5 Things you should know about the IBM Data Engine for Analytics Solution - Power Systems Edition
- The IBM Data Engine for Analytics is a customizable infrastructure solution with integrated software optimized for big data and analytics workloads.
- The IBM Data Engine is ideal for workloads such as Hadoop or Spark and provides flexible and adjustable storage and compute resources that are easy to deploy and align to specific line business requirements.
- This means you can move or add more storage and compute when and where it’s needed to address multiple workloads as requirements change and evolve. It provides an easy onramp for clients to lay the foundation for bringing different big data and analytics workloads together onto one infrastructure.
- Built on IBM Power Systems, the IBM Data Engine for Analytics fully integrates the innovative capabilities of IBM Elastic Storage Server, IBM Platform Computing and networking components with Linux on Power scale-out systems. Clients can add big data and analytics software such as IBM InfoSphere BigInsights for Hadoop and Spark based analytics, IBM InfoSphere Streams for high ingest streaming analytics, and IBM Watson Explorer analytical components for advanced Natural Language Processing of unstructured data.
- The deep integration and optimization of analytics workload performance on Power Systems enables businesses to reach unparalleled performance to deliver insights to the business faster.
The following are the features and benefits of the solution:
- Complete, pre-assembled and tested infrastructure with big data and analytics software preloaded.
- On-site services for fast configuration and data center integration.
- Intelligent cluster management and automation for effective deployment.
- Easily set-up and manage workloads for multiple tenants.
- Adjustable resource allocation to meet diverse line of business demands.
- Scalable and extendable as needs change and as the enterprise grows.
- Reliability without data duplication.
- Tailored big data and analytics optimizations.
- Lays the foundation for consolidating traditional data analytics with new workloads such as Hadoop and Spark.
For more information, refer to the following website:
Announcing the IBM ITSO POWER8 Technology and System Technical Deep Dive Workshops
The goal with this workshop is to bring to the technical communities the news on POWER 8. This class focuses on providing the attendees with valuable information on the new POWER architecture including the lastest virtualization features.
These workshops are designed for all IT professionals, including technical project managers, architects, systems programmers, systems designers and application developers who need to understand how to design and exploit the hardware and software infrastructure required to effectively run modern IBM System z and POWER8 solutions. All workshops are open to Clients, Business Partners, Independent Software Vendors (ISVs) and IBMers. These workshops are especially recommended if you plan to use the latest levels of technology that are available or recently announced.
For locations and the links to the registration for the IBM ITSO POWER8 Technology and System Technical Deep Dive, WRZ13G (1 day), follow this website:
I encourage anyone interested to participate in the IBM Platform Computing Solutions Reference Architecture and Best Practices to submit your nomination for consideration.
There are already multiple Redbooks publications, and a few RedPapers on different technical challenges which IBM Platform Computing is addressing via their solutions. If you have any suggestions for topics for this residency, do not hesitate on adding comments to this blog.
During the residency, the team will provide reference architectures and best practices for deploying the Platform Computing solutions. Moreover, the team will implement and test Platform Computing solutions software stack focusing on specific industry solutions (engineering, life sciences, financial services, business analytics, oli and gas) leveraging the comprehensive set of IBM System x rack servers, IBM BladeCenter, IBM General Parallel File System (GPFS). This IBM Redbooks publication will demonstrate and document that the combination of IBM's System x, IBM GPFS and IBM Platform Computing solutions deliver significant value to clients in need of cost-effective, highly scalable, and robust solutions. IBM depth of solutions can help the clients plan a foundation to face challenges in how to manage, maintain, enhance, provision computing environments to analyze, for example, the growing volumes of data within their organizations.
To submit a nomination, you must use the online web nomination form:http://www.redbooks.ibm.com/Residents.nsf/GetResidency?OpenAgent&ID=PW-3901-R01
You are invited to attend on Tuesday May 20 at 10:30 AM during the IBM Edge event, session sBD06 IBM Big Data Analytics Over a Public Cloud By: Luis Cruz and Daniel de Souza Casali and discover how to implement a big data analytic environment over SoftLayer running Hadoop with GPFS and performing map reduce with IBM Symphony. You can use the information presented during this session as a reference architecture that you can run over a public cloud for your company.
For additional information on all sessions to be presented during the event, refer to:
For information about the IBM Edge event, refer to the following website:
For information on the IBM Redbooks publication which can provide more details on the reference architecture presented during the session, refer to the IBM Platform Computing Solutions Reference Architectures and Best Practices, SG24-8169 at the following website:
The residency team invites you to download and read the Workload Optimized Systems: Tuning IBM POWER7 for Analytics Redbooks publication.
This publication addresses topics to help clients to take advantage of the virtualization strengths of the POWER platform to solve system resource utilization challenges and maximize system throughput and capacity while helping our clients set up environments to analyze large amounts of data.
This IBM Redbooks publication contains the following table of contents:
Chapter 1. Introducing analytics on IBM Power Systems
Chapter 2. Implementing Cognos on IBM Power Systems
Chapter 3. Implementing IBM SPSS on IBM Power Systems
Chapter 4. Preferred practices
There is greater focus to provide our clients with the systems, solutions, tools, and best practices to manage and extract information from large amount of data stored in their enterprise.
