datos crecen constantemente, y los usuarios esperan respuestas más rápidas.
Movilidad y el uso “democrático” de la información y la analítica hacen de la tecnologia in-memory y mensajería distribuida un requerimiento obligado. La velocidad cambia el negocio.
Nuevas y modernas arquitecturas de datawarehouse dinámicas reemplazarán los modelos tradicionales de datos por la demanda de datos en real-time.
La realidad es que vivimos en el mundo de la inmediates, el ahora ya es tarde, la movilidad, los sensores, adelantarnos, predecir es lo que marca la endencia pero en donod eencaja el bigdata? 29

30. Big Data y analítica del negocio La Revolución de los datos
2+ billion people on the Web by end 2011
30 billion RFID tags today (1.3B in 2005)
4.6 billion camera phones world wide
100s of millions of GPS enabled devices sold annually
76 million smart meters in 2009… 200M by 2014
De los datos mundiales
NO ESTRUCTURADOS
80%
12+ TBs of tweet data every day
IT Logs
? TBs of data every day
Obviously, there are many other forms of data. Let’s start with the hottest topic associated with Big Data today: social networks. Twitter generates about 12 terabytes a day of tweet data – which is every single day. Now, keep in mind, these numbers are hard to keep accurate, so the point is that they’re big, right? So don’t fixate on the actual number because they change all the time and realize that even if these numbers are out of date by 2 years, it’s at a point where it’s too staggering to handle exclusively using traditional approaches.
+CLICK+
Facebook over a year ago was generating 25 terabytes of log data every day (Facebook log data reference:
) and probably about 7 to 8 terabytes of data that goes up on the Internet.
Google, who knows? Look at Google Plus, YouTube, Google Maps, and all that kind of stuff. So that’s the left hand of this chart – the social network layer.
Now let’s get back to instrumentation: there are massive amounts of proliferated technologies that allow us to be more interconnected than in the history of the world – and it just isn’t P2P (people to people) interconnections, it’s M2M (machine to machine) as well. Again, with these numbers, who cares what the current number is, I try to keep them updated, but it’s the point that even if they are out of date, it’s almost unimaginable how large these numbers are. Over 4.6 billion camera phones that leverage built-in GPD to tag your location or your photos, purpose built GPS devices, smart metres. If you recall the bridge that collapsed in Minneapolis a number of years ago in the USA, it was rebuilt with smart sensors inside it that measure the contraction of the concrete based on weather conditions, ice build up, and so much more.
So I didn’t realise how true it was when Sam P launched Smart Planet: I thought it was a marketing play. But truly the world is more instrumented, interconnected, and intelligent than it’s ever been before and this capability allows us to address new problems and gain new insight never before thought possible and that’s what the Big Data opportunity is going to be all about!
25+ TBs of log data every day 30

31. Big Data: todo son datos Paradigma para extraer valor
Transaccional & Datos Aplicativos
Contenido Empresarial
Dato Social
Data Sensores
Big data comes from many sources. Its much more than traditional data sources. And it order to capitalize on the breakthrough opportunities we’ve discussed, you definitely need to look beyond traditional data sources. But at the same time, don’t forget that big data comes from those traditional sources too. Transactional data and application data is growing an a significant rate. Although it’s structured, that data is large and it is contained in many different structures.
Social data also needs to be incorporated. Most social data is really textual data. And the valuable insights remain locked within that text and its many possible meanings. And most of that data isn’t valuable, or has a very short expiry date during which it is valuable. That makes social data very challenging – extracting insight from largely textual content in very little time.
And enterprise content must be amalgamated as well. And that data comes in many forms, and also in significant volume.
Big data includes machine data – “the internet of things” – logs, web logs, instrumentation data, network data. Data generated by machines is multiplying quickly, and it contains valuable insights that need to be discovered.
Volumen
Estructurado
Entrada / Salida
Variedad
No estructurado
Veracidad
Velocidad
Ingestión

