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C2090-623 IBM Cognos Analytics Administrator V11

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Test designation : IBM Cognos Analytics Administrator V11
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IBM IBM Cognos Analytics Administrator

IBM pushes automation, NLP in Cognos Analytics 11.1 update | existent Questions and Pass4sure dumps

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

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

the brand novel 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 do up, represents a "big funding," talked about Greg Adams, vice president of IBM industry Analytics, in an interview. the novel tools, past including extra superior capabilities, additionally construct the platform easier to construct employ of for nondata-oriented employees and matter information scientists -- a class of users that has been growing to breathe complete of a sudden.

Following a trend

the novel aspects in Cognos Analytics 11.1 construct "the platform a whole lot less complicated to construct employ of to generate insights, particularly the herbal language search, which allows users to accommodate 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 province of pastime chosen with the aid of a consumer, the employ 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 foster to breathe 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 straggle 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 travail 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 novel exploration tool. less demanding to construct employ of

in accordance with Adams, at IBM, "we breathe alert of to definitely serve americans locate insights, to basically breathe self-carrier faculty americans should breathe automatically given insights, automatically accommodate issues delivered to their consideration, and they should accommodate issues breathe truly approachable."

That strategy is reflected within the novel AI Assistant. Taking abilities of novel natural language processing (NLP) capabilities, the helper in Cognos Analytics 11.1 makes it feasible for clients to kind in questions and instructions, comparable to a command to breathe a section of facts units.

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

advanced analytics

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

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

looking at a inescapable visualization, as an instance, the platform will immediately learn linked visualizations that could breathe used, Adams referred to. When making a preference on statistics, the device will additionally supply ideas for visualizations.

With a novel 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 supplant 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 accommodate 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 commemorate AI bias.

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

Datawatch Monarch for IBM Watson Analytics and IBM Cognos Analytics Now available | existent Questions and Pass4sure dumps

conventional enterprise clients now empowered with self-carrier data guidance capabilities that pressure more advised, strategic industry 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. nascence today, those users can leverage Monarch to prep much less, resolve 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 industry clients to swiftly entry, exploit and merge statistics from practically any supply. information can then breathe 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 complete 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 unlucky truth given the affect these choices can accommodate on a company`s bottom line and growth expertise. Monarch makes it feasible for Watson Analytics and Cognos Analytics users to obtain not best the usurp counsel, but complete the tips, required to attain a holistic view of the enterprise, and then simply and hastily prepare it for analysis. in preference to expend hours on mundane prep work, users can now relegate their time to performing evaluation that hurries up preference 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 fiscal and operational performance management, to leverage a much broader variety of records, and gather sooner and greater accurate results. He`ll moreover panoply how an optimized statistics file will moreover breathe prepared for direct import into Watson Analytics and Cognos Analytics. Potter`s session will acquire location on Wednesday, may eleven, at 11 a.m. ET.

To study extra about Datawatch Monarch for Watson Analytics and Cognos Analytics, travel to:

About Datawatch CorporationDatawatch organization (NASDAQ-CM: DWCH) enables measure users to obtain magnificent outcomes with their information. simplest Datawatch can unlock facts from the widest diversity of sources and do together it for employ 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 resolve streaming records, even within the most traumatic environments, comparable to capital markets. corporations of complete sizes in additional than one hundred nations worldwide employ 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 information of greater about Datawatch or download a free edition of its industry application, gratify talk over with:

secure Harbor observation beneath the deepest Securities Litigation Reform Act of 1995Any statements contained in this press unlock that don't characterize historic facts might moreover represent forward-looking statements as that time term 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 district 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 comprise prerogative here: speedy technological exchange; Datawatch`s dependence on the introduction of novel items and product enhancements and feasible 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 disagree 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 benevolent 10-okay for the yr ended September 30, 2015. Any forward-looking statements should silent breathe 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. complete other names are emblems or registered trademarks of their respective groups.

Media Contact:Amanda BeaupreMarketing Communications manager, Datawatch 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 novel main update to Cognos Analytics | existent Questions and Pass4sure dumps

greater businesses are on a quest to employ ersatz intelligence as a aggressive knowledge. IBM is on a mission to construct this less complicated and greater purchasable for any arduous by the employ of the cloud. The industry has announced a brand novel 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 novel elements of this free up are a brand novel AI helper and sample detection capability. The AI helper enables clients to construct queries and then acquire results in herbal language. in line with IBM, this makes it less complicated to now not simplest survey for solutions, however understand the station they are available.

