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C2090-623 exam Dumps Source : IBM Cognos Analytics Administrator V11

Test Code : C2090-623
Test Name : IBM Cognos Analytics Administrator V11
Vendor Name : IBM
Q&A : 60 Real Questions

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IBM IBM Cognos Analytics Administrator

IBM pushes automation, NLP in Cognos Analytics 11.1 update | killexams.com Real Questions and Pass4sure dumps

IBM has delivered a host of AI-powered equipment to its BI platform, Cognos Analytics, to enable greater advanced analytics,...

whereas at the identical time making the platform less demanding for patrons to make use of, the enterprise said.

the brand new Cognos Analytics 11.1 platform elements encompass an AI assistant, sample detection, visualization recommendations, greater storytelling tools, and greater superior analytics and predictive analytics capabilities.

The update, revealed in a Sept. 27 IBM weblog put up, represents a "big funding," talked about Greg Adams, vice president of IBM business Analytics, in an interview. the new tools, past including extra superior capabilities, additionally make the platform easier to make use of for nondata-oriented employees and citizen information scientists -- a class of users that has been growing to be all of a sudden.

Following a trend

the new aspects in Cognos Analytics 11.1 make "the platform a whole lot less complicated to make use of to generate insights, particularly the herbal language search, which allows users to have precise conversations with the records," pointed out Wayne Eckerson, founder and fundamental advisor at Eckerson group.

IBM is [in the] middle of the pack, which is a tad unbelievable, given their Watson heritage. Wayne Eckerson, Eckerson group

"It automates records guidance and records modeling initiatives, so analysts can focal point greater on insights. It additionally auto-generates insights in keeping with a field of pastime chosen with the aid of a consumer, the use of algorithms to tease out key drivers of a metric, as an example," he persevered.

nonetheless, Eckerson noted, these are features that "the entire BI providers are racing to incorporate."

"Some are a bit bit forward of others, but most will come to be in the equal region in 18 months. IBM is [in the] middle of the pack, which is a tad astounding, given their Watson heritage," he observed.

previous this yr, BI software dealer Alteryx Inc. released Alteryx 2018.three, which brought superior visualization capabilities and set the stage for future updates which are pointed out to enhance the platform's augmented intelligence and smart capabilities.

Tableau additionally made a move so as to add more automation to its platforms this 12 months with the acquisition of MIT startup Empirical programs. The startup worked on a platform to immediately model facts for analysis, and it offers predictive insights into that facts -- aspects that Tableau cited it is going to work so as to add into its own platforms.

Cognos Analytics 11.1 Cognos Analytics 11.1 allows quick comparisons of two visualizations in a brand new exploration tool. less demanding to make use of

in accordance with Adams, at IBM, "we be aware of to definitely help americans locate insights, to basically be self-carrier ability americans should be automatically given insights, automatically have issues delivered to their consideration, and we should have issues be truly approachable."

That strategy is reflected within the new AI Assistant. Taking abilities of new natural language processing (NLP) capabilities, the assistant in Cognos Analytics 11.1 makes it possible for clients to type in questions and instructions, comparable to a command to be a part of facts units.

"the key with the dialog technology, it be no longer whatever thing that we wanted to bolt onto the side," Adams noted. "We basically tried to inject it, so or not it's part of your common circulate."

advanced analytics

the new AI technologies in Cognos Analytics eleven.1 work well with the newly added superior analytics equipment, Adams noted.

The platform now has sample detection, that could immediately discover and existing relationships in records that is being explored.

looking at a certain visualization, as an instance, the platform will immediately discover linked visualizations that could be used, Adams referred to. When making a choice on statistics, the device will additionally supply ideas for visualizations.

With a new exploration device in Cognos Analytics 11.1, clients can drag and drop two visualizations for a "quick aspect-by-facet comparison" if you want to instantly search for relationships, Adams pointed out.

The replace additionally contains greater predictive analytics capabilities; extra information storytelling options, with the skill to create interactive narratives with sequenced visualizations and media; and simpler-to-use reporting tools.

setting apart and looking forward

while Adams recounted other BI systems have currently integrated equivalent points, he claimed IBM's attention to statistics governance units Cognos Analytics eleven.1 aside.