32. Big Data: todo son datos Gestión de los datos: No es única
Mobile Storefront
Sales Analysis
Real Time Fraud Detection
Demand Analysis
E-commerce
These innovative solutions that we just talked about on the previous slide are comprised of different types of applications, each of which are best served by different types of data systems that are optimized specifically to each workload for speed, reliability and cost efficiency.
At the top we have the types of innovative applications you are deploying or want to deploy
and at the bottom is IBM’s DB with BLU Acceleration or Informix 12.1 capabilities that are optimized to handle them.
JSON doc 2
Key 2
JSON doc 1
Key 1
Data series 2
Meter 2
Data series 1
Meter 1
Transactional Database
JSON Database
Analytics Data Warehouse
Operational Data Warehouse
Time Series Database
Transaction Processing
Mobile Data Serving
Reporting and Analytics
Operational Analytics
Sensor Data Analysis

33. Analítica dá la clave para incrementar la competitividad
Compañías que realizan analíticas sofisticadas superan a su competencia
2.6x
mas rendimiento que sus iguales del sector
1.6x
Mas ingresos
260%
estar entre los mejores del
sector
2.5x
Valorización del precio del stock
From a survey of over 4,500 executives, managers and analysts, from more than 30 industries in 122 countries, some key statistics have been uncovered, relating to Big Data and Analytics.
Businesses who use analytics, are 2.6 times more likely to outperform their competitors and achieve, on average, 1.6 times revenue growth, following implementation of an analytics solution.
And become 206% more likely to be one of the top performers in their industry, leading to as much as 2.5 times stock price appreciation.
Can any business afford to ignore these growth rates?
In essence if they are not implementing best of breed analytics solutions, they are falling behind their competitors, and loosing relevance in their marketplace, as they likely react too slowly to changes in market trends.
Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology Outperforming in a data-rich, hyper-connected world, IBM Center for Applied Insights study conducted in cooperation with the Economist Intelligence Unit and the IBM Institute of Business Value. 2012

34. Cuantificar valor de la analítica
Cierre Contable – Mejora del flujo de caja
Speed equals 39% faster payment*
Average closing of accounts
Source: SAP value engineering study
2011
2012
2013
days to payment 59 36
reduced days to payment
increased cash flow
business growth
So lets look at How an optimized analytics solution, makes a difference to the bottom line.
And illustrate, how speed of business process, equals money.
A study done by SAP, looked at how long companies take to complete their monthly financial close of their accounts
Looking at the average of the worst performing customers, they take 22 days, to close their books.
By contrast, the average of the best performing customers, they take just 7 days to close their books.
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If we put that into business terms, here is an example of a report generated by XERO one of the fastest growing SaaS companies globally, specialising in Accounting software , they analysed 16 million invoices from thousands of businesses totalling £20 billion and reported that by increasing the speed of invoicing companies were seeing a 39% improvement in the number of days it was taking to get paid. Reducing the number of days to payment has increased their cashflow and has lead to business growth
So here we truly see how speed of business process, is about money.
Doing things better is important, understanding the business better is important, but doing those things faster, is delivering business growth by improving cash flow.
*Based on analysis done by Xero, a SaaS company specialising in accounting software, Link to blog & infographic: HERE
Speed of Business Process, Is Money

35. La lógica del Data Warehouse Contemplar componentes, propósitos, zonas
Vertical Industry Accelerators
Advanced Application Capabilities
Information Integration & Governance
Data types
Real-time processing & analytics
Actionable insight
Decision management
Logical Data Warehouse
Machine and sensor data
Operational systems
Exploration, landing and archive
Deep analytics & modeling
Image and video
Predictive analytics and modeling
Trusted data
Enterprise content
Reporting & interactive analysis
Reporting, analysis, content analytics
Transaction and application data
Social data
Discovery and exploration
Third-party data

36. La lógica del Data Warehouse Ejemplo de la Solución de IBM
Vertical Industry Accelerators
BigSQL and SQL based applications
Advanced Application Capabilities
Information Integration & Governance
Data types
Real-time processing & analytics
Federation and In-memory federated cube
Actionable insight
Decision management
Logical Data Warehouse
Machine and sensor data
Operational systems
Exploration, landing and archive
Deep analytics & modeling
Image and video
Predictive analytics and modeling
Trusted data
ORACLE
Microsoft
Teradata
Enterprise content
Reporting & interactive analysis
Reporting, analysis, content analytics
Transaction and application data
Social data
BigMatch
Third-party data
Discovery and exploration
Streams

