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000-551 - IBM Optim Implementation for Distributed Systems (2009) - Dump Information

Vendor : IBM
Exam Code : 000-551
Exam Name : IBM Optim Implementation for Distributed Systems (2009)
Questions and Answers : 122 Q & A
Updated On : February 15, 2019
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000-551 IBM Optim Implementation for Distributed Systems (2009)

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000-551 exam Dumps Source : IBM Optim Implementation for Distributed Systems (2009)

Test Code : 000-551
Test Name : IBM Optim Implementation for Distributed Systems (2009)
Vendor Name : IBM
Q&A : 122 Real Questions

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IBM IBM Optim Implementation for

IBM and Clinton global Initiative collaborate to support influence lives through expertise | Real Questions and Pass4sure dumps

with the aid of Dr. Angel Diaz, IBM vice president of Developer know-how, Open supply, and Advocacy

When typhoon Maria hit Puerto Rico on September 20, 2017, I watched closely because the storm devastated my homeland and the place the place my fogeys nonetheless are living. We misplaced communication, and that i bear in mind wishing we had a method to hold in touch. within the months that adopted, my coronary heart ached with each story I heard of households who had been left without a option to reach every different physically because of broken infrastructure and no way to attain every other very nearly due to lack of connectivity.

expertise played (and continues to play) a major role in the island's healing. but the appropriate technology, utilized on the appropriate second, could have made even more of a change. figuring out that the underlying technology exists to support individuals in natural disasters is a big piece of what fueled us to launch demand Code. IBM partnered with David Clark cause, the United international locations Human Rights, the American purple move, and New enterprise buddies (NEA) to launch this global, multi-year initiative to developers to help clear up pressing global complications. In 2018, we geared toward mitigating the consequences of herbal failures through sustainable utility options.

greater than 100,000 developers and records scientists from 156 international locations participated in our inaugural demand Code problem and submitted hundreds of magnificent options. It became inspiring to see so many builders put in lots of of thousands of hours of coding outdoor of their day jobs — all to support individuals they've on no account met.

talking with builders world wide, i noticed that I wasn't on my own as a technologist who has been for my part littered with herbal disasters. in addition to Puerto Rico, we met developers on every continent who had encountered earthquakes, wildfires, flooding, and greater. The choice to lend their ability to a more robust trigger become convenient.

We made phenomenal progress in 2018, however we're not stopping there. definitely, we're doubling right down to expand our network of companions and enhance the number of lives we will aid improve.

Coding for a higher cause

The demand Code team recently back to San Juan, Puerto Rico, the place we joined 500 business, govt, and NGO leaders for the Clinton international Initiative motion community on submit-disaster recuperation. This two-day adventure focused on setting up new, selected, and measurable plans to improve recuperation and promote long-time period resiliency throughout Puerto Rico, the us Virgin Islands, Dominica, Antigua, and Barbuda.

To that conclusion, we're announcing a new collaboration between IBM and the Clinton international Initiative university. We're teaming up to work without delay with school college students to support them harness the energy of expertise, akin to AI, blockchain, cloud, and IoT fueled by means of facts, to boost options for one of the crucial world's most pressing challenges, including natural disasters.

Code, group, and faculties

This year, we're planning to host a series of in-adult and online campus "codeathons" to interact and equip school students with the expertise and expertise resources they need to assist turn their concepts into tangible motion.

we've considered already that college students are invaluable sources of notion for catastrophe relief options. Take, as an instance, Syracuse institution graduate pupil Anmol Handa and his classmates. As part of a codeathon remaining year, he and his group developed a funding platform to assist small groups in rebuilding their communities following failures. another promising thought changed into introduced forth by Jonah Mudse of Rensselaer Polytechnic Institute, who labored on a student team that created an Airbnb-impressed home sharing app to help displaced families in need.

From competitors to implementation

We're in the process of taking many of the appropriate concepts from ultimate yr's competition and putting them into action, starting with the 2018 call for Code profitable crew, venture Owl. This IoT and utility answer has the power to hold communities linked within the aftermath of a catastrophe. or not it's exactly the class of solution that could have stored me in touch with my family unit following typhoon Maria in 2017.