"one of the vital exceptional issues about Cognos is its commercial enterprise-grade, trusted environment," he referred to, including that IBM has additionally brought a system to immediately observe AI bias.

in addition to the update, IBM has released a brand new subscription pricing model for the platform. The mannequin sets the platform into three tiers: lite, premium and commercial enterprise. The Cognos Analytics 11.1 replace is available for the maximum tier as of Sept. 28, and it'll be obtainable on the other tiers through the end of the yr, in accordance with IBM.


Datawatch Monarch for IBM Watson Analytics and IBM Cognos Analytics Now available | killexams.com Real Questions and Pass4sure dumps

conventional enterprise clients now empowered with self-carrier data guidance capabilities that pressure more advised, strategic business decisions

BEDFORD, Mass., may 10, 2016 (GLOBE NEWSWIRE) -- Datawatch supplier (NASDAQ-CM: DWCH) today introduced the immediate availability of Datawatch Monarch for IBM Watson Analytics and IBM Cognos Analytics. earlier this yr, Datawatch revealed that IBM (NYSE: IBM) would resell Datawatch Monarch to deliver enhanced and faster records access and self-carrier facts preparation (prep) to its clients. beginning today, those users can leverage Monarch to prep much less, analyze extra and harness the power of IBM`s cognitive computing capabilities across the widest variety of statistics sources.

data that gives essentially the most analytical value has historically been locked away in up to now inaccessible multi-structured and unstructured files, similar to text reports, net pages, PDFs, JSON and log files. And, in many situations, a company`s supply facts is distinctive and infrequently gifts itself in an analysis-equipped layout. consequently, hours are spent on manual facts retrieval and prep methods.

The Datawatch Monarch self-service facts prep solution allows records analysts and generic business clients to swiftly entry, manipulate and mix statistics from practically any supply. information can then be prepared for analysis in Watson Analytics and Cognos Analytics in a fraction of the time that it takes using spreadsheets and other manually-intensive measures.

"nearly all of strategic company selections are made on incomplete or old-fashioned counsel, due to records retrieval challenges and time-intensive manual prep strategies," said Michael Morrison, president and CEO of Datawatch. "here's an unfortunate truth given the affect these choices can have on a company`s bottom line and growth expertise. Monarch makes it possible for Watson Analytics and Cognos Analytics users to obtain not best the appropriate counsel, but all the tips, required to attain a holistic view of the enterprise, and then simply and hastily prepare it for analysis. in preference to spend hours on mundane prep work, users can now commit their time to performing evaluation that hurries up choice making and drives enterprise price."

IBM VisionDan Potter, Datawatch`s chief advertising officer, is scheduled to current on new advances in self-service data prep at the upcoming IBM imaginative and prescient conference in Orlando, Florida. Potter will focus on how self-service statistics prep permits clients, primarily these in financial and operational performance management, to leverage a much broader variety of records, and reap sooner and greater accurate results. He`ll also display how an optimized statistics file will also be prepared for direct import into Watson Analytics and Cognos Analytics. Potter`s session will take location on Wednesday, may eleven, at 11 a.m. ET.

To study extra about Datawatch Monarch for Watson Analytics and Cognos Analytics, go to: http://www.datawatch.com/ibm-analytics.

About Datawatch CorporationDatawatch organization (NASDAQ-CM: DWCH) enables standard users to obtain magnificent outcomes with their information. simplest Datawatch can unlock facts from the widest diversity of sources and put together it for use in visualization and analytics equipment, or for different company techniques. When true-time visibility into swiftly changing facts is vital, Datawatch additionally allows for clients to analyze streaming records, even within the most traumatic environments, comparable to capital markets. corporations of all sizes in additional than one hundred nations worldwide use Datawatch products, including ninety three of the Fortune one hundred. The company is headquartered in Bedford, Massachusetts, with workplaces in manhattan, London, Frankfurt, Stockholm, Singapore and Manila. To gain knowledge of greater about Datawatch or download a free edition of its business application, please talk over with: www.datawatch.com.

secure Harbor observation beneath the deepest Securities Litigation Reform Act of 1995Any statements contained in this press unlock that don't describe historic facts might also represent forward-looking statements as that time period is defined in the private Securities Litigation Reform Act of 1995. the sort of statements contained herein, including but now not constrained to those concerning product performance and viability, are in accordance with existing expectations, however are area to a few dangers and uncertainties that could cause specific outcomes to vary materially from expectations. The elements that might trigger precise future consequences to vary materially from present expectations include right here: speedy technological exchange; Datawatch`s dependence on the introduction of new items and product enhancements and possible delays in those introductions; acceptance of latest products by using the market, competitors within the software trade frequently, and in the markets for next era analytics in particular; and Datawatch`s dependence on its major products, proprietary software know-how and utility licensed from third parties. additional tips on factors that could cause specific consequences to differ from these anticipated is exact in various publicly-available files, which consist of, but are not confined to, filings made by using Datawatch sometimes with the Securities and trade commission, including but no longer restricted to, these acting within the company`s Annual file on kind 10-okay for the yr ended September 30, 2015. Any forward-looking statements should still be regarded in mild of those components.