37. ¿Qué hace diferente BLU Acceleration
¿Qué hace diferente BLU Acceleration? Innovacionees de IBM Research & Developments Labs.
Next Generation In-Memory
In-memory columnar processing with
dynamic movement of data from storage
Analyze Compressed Data
Patented compression technique that preserves order so data can be used without decompressing
Encoded
CPU Acceleration
Multi-core and SIMD parallelism (Single Instruction Multiple Data)
Data Skipping
Skips unnecessary processing of irrelevant data
Instructions
Data
Results
BLU Acceleration is a game changing combination of innovations from IBM Research and Development Labs that dramatically simplifies and speeds the delivery of business insight from data. Easy to set up and self optimizing, BLU Acceleration eliminates the need for indexes, aggregates, or time consuming database tuning to achieve top performance and storage efficiency.
With next generation In-memory capabilities, BLU Acceleration can deliver the performance of in-memory processing without the cost or limitations of in-memory only systems. BLU Acceleration does not require all data to fit in memory in order to achieve breakthrough performance. The system has the efficiency and intelligence of keeping the most relevant data in memory to maximize performance – optimizing both system memory and CPU memory (known as cache). This means, as data volumes grow, clients do not need to continuously buy expensive memory.
Columnar organized BLU tables are well suited for compression because of their similar, common, and repeating data in each column – which is optimized by encoding frequent values with fewer bits. The patented encoding technology of BLU Acceleration’s Compression preserves the order of the data, enabling compressed data in BLU tables to be used without decompressing it. Furthermore, the encoded values are packed into bits matching the register width of the CPU – for reduced I/O, and better CPU and memory utilization. As a result of the very high levels of compression (clients report 10x compression) and elimination of indexes and aggregates, BLU Acceleration significantly reduces the need for storage. These storage savings result in cost saving on multiple fronts: e.g., hardware, power, and maintenance.
BLU Acceleration is designed to take full advantage of the latest innovations in microprocessor advancements. With SIMD processing (Single Instruction Multiple Data), BLU Acceleration can apply a single instruction to many data elements simultaneously, for faster data processing. BLU Acceleration is as designed to take advantage of multiple cores for maximum core utilization.
BLU Acceleration automatically detects large sections of data that don’t qualify for a query – and skips the unnecessary processing of this irrelevant data. E.g. skipping all the records prior to 2010 for a question about data from 2010 to the present.
This is done with automatically maintained metadata that users do not have to worry about defining or maintaining. Data skipping can deliver vast savings across compute resources (CPU, RAM, and I/O).

38. + + + BLU Shadow Tables Single Server
Dedicated analytics and reporting
Operational analytics
Mixed workload analytics with OLTP
OLTP Indexes
Analytical Indexes +
Traditional row-based tables, with indexes for, for tables dedicated to OLTP or Operational Analytics
Simple BLU tables ( columnar ) for tables dedicated to analytics and reporting workloads
OLTP Indexes
Traditional row-based tables, with indexes and BLU Shadow Tables for tables with mixed workloads + +
Power of BLU
Faster analytics and reporting
Faster OLTP
Simpler environment
Single Server
All 3 scenarios in a single database

39. Oportunidad: Big Data y Analytics
2+ billion people on the Web by end 2011
30 billion RFID tags today (1.3B in 2005)
4.6 billion camera phones world wide
100s of millions of GPS enabled devices sold annually
76 million smart meters in 2009… 200M by 2014
PROBLEMAS DE RENDIMIENTO
SAP BW
CARGAS ANALÍTICAS
COMPETENCIA:
SAP con HANA
ORACLE con EXADATA
TERADATA
MS-SQL
PREMISA: AHORRO DE COSTES
Of world’s data is unstructured
80%
12+ TBs of tweet data every day
IT Logs
? TBs of data every day
Obviously, there are many other forms of data. Let’s start with the hottest topic associated with Big Data today: social networks. Twitter generates about 12 terabytes a day of tweet data – which is every single day. Now, keep in mind, these numbers are hard to keep accurate, so the point is that they’re big, right? So don’t fixate on the actual number because they change all the time and realize that even if these numbers are out of date by 2 years, it’s at a point where it’s too staggering to handle exclusively using traditional approaches.
+CLICK+
Facebook over a year ago was generating 25 terabytes of log data every day (Facebook log data reference:
) and probably about 7 to 8 terabytes of data that goes up on the Internet.
Google, who knows? Look at Google Plus, YouTube, Google Maps, and all that kind of stuff. So that’s the left hand of this chart – the social network layer.
Now let’s get back to instrumentation: there are massive amounts of proliferated technologies that allow us to be more interconnected than in the history of the world – and it just isn’t P2P (people to people) interconnections, it’s M2M (machine to machine) as well. Again, with these numbers, who cares what the current number is, I try to keep them updated, but it’s the point that even if they are out of date, it’s almost unimaginable how large these numbers are. Over 4.6 billion camera phones that leverage built-in GPD to tag your location or your photos, purpose built GPS devices, smart metres. If you recall the bridge that collapsed in Minneapolis a number of years ago in the USA, it was rebuilt with smart sensors inside it that measure the contraction of the concrete based on weather conditions, ice build up, and so much more.
So I didn’t realise how true it was when Sam P launched Smart Planet: I thought it was a marketing play. But truly the world is more instrumented, interconnected, and intelligent than it’s ever been before and this capability allows us to address new problems and gain new insight never before thought possible and that’s what the Big Data opportunity is going to be all about!
25+ TBs of log data every day 39