As destiny would have it, Luis Arocho, Chief information Officer for the government of Puerto Rico, has agreed for his office to serve as an implementation companion with the intention of retaining first responders and victims related in a herbal disaster. We believe Puerto Rico is the perfect place to serve as a checking out environment as this technology is deployed, and the IBM company provider Corps is poised to work with the OWL team to make it ensue.

At IBM, we're always considering of ways we can harness the energy of know-how for respectable. As technologists, we recognize we're more desirable once we work together. this is why we're so excited to move into the next iteration of delivering code for first rate with new companions by using our facet. together, we're expanding the scope of the developers we will attain and the variety of lives we will assist improve. the realm can all the time use yet another hero. We hope you're going to trust donning your cape and becoming a member of us in this impressive event.

To learn more about how IBM and CGI U are teaming up collectively — as well as next steps from 2018 demand Code winner challenge Owl — be sure to attend the consider Innovation speak "Igniting the subsequent generation of Innovation to trade the realm" on February 14 at 9:30am PST.

This post is sponsor content from IBM and became created through IBM and Insider Studios.

Sitecore® publicizes world Partnership with IBM iX to allow main internet content material administration, Commerce, and advertising solutions | Real Questions and Pass4sure dumps

Sitecore®, the  leader in digital event administration utility, these days introduced a new world partnership with IBM iX, one of the crucial world's largest digital groups and world business design companions. The partnership will make purchasable to valued clientele Sitecore’s leading net content material management, commerce, and advertising solutions via IBM iX designers, know-how experts, and industry strategists in 40 IBM Studios global. 

The elevated partnership brings collectively the full breadth of IBM iX’s capabilities to capitalize on the growing demand for digital advertising and marketing capabilities that create extremely-personalized client experiences throughout all digital touchpoints. 

Matthew candy, global leader, IBM iX, cited that “customer event is the important thing strategic goal of many agencies and core to those businesses’ potential to radically change. i'm very excited that we're expanding out our existing relationship with Sitecore into a worldwide partnership, as they develop into a vital player in our ecosystem of companions.” 

As a world Platinum partner within the Sitecore answer provider program, IBM iX gives the world-type consulting, design, building and implementation services required to set up options on the Sitecore platform and convey exquisite consequences for valued clientele. Matched to Sitecore’s main digital experience administration capabilities, businesses can deliver conclusion-valued clientele with seamless, omnichannel experiences to drive differentiation, promote enterprise transformation, and increase profits and consumer lifetime price. The IBM iX and Sitecore partnership is further empowered with choicest practices and accelerators, as well because the ability to leverage the vigour of IBM Cloud and IBM Watson expertise. IBM iX also brings to endure the unparalleled skills of Bluewolf, an IBM company, creating experiences with Salesforce, with whom Sitecore has a strategic alliance. 


IBM iX and Sitecore® Launch international advertising services and expertise agreement | Real Questions and Pass4sure dumps

SAN FRANCISCO, Jan. 29, 2019 /PRNewswire/ -- Sitecore [®] , the international chief in digital event administration utility, today announced a new global partnership with IBM iX, one of the crucial world's greatest digital agencies and global business design partners. The partnership will make accessible to customers Sitecore's leading net content management, commerce, and marketing solutions via IBM iX designers, technology experts, and trade strategists in forty IBM Studios global.

IBM iX is a confirmed leader in providing Sitecore options, with greater than a decade's success of both companies working together in Europe to handle CMOs' crucial need for accelerated return on advertising and marketing investment. The extended partnership brings together the full breadth of IBM iX's capabilities to capitalize on the becoming demand for digital advertising capabilities that create enormously-personalized customer experiences throughout all digital touchpoints.

Matthew sweet, international leader, IBM iX, pointed out that "customer experience is the important thing strategic aim of many organizations and core to those groups' potential to radically change. i am very excited that we are expanding out our current relationship with Sitecore into a worldwide partnership, as they become a crucial player in our ecosystem of companions." 