Story continues

© 2016 Datawatch organization. Datawatch and the Datawatch emblem are logos or registered trademarks of Datawatch employer in the u.s. and/or other nations. All other names are emblems or registered trademarks of their respective groups.

Media Contact:Amanda BeaupreMarketing Communications manager, Datawatch Corporationamanda_beaupre@datawatch.com 978-275-8387Twitter: @datawatch 

This announcement is dispensed via NASDAQ OMX company options on behalf of NASDAQ OMX corporate solutions valued clientele.

The company of this announcement warrants that they're solely answerable for the content, accuracy and originality of the information contained therein.source: Datawatch organization via GlobeNewswireHUG#2011258


IBM integrates company intelligence and statistics science with new main update to Cognos Analytics | killexams.com Real Questions and Pass4sure dumps

greater businesses are on a quest to use artificial intelligence as a aggressive knowledge. IBM is on a mission to make this less complicated and greater purchasable for any firm by the use of the cloud. The business has announced a brand new version of its Cognos Analytics solution, which integrates company intelligence and facts science technologies into a suite of tools purchasable on IBM Cloud.

the key new elements of this free up are a brand new AI Assistant and sample detection capability. The AI Assistant enables clients to make queries and then acquire results in herbal language. in line with IBM, this makes it less complicated to now not simplest look for solutions, however understand the place they are available.

pattern detection identifies and gifts important relationships within information, pointing out patterns that may additionally now not had been considered in the past. through detecting patterns, the equipment can get rid of blind spots or guesswork in analysis, the enterprise defined.

“When mixed with the foundational governance and have faith capabilities developed into Cognos Analytics, which provide information coverage, relevancy, integrity and safety, AI Assistant and pattern detection will give users not best quick entry to insights, however added self belief in the effects,” Greg Adams, vice chairman of building for company analytics at IBM, wrote in a put up.

This version also provides storytelling, which allows clients to create interactive narratives by way of assembling visualizations into a chain and then bettering it with media, net pages, photographs, shapes, and check.

sensible exploration will aid users be in a position to greater remember what’s in the back of their results by using examining it with computer getting to know and pattern detection. The system will also suggest essentially the most valuable visualization of effects through a multi-stage suggestion system.

The equipment assembles new content material directly by means of re-the usage of vital components from present dashboards.

finally, it has advanced analytics that encompass predictive analytics, the means to identify information patterns and variables riding a certain influence, wise annotation, and herbal language generated insights of statistics.

“Analytics, facts science and business intelligence, have develop into table stakes in the business world,” wrote Adams. “They’re part of the fundamental constructing blocks, or rungs within the Ladder to AI, as we focus on. And we’ve worked hard to make these subtle, advanced technologies handy to entry, easy to use, and straightforward to comprehend for almost any – all by way of the IBM Cloud. We believe businesses the world over will see actual cost in it and start making even greater, extra strategic choices to propel their groups into the long run.”


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    SEMINAR: Catching Bad Guys with Math: Real World Data Science Use Cases for Cyberattack Detection and PreventionSPEAKER: Stephan Jou (CTO, Interset)

    DATE: March 7th, 2017TIME: Refreshments, Lunch, and Networking: 11:30 a.m.; Seminar: 12:00 p.m. – 01:30 p.m.PLACE: The Marshes Golf Club, 320 Terry Fox Drive, KanataPARKING: Free parking available.ADMISSION: Open to all, free of charge. Registration is required.EVENT SITE: http://ewh.ieee.org/r7/ottawa/lunchandlearn/EVENT REGISTRATION: https://www.eventbrite.ca/e/ieee-ottawa-lunch-and-learn-presents-catching-bad-guys-with-math-by-stephan-jou-cto-interset-tickets-32019829171