40. DB2 with BLU vs Microsoft SQLServer Query Response Time: (In Seconds, Less is Better)
7X-8X Better Performance with equal cores

41. “56% better performance, with 25% of the cores ! Wow, that’s great !”
DB2 with BLU vs Microsoft SQLServer Query Response Time: (In Seconds, Less is Better)
BestOffer
Less Cores & Licenses but Much more Performance => Better SLA
“56% better performance, with 25% of the cores ! Wow, that’s great !”

42. Estimated HW Infrastructure for Production – Year 1 and Year 5 assumption yearly 20% growth
Source Oracle database 8 TB on BW 7.0 (non-unicode)
DB2 on 2-tier architecture (on one server all components)
HANA on 3-tier rachitecture (database and application on different servers)
Huge savings through DB2 Technology
Often DB2 BLU needs 70-95% less HW

43.  4 x POWER servers (160 cores)
COMPARATIVA ENTRE IBM POWER + DB2 contra ORACLE EXADATA
NECESIDAD INICIAL: Sistema SAP (180 sistemas, 48 entornos de producción)
CONTINUIDAD DEL NEGOCIO: Contingencia en 2 centros separados
NOTA:
El ejercicio de sizing se ha basado en la metodología SAP con entornos para Producción, Pre-Producción y Desarrollo/Q
El nivel de rendimiento SAPS ha sido el mismo en ambos casos
La infraestructura IBM es POWER8 + AIX + DB y la de Oracle es EXADATA (INTEL`+ Oracle Linux + Oracle DB)
La opción de IBM permite virtualización
El ejercicio es una estimación y está orientada a mostrar las diferencias de infraestructura entre ambas soluciones
Customer runs DB2 on POWER
- 180 systems, 48 production
- 26 HA (LPM*) + 26 DR (PowerHA)
2 x data centers
Possible Exadata implementation **
- 180 systems, 48 production
- 26 HA + 26 DR clusters
- 2 x BIGGER or more data centers
6 full racks for production + HA
6 full racks for DR
6 full racks for test/QA
6 full racks for dev
6 full racks for the rest 36 systems
 4 x POWER servers (160 cores)
 ~30 full racks (5760 cores)
* LPM - AIX live partition mobility
** No virtualization + limited number of databases per rack (e.g. 8 database servers per full rack, max 24 processor per database)

44.  4 x POWER servers (160 cores)
COMPARATIVA ENTRE IBM POWER + DB2 contra SAP HANA
NECESIDAD INICIAL: Sistema SAP (180 sistemas, 48 entornos de producción)
CONTINUIDAD DEL NEGOCIO: Contingencia en 2 centros separados
NOTA:
El ejercicio de sizing se ha basado en la metodología SAP con entornos para Producción, Pre-Producción y Desarrollo/Q
El nivel de rendimiento SAPS ha sido el mismo en ambos casos
La infraestructura IBM es POWER8 + AIX + DB y la de SAP HANA (INTEL+ Linux + HANA)
La opción de IBM permite virtualización
El ejercicio es una estimación y está orientada a mostrar las diferencias de infraestructura entre ambas soluciones
1 HANA UNIT = 64 Gb RAM = 13 K€
Customer runs DB2 on POWER
- Customer runs DB2 on POWER
- 180 systems, 48 production
- 26 HA (LPM*) + 26 DR (PowerHA)
2 x data centers
Possible HANA implementation **
- 180 systems, 48 production
- 26 HA + 26 DR clusters
- 2 x BIGGER or more data centers
48 appliance servers for production
52 appliance servers for HA+DR clusters
up to 48 appliance servers for test/QA
up to 48 appliance servers for dev
up to 36 appliance servers for rest
 4 x POWER servers (160 cores)
 x HANA servers
( cores)
* LPM - AIX live partition mobility
** No virtualization + limited number of databases per rack (e.g. 8 database servers per full rack, max 24 processor per database)