As a worldwide Platinum associate in the Sitecore solution issuer program, IBM iX provides the world-category consulting, design, development and implementation functions required to deploy solutions on the Sitecore platform and deliver outstanding effects for clients. Matched to Sitecore's leading digital event administration capabilities, organisations can deliver end-purchasers with seamless, omnichannel experiences to drive differentiation, promote company transformation, and enhance earnings and client lifetime cost. The IBM iX and Sitecore partnership is extra empowered with most fulfilling practices and accelerators, as smartly as the potential to leverage the energy of IBM Cloud and IBM Watson know-how. IBM iX additionally brings to bear the unparalleled talents of Bluewolf, an IBM enterprise, developing experiences with Salesforce, with whom Sitecore has a strategic alliance.

"IBM iX gives the electricity, scale, and way of life of innovation required to bring immersive, conclusion-to-end digital solutions for our joint customers," spoke of Mark Zablan, Chief earnings Officer for Sitecore. "Our partnership makes a amazing mixture for companies who need to accelerate the digitization of their business and foster a consumer-centric approach to digital transformation."

For greater advice on IBM iX, talk over with  and comply with @IBM_iX on Twitter.

About SitecoreSitecore is the global leader in digital adventure administration utility that combines content management, commerce, and consumer insights. The Sitecore experience Cloud™ empowers entrepreneurs to deliver customized content material in precise time and at scale throughout each channel—earlier than, throughout, and after a sale. greater than 5,200 manufacturers––including American categorical, Carnival Cruise lines, Dow Chemical, and L'Oréal––have trusted Sitecore to bring the customized interactions that pride audiences, construct loyalty, and force income.  

ContactMatt KrebsbachSr. Director, Public & Analyst family members at

Sitecore Media RelationsWE

Sitecore®, personal the journey®, Sitecore adventure Cloud™, Sitecore xConnect™, Sitecore Cortex™, Sitecore® adventure Platform™, Sitecore journey supervisor™ and Sitecore® event Database™ are registered trademarks or trademarks of Sitecore agency A/S in the u . s . and different countries. All different brand names, product names or trademarks belong to their respective holders.

View common content to down load multimedia:

source Sitecore

Copyright (C) 2019 PR Newswire. All rights reserved

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IBM Optim Implementation for Distributed Systems (2009)

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EnergyAustralia and IBM Unite for Large-Scale Smart Grid Implementation | real questions and Pass4sure dumps



March 31, 2009 10:02 ET

SYDNEY, AUSTRALIA--(Marketwire - March 31, 2009) - EnergyAustralia, Australia's largest electricity distribution network, today announced an agreement with IBM (NYSE: IBM) for the implementation of an energy network monitoring and control solution.

A key project within EnergyAustralia's overall intelligent network program, the Distribution Monitoring and Control (DM&C) project involves the roll-out of 12,000 sensing devices throughout the electricity distribution network, creating a smart grid. The project will enable EnergyAustralia to deliver energy more efficiently and reliably, and allow a greater number and range of environmental solutions to be integrated into the electricity network such as renewable energy.

Under the agreement signed in the first quarter of this year, IBM will design and build the system IT architecture to support the project, in which sensing devices will connect with EnergyAustralia's operational systems using a combination of fourth generation and existing technologies. This world-class intelligent network will carry the necessary data for EnergyAustralia to reduce outages through faster fault location and preventative maintenance and, to work towards managing distributed energy sources such as solar and storage devices.

EnergyAustralia's Managing Director George Maltabarow said the project was an important part of the company's initial investment of $170 million in its smart network rollout.

"This project will help us stay at the forefront of the global intelligent network transformation," Mr. Maltabarow said. "It will give us an instant picture of the electricity network which will help shorten power interruptions by allowing us to quickly locate and repair faults.

"It will also mean preventative maintenance can be better targeted so we can avoid faults and outages in the first place."

In addition to consulting, systems integration and IT services expertise, IBM has invested heavily in solutions such as Tivoli Netcool and Websphere Datapower to assist utilities in realizing their intelligent network visions.

"IBM is delighted to bring its infrastructure, systems integration and project management expertise to bear on this ground-breaking transformation project," said David Murray, General Manager, IBM Communications Sector, Australia.

"Only through the creation of a smart grid that can sense, communicate, analyze and respond, can Australia build the energy infrastructure it needs to meet the challenges of climate change, globalization, and changing consumer demand."