    SPEAKER BIOStephan Jou is CTO of Interset, a leading edge cybersecurity company that uses machine learning and behavioral analytics to provide unprecedented insight into how corporate intellectual property is being attacked, moved, shared and utilized. Jou was a Technical Architect, Research Staff Member and Sr. Manager at IBM’s Business Analytics Office of the CTO. In his career at Cognos and IBM, he has architected and lead the development of over ten 1.0 Cognos and IBM products in the areas of cloud computing, mobile, visualization, semantic search, data mining and neural networks. A frequent speaker, Stephan has also contributed to the Verizon Data Breach Investigation Report and ISSA Magazine on the use of data science in cybersecurity. Jou holds a M.Sc. in Computational Neuroscience and Biomedical Engineering, and a dual B.Sc. in Computer Science and Human Physiology, all from the University of Toronto. He has held advisory positions on NSERC Strategic Networks and is involved in setting goals for NSERC Strategic Research Grant research topics in the areas of analytics and security.

    TALK ABSTRACTThere is a lot of buzz about the potential of data science, machine learning and analytics in cyberattack and advanced persistent threat (APT) threat detection, but what are the techniques and tools in use and working in the real world? Properly implemented, data science can be a highly effective tool against APT, cyberattacks, and fortify an organization’s interior defense. Our distinguished speaker, Stephan Jou leads the technology and data science teams at Interset, a leading edge Ottawa company that has developed an award-winning solution, based on machine learning, to detect and prevent cyberattacks. This seminar shall describe the feature engineering, mathematical models, visualizations, development techniques and open source tools in real world implementations developed over the past two years, illustrated through four real-world customer examples. The information and techniques will be presented with visualizations, real (anonymized) data, and accessible descriptions of the mathematics, so that deep experience in statistics or mathematics is not required. Attendees will learn about how data science has been used to detect data theft from a manufacturing company, insider theft in a military defense contractor, system admin data loss in a life sciences company, and compromised account detection in a media company.

    THANK YOU TO OUR PATRONS for making this event possibleMarch Networks (https://www.marchnetworks.com/)Kanata North BIA (https://www.kanatanorthbia.ca/)Invest Ottawa (https://www.investottawa.ca/)you.i tv (http://www.youi.tv/)Smart & Biggar (http://www.smart-biggar.ca/en/index.cfm)Carleton University, Faculty of Engineering and Design (http://carleton.ca/engineering-design/)University of Ottawa, Faculty of Engineering (http://engineering.uottawa.ca/)The Marshes Golf Club (http://www.marshesgolfclub.com/index.php)

    Regards,Eric Karmouch, Ph.D., SMIEEEChair, IEEE Ottawa Computer Society (http://sites.ieee.org/ottawa-cs/)Chair, IEEE Ottawa Lunch and Learn (http://ewh.ieee.org/r7/ottawa/lunchandlearn/)


    Predictive Analytics, Operational BI and Data Warehousing on the Mainframe: A Spotlight Q&A with Alan Meyer of IBM | killexams.com real questions and Pass4sure dumps

    BeyeNETWORK Spotlights focus on news, events and products in the business intelligence ecosystem that are poised to have a significant impact on the industry as a whole; on the enterprises that rely on business intelligence, analytics, performance management, data warehousing and/or data governance products to understand and act on the vital information that can be gleaned from their data; or on the providers of these mission-critical products.

    Presented as Q&A-style articles, these interviews conducted by the BeyeNETWORK present the behind-the-scene view that you won’t read in press releases.

    This BeyeNETWORK Spotlight features Ron Powell's interview with Alan Meyer, Marketing Manager of Data Warehousing on System z, IBM Software Group. A few of the topics they discuss include business analytics, federation and how mainframes can reduce cost and complexity and also deliver data safely and securely.

    Alan, one of the biggest trends we see today is that enterprises are looking to reduce cost and complexity. Given that trend, is anyone buying mainframes today? If so, why would they spend all that money when there are less expensive options?

    Alan Meyer:

    When customers are looking at their environments today, they're looking at ways to reduce cost and simplify. This is driving the movement toward consolidation. It gives them the ability to lower their overall cost, increase security, make administration much easier and make better use of their resources. As far as costs are concerned, most customers are finding that the mainframes are actually cheaper. In fact, a study conducted by Dr. Howard Rubin, a consulting organization focusing on the economics of IT, has shown that customers who were mainframe-centric – that is, using the mainframe as their primary platforms – actually had anywhere from 25 to 34% lower IT cost per item produced than those who weren't. It's really a less expensive option. It's one of the reasons people are rediscovering the mainframe.