45. 98 percent 30 percent 50 percent
Balluff GmbH – Game-changing boost to information delivery with IBM DB2 enables rapid insight
98 percent
faster access to complex reports
30 percent
typical report speed increase
50 percent
faster SAP ERP response times
Solution Components
SAP® Business Warehouse, SAP ERP, SAP ERP HCM, SAP CRM, SAP NetWeaver® Enterprise Portal, SAP PI
IBM® AIX®, DB2® for Linux, UNIX and Windows with BLU Acceleration, PowerHA® SystemMirror®, PowerVM®, System Storage SAN Volume Controller, Tivoli® Storage FlashCopy® Manager, IBM® Power® 750, FlashSystem™ 840, XIV®, IBM System and Technology Group Lab Services, IBM Software Group Services
Business challenge: Balluff knew that slow access to finance and business reports threatened productivity and potential growth. How could executives gain fast insight into critical data to make better business decisions?
The solution: The company moved its SAP Business Warehouse to IBM® DB2® with BLU Acceleration, running on IBM Power Systems™ with IBM AIX® and IBM PowerHA®.
“IBM DB2 with BLU Acceleration is the ideal solution for us because we can gain new insights into business data more rapidly. Deploying IBM DB2 with BLU Acceleration was a low-risk project; implementation was quick and easy without affecting availability.”
—Bernhard Herzog, Team Manager Information Technology SAP, Balluff
Deep Blue IBM Solution SAP Stack
IBM SAP Alliance
© 2014 IBM Corporation 45