IBM Smart Grid

IBM is working with clients in nearly 50 Smart Grid engagements across emerging and mature markets around the world. More about IBM's 'Smarter Planet' initiative: its vision to bring a new level of intelligence to how the world works -- how every person, business, organization, government, natural system, and man-made system interacts, can be found here:

EnergyAustralia Intelligent Networks

EnergyAustralia began its intelligent network program in 2006. It was the first utility in the world to build and operate a communications network using carrier grade Internet Protocol (IP) technology. EnergyAustralia has also rolled out 800 kilometres of fibre optic cable to its 200 major substations and depots, installed hundreds of communications switches, and built a trial telecommunications network to allow two-way communication across its electricity network. For more information see

A Short History of Performance Engineering | real questions and Pass4sure dumps

Performance engineering has a rather long and fascinating history, especially if considered in the context of changing computing paradigms. While not everything in the past may be applied to every new technology, the underlying principles often remain the same—and knowledge of history keeps us from reinventing the wheel when it is unnecessary. Unfortunately, statements referring to the past are not often completely correct. The history of performance engineering is not well-known, so here is some information that I find to be quite interesting. The approach was to find the first mature appearance of still-relevant performance concepts (without diving into the in-depth history of each notion). It is not scientific research, and not much information is available overall—so a lot of important information may still be missed.

We will start by listing the following computing paradigms:


Late ‘50s

Distributed Systems

Late ‘70s


Mid ‘90s

Mobile, Cloud

Mid 2000s

Performance expertise related to a paradigm usually materializes later when the technology is more mature.


Performance went beyond single-user profiling when mainframes started to support multiprogramming. In the early mainframe years, processing was concerned mainly with batch loads. Mainframes, however, had sophisticated scheduling and could ration consumed resources. They also had pretty powerful OS-level instrumentation allowing the engineers to track down performance issues. The cost of mainframe resources was high; therefore, capacity planners and performance analysts were needed to optimize mainframe usage.

While not everything in the past may be applied to every new technology, the underlying principles often remain the same—and knowledge of history keeps us from reinventing the wheel when it is unnecessary.

We can definitely say that performance engineering became a distinct discipline when instrumentation was introduced with SMF (System Management Facilities), released as part of OS/360 in 1966 (still in use in IBM z/OS mainframes today).

In 1968, Robert Miller (IBM) in his Response Time in Man-Computer Conversational Transactions paper described several threshold levels of human attention. The paper was widely cited by many later researchers and remains mostly relevant now.

In 1974, monitoring was introduced with RMF (Resource Measurement Facility) as part of MVS (still in use). OMEGAMON for MVS by Candle (acquired by IBM in 2004), released in 1975, is often claimed to be the first real-time monitor.

A performance community, the Computer Measurement Group (CMG), was created in 1974, holding annual conferences ever since—now across a wide spectrum of technologies.

In 1977, BEST/1 was released by BGS Systems (acquired by BMC in 1998), the first commercial package for computer performance analysis and capacity planning to be based on analytic models.

Distributed Systems

When the paradigm changed to client-server and distributed systems, the available operating systems at the time didn't have much instrumentation or workload management capabilities. Load testing and system-level monitoring became the primary ways to handle multi-user performance. Deploying across multiple machines was more difficult, and the cost of rollback was significant, especially for Commercial Off-The-Shelf (COTS) software that might be deployed by hundreds or even thousands of customers. Thus, there was more of a need for performance design to be correct from the beginning.

"Fix-it-later was a viable approach in the 1970s, but today, the original premises no longer hold - and fix-it-later is archaic and dangerous. The original premises were:

  • Performance problems are rare.

  • Hardware is fast and inexpensive.

  • It's too expensive to build responsive software.

  • You can tune software later, if necessary."

  • Have you heard something like this recently? That is a quote from Dr. Connie Smith's Performance Engineering of Software Systems, published in 1990. The book presented the foundations of software performance engineering, and already had 15 pages of bibliography on the subject.

    The most known load testing tool, LoadRunner, was released in 1991 by Mercury Interactive (acquired by HP in 2006, now part of Micro Focus). For a while, load testing became the main way to ensure high performance of distributed systems, and performance testing groups became the centers of performance-related activities in many organizations.

    "Fix-it-later was a viable approach in the 1970s, but today, the original premises no longer hold - and fix-it- later is archaic and dangerous."