    That’s intriguing because most people think of the mainframe as a major expense. Does it also reduce complexity?Alan Meyer: That’s right, because you're now managing one system instead of hundreds of small systems spread across the data center. In addition, organizations are not only running both their OLTP and data warehouse on the same platform, they are also consolidating their data marts onto the platform.  This saves in hardware, software, floor space and administrative costs as well.

    Another major trend that continues to accelerate is operational BI and analytics. A trend where IBM has been one of the early pioneers is business analytics. A lot of people in an enterprise, as well as customers and suppliers, need access to the information in the data warehouse for analytics. How does System z help make that information available in a safe and secure way?Alan Meyer: Operational business analytics are another reason people are returning to the mainframe. They're looking at how to make use of the information that's been locked away in the data warehouse. It's become the new silo. In fact, Gartner states that only about 8.2% of an organization has access to the insights that are in the data warehouse. These are the knowledge workers who use the BI tools.  Organizations are asking how they can share the insights with the other 92%, as well as their vendors and customers, to enable everyone to make more effective decisions at the right time, in the right context. These businesses are making insights available to the entire organization through their operational systems.  But this means the data warehouse needs the same operational characteristics.  For the same reason that organizations run their operational systems on System z – availability, recoverability and security – they are now looking at bringing those attributes to the data warehouse.  These operational insights provide the ability to accurately identify each customer’s need, and meet that need, at the time of transaction, all in a highly available and secure environment.

    That also coincides with what we are seeing for business intelligence at the BeyeNETWORK that the next big wave is to reach everyone in the enterprise over the next 2 to five years. Looking specifically at analytics and IBM's acquisition of Netezza, how have you integrated DB2 and zSeries with Netezza and what benefits does that integration provide?Alan Meyer: In 2010 we came out with a product called the Smart Analytics Optimizer, which used in-memory database and columnar store technologies, and was tightly integrated with DB2. Around that same time, we acquired Netezza, and we recognized that we had a technology that would allow us to do hardware acceleration for particular kinds of queries.  We’ve realized that capitalizing on the Netezza technology offers even better performance, capacity and appliance characteristics, so we replaced the Smart Analytics Optimizer engine with Netezza technology but kept it fully integrated it into DB2 for z/OS. That marked the birth of IBM DB2 Analytics Accelerator (IDAA). What we have done is taken the two technologies, each optimized for specific workloads, and blended them into the best of both worlds. This allows us to use the Netezza hardware acceleration for complex queries – full table scans, aggregations, and tasks of that nature – and DB2 for z/OS to perform the more traditional mixed workload where it excels. This enables our customers to capitalize all the capabilities of Netezza while retaining all the attributes of System z and DB2

    The DB2 Analytics Accelerator is transparent to the DB2 application or end user; queries just run faster when it is present.  This is a full and tight integration from the standpoint that it utilizes the DB2 Optimizer to route queries to the most appropriate technology, either to DB2 or to the DB2 Analytics Accelerator. The results are remarkable. We've seen our beta customers run queries against millions rows to billions of rows tables that used to take hours that are now running in seconds and sub-seconds. It's very encouraging. It’s probably one of our most exciting products in System z in recent times, and it's changing the way people are looking at things.

    Many people today talk about appliances, but this offering truly meets the definition. Every customer that has installed has been running queries in less than two days after the box arrives. It runs DB2 queries, so it is simply a matter of installing the system and loading the data. The data retains its system-of-record in DB2 for z/OS and retains all of the security and operational attributes of DB2 data. There is a second copy of data maintained on the Accelerator that is synchronized with the DB2 data and the Accelerator uses this data for high speed analysis. The Accelerator is fully managed via DB2 stored procedures, making it a truly plug-and-play appliance.

    How does this change the dynamics of the architecture and why is that so important to customers?Alan Meyer: For some data warehouse applications, the data has often been moved to other platforms to provide higher speed analysis. With the new DB2 Analytics Accelerator that is no longer a requirement.  In fact, it provides a platform that enables organizations to blend both their operational data store (ODS) and their data warehouse. In a typical data warehouse environment, data is accumulated and taken off of the operational systems, put through a transformation and loaded into the data warehouse. That movement increases data latency. It also creates a lot of cost and overhead in moving that data around, opening the data to possible intrusions. With System z, everything is kept on the same platform, and DB2 and SQL is used to move data and do the transformations; the data never leaves the platform. This provides the ability to lower data latency, reduce costs, and make it a simpler overall environment.