46. Business Analytics Accelerator
Big Data & Analytics
Big Data & Analytics
The Business Value, Why Speed is Money
Dynamic Query
Compatible Query
Dynamic Cubes
DB2 with BLU
Business Analytics Accelerator
Increase productivity & drive business growth
Adding Value, not complexity
Infrastructure
That
Matters
82X más rápido
An important consideration for your selling approach, is understanding that 63% of all opportunity now come from outside of IT.
Just think about that one. If you are only talking to, and selling to IT staff, you are only addressing, one third of IT based opportunities in your clients.
If you have only been focused on IT, you could now triple your opportunity scope, if you SELL into the line of business in your clients.
A perfect example of this recently, was a business who knew they had an issue with how long queries were taking to run on their database, and had attributed a cost to time wasted in waiting for a response.
IBM and a Business Partner ran a proof of concept with a UK customer, but we focussed on presenting the POC to the Managing Director, The Finance Director and the Chief Operating officer, all of them board members in this company. The POC was such a big improvement, their query time so improved, that initially the client thought IBM had manipulated the system. The finance director then spent 30 minutes running some ad hoc queries of his own, including a very complex query that completed in 97 secs, the FD told us that this was a report that they were never able to complete in their existing environment. In fact he said they stopped this query on their system because after several hours it still had not completed. The client was so impressed, that they ended the POC by saying “We’ll take it”.
The Client didn’t know what the solution was. They didn’t know what the hardware, software or services were. IBM and our partner had just fixed a business problem, and could do so at a cost that would pay back to the business in a few months. There was no discussion of how IBM’s hardware compared to a competitors. No going through a feeds and speeds check list, to see what solution was better on paper. Importantly, there wasn’t the same issue with price negotiation, as there was no competitive price to compare to.
This is the difference selling to line of business makes, talking about and solving business issues
<click>
So what we want to talk through in this session, is a different way of talking to clients.
We want to give them a “WOW”.
And in this example, we can talk through what difference a big data and analytics project, can make to a business. Its understanding of its business. How it can help identify new market opportunities, to help growth. Importantly, selling a business vision with a “WOW” factor.
Once we have the customer bought into the vision, excited at the prospect, we need to discuss, still from a business level perspective, “HOW” we can both enable AND deliver this difference to their business. Still with the focus on the business value, still not discussing features.
And then importantly, for our sellers, our partners, and for IT Staff that may be engaged by the business, “WHAT” hardware & software we are actually providing for this solution.
As the inverted triangle is alluding to, importantly, we must learn how to change the focus, so that the value to business becomes the most important aspect, not what the components of the solution are.
The other great benefit is you will also be talking in a similar language to other sellers calling on the business.
The objective here is not to make you an expert in Big Data and Analytics, but understand some of its benefits, and how linking with other sellers, can help you drive new and larger opportunities. It could be you help uncover a new opportunity for Big Data and Analytics, just through understanding the high level benefits to a business, at which point you can engage with your colleagues who are the experts in this field, and be part of the team that builds the end-to-end solution for the client.
vs. Competitor Row Store Database on Ivy Bridge (x86)1
1) Based on IBM internal tests as of April 7, 2014 comparing IBM DB2 with BLU Acceleration on Power with a comparably tuned competitor row store database server on x86 executing a materially identical 2.6TB BI workload in a controlled laboratory environment. Test measured 60 concurrent user report throughput executing identical Cognos report workloads. Competitor configuration: HP DL380p, 24 cores, 256GB RAM, Competitor row-store database, SuSE Linux 11SP3 (Database) and HP DL380p, 16 cores, 384GB RAM, Cognos , SuSE Linux 11SP3 (Cognos). IBM configuration: IBM S824, 24 cores, 256GB RAM, DB2 10.5, AIX 7.1 TL2 (Database) and IBM S824, 16 of 20 cores activated, 384GB RAM, Cognos , SuSE Linux 11SP3 (Cognos). Results may not be typical and will vary based on actual workload, configuration, applications, queries and other variables in a production environment.
82x calculation based on geometric mean calculation giving equal weighting to the report per hour (RPH) improvements in the three categories of simple, intermediate, and complex reports. GEOMEAN(RPH_simple,RPH_intermediate,RPH_complex) = GEOMEAN(18.85,40.07,747.63)=82.66

47. POWER + BLU Acceleration pero y …. ¿Cómo avanzamos?

48. Elegir una opción de las dos configuraciones
Small Configuration
Large Configuration
Existing Data Warehouse
Supports up to 5 TB uncompressed active data (1 TB compressed data)
Hardware Configuration
Power S814: 8 cores, 3.72 GHz
Memory: 256 GB DRAM
Storage:
146 GB (RAID 1) (OS/PGM VG)
2.4 TB HDD (RAID 5) (Data VG)
AIX Standard Edition
PowerVM Enterprise Edition
Software Configuration
DB2 Advanced Workgroup Edition
Existing Data Warehouse
Supports up to 10 TB uncompressed active data (3 TB compressed data)
Hardware Configuration
Power S824: 24 cores, 3.52 GHz
Memory: 1 TB DRAM
Storage:
2.4 TB HDD (RAID 5) (Data VG)
1.55 TB SSD (DB2 overflow cache)
146 GB (RAID 1) (OS/PGM VG)
AIX Standard Edition
PowerVM Enterprise Edition
Software Configuration
DB2 Advanced Workgroup Edition
PRECIO MUY INTERESANTE ** PREGUNTE A SU VENDEDOR DE IBM ** 48

49. Configuración Try&Buy, incluye HW & SW
New BLU POC Program
Stack: Power 8, DB with BLU Acceleration and Cognos BI 10.2 with Dynamic Cubes
Target Use Cases: “Business Intelligence Workload Accelerator”
Provides acceleration for BI workloads in competitive or back-level environments
Can work in any environment
Commodity hardware accounts
Microstrategy, Business Objects
SQLServer, Oracle
Is an accelerator to your existing environment
Configurations
5 pre-defined Power 8, DB2 BLU and Cognos BI configurations to support various workload sizes
Announcement Highlights
Announced: June, 2014
Leverages established Power POC processes
Define the free trial period
Try with your own data
Owners for Additional Information

50. GRACIAS