The residency team looks forward to reading your comments on this publication, and on the topic of analytics.
The residency team is pleased to announce the draft release of the Implementing an IBM InfoSphere BigInsights Cluster using Linux on Power, SG24-8248. The topics described in this publication are as follows:
Introduction to the solution
Step by step integration and configuration for IBM Spectrum Scale (formerly GPFS), Hadoop and IBM Platform Symphony
The draft publication can be downloaded at the following website:
Note: The team encourages the readers to send us feedback. Please add your comments to my blog entry.
Keep tune to http://www.redbooks.ibm.com/
under the Residencies Tab for IBM ITSO residency announcements for BigData and analytics on IBM Power Systems.
For additional information about IBM BigData and analytics on IBM Power Systems, refer to the following website:
I would like to announce the opening for nominations for the Implementing an Analytics Optimized Solution on IBM POWER8 residency focusing on configuring, writing, exploring, testing, tuning, and documenting how to leverage the latest IBM POWER8 and Big Data solutions to run analytics workloads.
The goal for this residency is to continue to develop technical content and scenarios to:
1. Describe how to plan, prepare, install, manage and show how to use IBM POWER8 to run analytic workloads on IBM POWER8.
2. Deliver additional technical documentation, complementing available products and solutions manuals to help you with your data analytic needs.
3. Document scenarios on how to use IBM POWER8 Cluster for Technical Computing workloads.
The residency announcement including time table, requirements, and the nomination form which can be found at the following website:
Note: Your feedback is important and welcome. For topic suggestions or residency recommendations, please add your comments to my blog entry.
For more information on IBM Analytics Solutions, refer to the solutions website at:
The IBM Analytics Solutions on IBM POWER8 residency team would like to invite you to stop by the IBM booth during SC15 in Austin, Texas to see the implementation of the IBM Data Engine for Analytics on IBM POWER8 with the IBM Elastic Storage Server (ESS), and to view the demonstration on how to leverage IBM BigInsights, IBM DB2, IBM BigSQL, IBM Cognos, IBM SPSS, and IBM Spectrum Scale for a real time retail offer generation.
The residency team consisted of (from left to right, see photo below):
- Antonio Moreira de Oliveira Neto IBM Brazil
- Dino Quintero IBM USA - IBM Redbooks Project Leader
- Kanako Harada IBM Japan
- Brian Yaeger IBM USA
- Reinaldo Tetsuo Katahira IBM Brazil
- Robert Simon IBM USA (not in the photo)
For more information about the SC15 conference, refer to the following website:
For more information about IBM Data Engine for Analytics - Power Systems Edition, refer to the following website:
The residency team is pleased to announce the draft release of the IBM Platform Computing Big Data for Analytics Workloads, SG24-8265. The topics described in this publication are the following:
Introduction to Big Data
Big Data, analytics and risk calculation software portfolio
IBM Platform Symphony v7.1 with Application Service Controller
Big Data mixed IBM Power Systems and Intel environment planning
IBM Spectrum Scale for Big Data environments
IBM Application Service Controller in a mixed environment
IBM Platform Computing Cloud Services
The draft publication can be downloaded from the following website:
Note: The team encourages the readers to send us feedback. Your feedback is important and welcome. Please add your comments to my blog entry.
Keep tune to http://www.redbooks.ibm.com/
under the Residencies Tab for IBM residency announcements in the area of IBM Platform Computing Solutions for Cloud, Analytics, Big Data, and so on.
For additional information about IBM Platform Computing Solutions, refer to the following website:
The residency team is pleased to announce the publication of the Implementing an Optimized Analytics Solution on IBM Power Systems, SG24-8291 publication which positions IBM Analytics and Big Data solutions with a well-defined and documented deployment model within a POWER8 virtualized environment.
Table of contents
Chapter 1. Introduction
Chapter 2. Solution reference architecture
Chapter 3. IBM POWER8 for analytics workloads
Chapter 4. Scenario: How to implement the solution components
Chapter 5. Scenario: Integration of the components for the solution
Chapter 6. Scenario: How to use the solution
Appendix A. Advanced implementation
Appendix B. Ambari node role planning
The publication can be found at the following website:
Note: Your feedback is welcome. For any topic suggestions or overall residency recommendations, add your comments to my blog entry.
For more information on the IBM Data Engine for Analytics - Power Systems Edition, refer to the solutions website at:
5 Things You Should Know about IBM Watson:
- IBM Watson is made of a cluster of IBM Power Systems servers
- The cluster also contains additional I/O, network and cluster controller nodes
- IBM Watson is designed to find insight, discover breakthroughts, and predict outcomes
- IBM Watson is unfolding cognitive thinking by predicting events and taking preemtive actions
- IBM Watson can help businesses analize their data and help them become more competitive
For more information, refer to the following website: http://ibm.co/1VCgjCa
Algo Que Debe Usted Saber acerca de IBM Watson
- Sabia usted que IBM Watson esta compuesto de un cluster de servidores IBM Power Systems
Para mas informacion acerca de la solucion, visite la siguiente direccion: http://ibm.co/1VCgjCa