    By leveraging the same database, managing the data is simple, and operational processes are already in place, which minimizes the effort to deploy. Since administration of the Netezza technology is done with stored procedures within DB2, they can be placed into standard automation procedures. Therefore, the DB2 Analytics Accelerator looks like a service within DB2 itself. It's completely transparent to end users. They continue to use their DB2 in their applications, and the only thing that's different from their perspective is things just happen a lot faster.

    We are also discovering that customers have many creative ways to benefit from this technology. Beyond using IDAA for data warehousing and data marts, customers are actually seeing that their operational reporting can be accelerated. Today, we're seeing a lot of regulation that requires operational reporting to be far more complex than it has been in the past. So here's a way of being able to apply technology and substantially reduce the time that it takes to create these operational reports. It changes the way people are looking at their overall enterprise architecture and changing some of the basic assumptions about where to run particular types of workloads.So the Accelerator makes that determination based upon the query, right?Alan Meyer: Exactly. If the two technologies were not tightly integrated then developers or users would have to try to figure which query to submit to the appropriate technology and how to optimize that query for the technology. With this integration, it's not something that the end user has to worry about. The optimizer within DB2 analyzes each query and determines the fastest and most cost effective way to execute each query.  There is no requirement for manual intervention of any kind.  Most organizations have a database analyst who spends a great deal of time looking at query plans for their warehousing systems, trying to figure out whether to add an index to a table or rewrite the query. All of this inspection and work goes away. In the DB2 Analytics Accelerator there are no indexes to create or manage; it is all done within the hardware acceleration of the Netezza technology.  The SQL is moved out to the hardware accelerator so the end user and the database administrator don't have to worry about it. You continue to use the same applications, and they have much faster query times.

    It gets back to reducing complexity for the enterprise.Alan Meyer: Absolutely.

    Another big area of interest for our audience is data federation. What is your definition of data federation and what kind of federation options does System z provide?Alan Meyer: Federation is a process of accessing data that's in a variety of different places without actually having to move the data. It allows me to go and find the records that I want and bring them into my environment, application or data warehouse without necessarily having to move that entire file. This is helpful when I don't own the data. For instance, if I'm going out to a remote service, capturing information on the Web, or perhaps going after legacy file systems or legacy databases that require a variety of complex interfaces, federation provides me a great opportunity. I have a simple DB2 SQL interface and access a wealth of different information, irrespective of where it is. Our federation product has interfaces to almost every different data type, and we use it ourselves.  Many IBM solutions leverage federation technology as their gateway into the disbursed and heterogeneous world including such products as DataStage, Optim and Event Publisher.

    In recent years, IBM has made other acquisitions in predictive analytics with Cognos and SPSS. Have the SPSS capabilities been integrated into the mainframe environment?Alan Meyer: Absolutely. Today, we run SPSS on Linux on z, which is either SUSE or Red Hat, and we have the full modeling and predictive analytics capabilities of SPSS. It allows us to be able to do those predictive analytics in line, in the database, and we also are in the process of integrating that into our Cognos application so Cognos will be able to capitalize on SPSS algorithms at the time of reporting.

    Predictive analytics are becoming an even greater part of our customer’s information environment, and we are working on ways to make them easier to implement and more robust in their ability to find meaningful and actionable insights.

    Do you have the latest growth statistics regarding mainframe adoption?Alan Meyer: We've certainly seen very strong growth in mainframe, and this is especially true now that we announced the z196 last year and the z114 this year. The z114 really changes the perspective of the cost of a mainframe. In fact, you can buy a starting z114 as inexpensively as $75,000 so it really changes the dynamics. It allows you to have all of the attributes of a System z environment at an entry-level price point. In the last quarter of 2010 we added 35 new System z customers giving us an increase of 77 for the full year.  So as you can see, customers are recognizing the real value in this growing platform.

    I really appreciate you taking the time bringing us up to speed on the DB2 Analytics Accelerator, what's happening with Netezza, and giving us some insight into the zSeries and mainframes.

    Recent articles by Ron Powell



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