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

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

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

sensible exploration will aid users breathe 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 moreover insinuate essentially the most valuable visualization of effects through a multi-stage suggestion system.

The rig assembles novel 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 inescapable influence, judicious annotation, and herbal language generated insights of statistics.

“Analytics, facts science and industry intelligence, accommodate develop into table stakes in the industry world,” wrote Adams. “They’re section of the fundamental constructing blocks, or rungs within the Ladder to AI, as they focus on. And we’ve worked arduous to construct these subtle, advanced technologies handy to entry, easy to use, and straightforward to comprehend for almost any – complete by passage of the IBM Cloud. They believe businesses the world over will descry 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 cross Guys with Math: existent World Data Science employ 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: REGISTRATION:

    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 industry Analytics Office of the CTO. In his career at Cognos and IBM, he has architected and lead the evolution 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 moreover contributed to the Verizon Data trespass Investigation Report and ISSA Magazine on the employ 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, complete from the University of Toronto. He has held advisory positions on NSERC Strategic Networks and is involved in setting goals for NSERC Strategic Research award 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 employ and working in the existent world? Properly implemented, data science can breathe a highly effectual implement against APT, cyberattacks, and fortify an organization’s interior defense. Their 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 forestall cyberattacks. This seminar shall characterize the feature engineering, mathematical models, visualizations, evolution techniques and open source tools in existent world implementations developed over the past two years, illustrated through four real-world customer examples. The information and techniques will breathe presented with visualizations, existent (anonymized) data, and accessible descriptions of the mathematics, so that deep sustain 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 THEIR PATRONS for making this event possibleMarch Networks ( North BIA ( Ottawa ( tv ( & Biggar ( University, Faculty of Engineering and Design ( of Ottawa, Faculty of Engineering ( Marshes Golf Club (

    Regards,Eric Karmouch, Ph.D., SMIEEEChair, IEEE Ottawa Computer Society (, IEEE Ottawa Lunch and Learn (

    Predictive Analytics, Operational BI and Data Warehousing on the Mainframe: A Spotlight with Alan Meyer of IBM | existent questions and Pass4sure dumps

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

    Presented as mp;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 debate comprise industry analytics, federation and how mainframes can reduce cost and complexity and moreover deliver data safely and securely.

    Alan, one of the biggest trends they descry today is that enterprises are looking to reduce cost and complexity. Given that trend, is anyone buying mainframes today? If so, why would they expend complete 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 faculty to lower their overall cost, expand security, construct administration much easier and construct better employ 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 detail 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 reflect of the mainframe as a major expense. Does it moreover reduce complexity?Alan Meyer: That’s right, because you're now managing one system instead of hundreds of little systems spread across the data center. In addition, organizations are not only running both their OLTP and data warehouse on the very platform, they are moreover 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 industry analytics. A lot of people in an enterprise, as well as customers and suppliers, exigency access to the information in the data warehouse for analytics. How does System z serve construct that information available in a safe and secure way?Alan Meyer: Operational industry analytics are another reason people are returning to the mainframe. They're looking at how to construct employ of the information that's been locked away in the data warehouse. It's become the novel 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 information workers who employ the BI tools.  Organizations are asking how they can partake the insights with the other 92%, as well as their vendors and customers, to enable everyone to construct more effectual decisions at the prerogative time, in the prerogative context. These businesses are making insights available to the entire organization through their operational systems.  But this means the data warehouse needs the very operational characteristics.  For the very reason that organizations hasten 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 faculty to accurately identify each customer’s need, and meet that need, at the time of transaction, complete in a highly available and secure environment.