    The term Application Performance Management (APM) was coined by Programart Corp. (acquired by Compuware in 1999) in 1992 (in the mainframe context, as a combination of their STROBE and APMpower tools). However, STROBE, which they refer to as an application performance measurement tool, had been on the market since the '70s. Still, there is an opinion that the first APM tool—as we know them now—was Introscope by Wily Technology, founded by Lew Cirne in 1998 (acquired by CA in 2006).

    The history of End-User Monitoring (EUM)/Real-User Monitoring (RUM) can be traced at least to ETEWatch (End-to-End Watch), an application response time monitor released in 1998 by Candle (acquired by IBM in 2004, then a part of Tivoli). However, EUM/RUM gained popularity later with development of web and mobile technologies.

    Web and Mobile

    Most existing expertise was still applicable to the back-end. The first books to apply existing knowledge and techniques to the web were published in 1998—for example, Web Performance Tuning and Capacity Planning for Web Performance.

    In 2007, Steve Souders published High Performance Web Sites: Essential Knowledge for Front-End Engineers, stating that 80-90% of user response time is spent in the browser, which started a movement of Web Performance Optimization (WPO) centered on the client-side.

    The WPO community was built around the Velocity Conference (first held in 2008) and Web Performance meetups. Velocity was a very popular performance conference—at least until Steve Souders stepped off as an organizer, O'Reilly merged Web Performance into the Fluent conference, and Velocity became more of a DevOps conference. Maybe it was an indication that WPO had become more mature and integrated with other aspects of technology.

    Mobile technologies supported the further development of web performance, as client-side performance was even more important on mobile devices.


    In the last ten years, we saw another paradigm shift to the cloud. While the term "cloud computing" was popularized when Amazon released its Elastic Compute Cloud in 2006, references to "cloud computing" have appeared as early as 1996. Technologies mature more quickly nowadays—for example, Amazon's own monitoring solution CloudWatch was released only three years later, in 2009. Of course, many established performance products started to support cloud, and new products still enter the market.

    While the cloud looks much different than mainframes, there are many similarities between them, especially from a performance point of view. They both provide:

  • Availability of computer resources to be allocated.

  • An easy way to evaluate the cost associated with these resources and implement chargeback.

  • Isolation of systems inside a larger pool of resources.

  • Easier ways to deploy a system and pull it back if needed without impacting other systems.

  • However, there are notable differences that make managing performance in the cloud more challenging. First of all, there is no instrumentation on the OS level, and even resource monitoring becomes less reliable due to the virtualization layer. So, instrumentation must be on the application level. Second, systems are not completely isolated from the performance point of view, and they could impact each other, and we mostly have multi-user interactive workloads, which are difficult to predict and manage. That means that such performance risk mitigation approaches like APM, performance testing, and capacity management become very important in a cloud environment.

    What Lies Ahead?

    While performance is the result of all design and implementation details, the performance engineering area remains very siloed—maybe due to historic reasons, maybe due to the huge scope of expertise. People and organizations trying to condense all performance-related activities together are rather few and far apart. Attempts to span different silos (for example, DevOps) often leave many important performance engineering areas out.

    Technologies mature more quickly nowadays—for example, Amazon's own monitoring solution CloudWatch was released only three years later, in 2009.

    The main lesson of the history is that the feeling that we are close to solving performance problems has existed for the last 50+ years, and it will probably stay with us for a while—so instead of hoping for a silver bullet, it is better to understand different existing approaches to mitigating performance risks and find an optimal combination of them to address performance risks in your particular context.

    This article is featured in the new DZone Guide to Performance: Testing and Tuning. Get your free copy for more insightful articles, industry statistics, and more! 

    A Sweet Introduction to R Programming | real questions and Pass4sure dumps

    R is a open source and very popular programming language and environment for statistical computer and graphics.R was designed by statisticians and was specialized for statistical computing, and thus is known as the lingua franca of statistics. It is mostly used in Data Science and Machine Learning. It is managed by R core development team — team of volunteer developer from across the globe. R provide a wide variety of statistical and graphical techniques and highly extensible.It was developed at Bell Laboratories by John Chambers and colleagues.R is a consolidated environment for performing statistical operation and generating R data analysis reports in graphical or text formats.

    History of R:

    R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and currently developed by the R Development Core Team. R is an implementation of the S programming Language and combines with lexical scoping semantics inspired by Scheme. John Chambers and colleagues developed S at Bell Laboratories. R was named partly after the first names of two R authors. The initial version of R is released in 1995 and a stable beta version released in 2000.

    Language Features:
  • R is a well defined and effective programming language which includes functions, loops, user defined function, input and output facilities and many more
  • R is both flexible and powerful.
  • R has effective data and storage facilities
  • R provides graphical facilities for data analysis
  • R is easy to learn and free to use as it is open sourced
  • R is interpreted language
  • R is Object-Oriented Programming Language
  • R supports matrix arithmetic.
  • R is case sensitive
  • R is widely use among mathematician and data miners for data analysis.
  • Alternatives of R:

    R is not only language in the domain of statistical computing and graphics. Some popular alternatives of R:


    Python is very powerful high level , object oriented language with very simple syntax.It is also extremely popular between data scientist and researcher. Most packages in R is equivalent to packages in Python.

    The choice between R vs Python also depends on what you are trying to accomplish with your code. If you are trying to analyze a data set and present the findings in a research paper, then R is probably a better choice. But if you are writing a data analysis program that runs in a distributed system and interacts with lots of other components, it would be preferable to work with Python.

    SAS (Statistical Analysis System)

    SAS (Statistical Analysis System) introduced the SAS Business Intelligence & Analytics Solution for large enterprises to explore their large data sets in a visually appealing format. SAS analytics is a data analytics tool that is used increasingly in Data Science, Machine learning, and Business Intelligence applications.It has been the first choice of many private enterprise for their analytics for a long time.

    Although SAS is extremely popular in commercial analysis, R and Python is gaining momentum in the enterprise space and companies are also trying to move towards open-source technologies.

    SPSS — Software package for statistical analysis

    SPSS is a popular statistical tool which is commonly used in the social sciences and is considered as easiest to learn among enterprise statistical software/tools.It is loved by non-statisticians because it is similar to excel. SPSS has the same downside as SAS — it is expensive. SPSS was acquired by IBM in 2009 for a reported $1.2 billion.

    Why should we adopt R Programming Language ?
  • R is open source. Therefore Google is using R Programming as it is suitable language. By using R we can create any form of statistics and data manipulation.
  • R programming language is best for statistical, data analysis and machine learning. By using this language we can create objects, functions, and packages. We can use it anywhere. It’s platform- independent, so it can be applied to all operating system. It’s free, so anyone can install it in any organization without purchasing a license.
  • R, SAS, and SPSS are three statistical languages. Of these three statistical languages, R is the only an open source.R Programming is extensible and hence, R groups are noted for its energetic contributions. Lots of Rs typical features can be written in R itself and hence, R has gotten faster over time and serves as a glue language.
  • As companies gather more and more data, the demand for data scientists are also greatly increasing. Demand for R developers will no doubt be on the rise.
  • Working with R scripts:

    R provides the freedom of selecting and editing tools to interact with the native console. While scripting in R, you don’t need to type commands but rather call functions to achieve results. The R Console allows command editing.The Prominent editors available for R programming language:

  • RGui (R graphical user Interface)
  • RStudio — It is an integrated development environment (IDE) for R language and offers a very rich environment for editing and creating R scripts than RGui.
  • R Scripting:

    R holds a reputation for getting things done with very little code.Let us start scripting in R with a very simple program called “Hello World”.

    #printing Hello Worldprint("Hello World !!")

    And the output is

    Let create a more complex script in R to generate 1000 number in a random distribution and arrange them based on their frequency and create a bar chart.

    n <- floor(rnorm(10000, 500, 100)) t <- table(n) barplot(t)

    And the output of this script :

    A Bar Plot

    NOTE: The extension of R scripts is .R .


    In a nutshell, R is easy to learn and use language. It is widely in practice and students and data scientists. With the data science predicted to grow immensely the importance of R is also undoubted. Hence learning R will the wisest decision you will make for launching your career in the big data space.

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    IBM 000-551 Exam (IBM Optim Implementation for Distributed Systems (2009)) Detailed Information


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