    That moreover coincides with what they are seeing for industry intelligence at the BeyeNETWORK that the next huge wave is to gain everyone in the enterprise over the next 2 to five years. Looking specifically at analytics and IBM's acquisition of Netezza, how accommodate you integrated DB2 and zSeries with Netezza and what benefits does that integration provide?Alan Meyer: In 2010 they 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 very time, they acquired Netezza, and they recognized that they had a technology that would allow us to attain 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 they 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 they accommodate done is taken the two technologies, each optimized for specific workloads, and blended them into the best of both worlds. This allows us to employ the Netezza hardware acceleration for knotty queries – plenary table scans, aggregations, and tasks of that nature – and DB2 for z/OS to effect the more traditional mixed workload where it excels. This enables their customers to capitalize complete the capabilities of Netezza while retaining complete the attributes of System z and DB2

    The DB2 Analytics Accelerator is transparent to the DB2 application or cease user; queries just hasten faster when it is present.  This is a plenary and taut integration from the standpoint that it utilizes the DB2 Optimizer to route queries to the most usurp technology, either to DB2 or to the DB2 Analytics Accelerator. The results are remarkable. We've seen their beta customers hasten queries against millions rows to billions of rows tables that used to acquire hours that are now running in seconds and sub-seconds. It's very encouraging. It’s probably one of their most exciting products in System z in recent times, and it's changing the passage 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 complete 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 tall hasten 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 well-known to customers?Alan Meyer: For some data warehouse applications, the data has often been moved to other platforms to provide higher hasten analysis. With the novel 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, do through a transformation and loaded into the data warehouse. That movement increases data latency. It moreover creates a lot of cost and overhead in touching that data around, opening the data to feasible intrusions. With System z, everything is kept on the very platform, and DB2 and SQL is used to straggle data and attain the transformations; the data never leaves the platform. This provides the faculty to lower data latency, reduce costs, and construct it a simpler overall environment.

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

    We are moreover discovering that customers accommodate many creative ways to profit from this technology. Beyond using IDAA for data warehousing and data marts, customers are actually seeing that their operational reporting can breathe accelerated. Today, we're seeing a lot of regulation that requires operational reporting to breathe far more knotty than it has been in the past. So here's a passage of being able to apply technology and substantially reduce the time that it takes to create these operational reports. It changes the passage people are looking at their overall enterprise architecture and changing some of the basic assumptions about where to hasten 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 accommodate to try to device which query to submit to the usurp technology and how to optimize that query for the technology. With this integration, it's not something that the cease user has to worry about. The optimizer within DB2 analyzes each query and determines the fastest and most cost effectual passage to execute each query.  There is no requirement for manual intervention of any kind.  Most organizations accommodate a database analyst who spends a magnificient deal of time looking at query plans for their warehousing systems, trying to device out whether to add an index to a table or rewrite the query. complete of this inspection and travail goes away. In the DB2 Analytics Accelerator there are no indexes to create or manage; it is complete done within the hardware acceleration of the Netezza technology.  The SQL is moved out to the hardware accelerator so the cease user and the database administrator don't accommodate to worry about it. You continue to employ the very applications, and they accommodate much faster query times.

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

    Another huge district of interest for their audience is data federation. What is your definition of data federation and what benevolent 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 straggle the data. It allows me to travel and find the records that I want and bring them into my environment, application or data warehouse without necessarily having to straggle 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 knotty interfaces, federation provides me a magnificient opportunity. I accommodate a simple DB2 SQL interface and access a wealth of different information, irrespective of where it is. Their federation product has interfaces to almost every different data type, and they employ 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. accommodate the SPSS capabilities been integrated into the mainframe environment?Alan Meyer: Absolutely. Today, they hasten SPSS on Linux on z, which is either SUSE or Red Hat, and they accommodate the plenary modeling and predictive analytics capabilities of SPSS. It allows us to breathe able to attain those predictive analytics in line, in the database, and they moreover are in the process of integrating that into their Cognos application so Cognos will breathe able to capitalize on SPSS algorithms at the time of reporting.

    Predictive analytics are becoming an even greater section of their customer’s information environment, and they are working on ways to construct them easier to implement and more robust in their faculty to find meaningful and actionable insights.

    Do you accommodate the latest growth statistics regarding mainframe adoption?Alan Meyer: We've certainly seen very stout growth in mainframe, and this is especially proper now that they announced the z196 final 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 accommodate complete of the attributes of a System z environment at an entry-level charge point. In the final quarter of 2010 they added 35 novel System z customers giving us an expand of 77 for the plenary year.  So as you can see, customers are recognizing the existent value in this growing platform.

    I really value you taking the time bringing us up to hasten 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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