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000-SS2 - IBM Systems Software Technical Sales Mastery V1 - Dump Information

Vendor : IBM
Exam Code : 000-SS2
Exam Name : IBM Systems Software Technical Sales Mastery V1
Questions and Answers : 32 Q & A
Updated On : February 22, 2019
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000-SS2 Questions and Answers

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000-SS2 IBM Systems Software Technical Sales Mastery V1

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000-SS2 exam Dumps Source : IBM Systems Software Technical Sales Mastery V1

Test Code : 000-SS2
Test Name : IBM Systems Software Technical Sales Mastery V1
Vendor Name : IBM
Q&A : 32 Real Questions

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IBM IBM Systems Software Technical

IBM (IBM) Down 10.three% considering remaining income document: Can It Rebound? | killexams.com Real Questions and Pass4sure dumps

A month has passed by in view that the last earnings document for IBM (IBM). Shares have lost about 10.3% in that point frame, underperforming the S&P 500.

Will the recent bad fashion proceed leading as much as its next profits free up, or is IBM due for a breakout? earlier than we dive into how traders and analysts have reacted as of late, let's take a quick appear on the most fresh earnings record in order to get a higher address on the vital catalysts.

IBM’s Q2 results advantage from cost slicing, lessen Share count number

IBM mentioned third-quarter 2018 non-GAAP revenue of $three.forty two per share, which beat the Zacks Consensus Estimate by way of couple of cents. income per share (EPS) expanded four.9% from the 12 months-ago quarter.

The 12 months-over-year growth in EPS can also be attributed to solid pre-tax margin operating leverage (28 cents contribution) and aggressive share buybacks (19 cents contribution). This became in part offset by means of lower revenues (seven cents poor influence) and higher tax price (17 cents bad have an effect on).

Revenues of $18.76 billion lagged the Zacks Consensus Estimate of $19.10 billion and declined 2.1% on a year-over-yr foundation. At constant forex (cc), revenues remained flat.

IBM stated that signings plunged 21% to $8 billion. functions backlog declined 3% from the yr-in the past quarter to $113 billion.

Geographic revenue details

Revenues from Americas inched up 1%, driven with the aid of persisted boom in Canada and Latin america and modest increase in the united states.

Europe, center-East and Africa diminished 2% from the yr-ago quarter, pushed by using decline in Germany and France, in part offset by using growth in Spain and the United Kingdom.

Asia-Pacific revenues declined 1% on a 12 months-over-yr groundwork with modest increase in Japan.

Strategic Imperatives growth Continues

Strategic Imperatives (cloud, analytics, mobility and security) grew 7% at cc from the year-in the past quarter to $9.3 billion. safety revenues surged 34%. On a trailing 12-month basis, Strategic Imperatives revenues had been $39.5 billion, up 13% (eleven% at cc).

Cloud revenues surged 13% from the yr-ago quarter to $4.6 billion. The annual run cost for cloud as-a-provider revenues improved 24% at cc on a year-over-12 months foundation to $11.four billion.

Cloud revenues of $19 billion on a trailing 12-month groundwork multiplied 20% (18% at cc) and now debts for 24% of IBM’s total revenues.

Cognitive Revenues Decline

Cognitive solutions’ revenues-exterior lowered 5.7% year over 12 months (down 5% at cc) to $four.15 billion. Segmental revenues referring to Strategic Imperatives and Cloud declined 4% and a couple of%, respectively. Cloud as-a-service salary annual run expense become $2 billion.

options software includes choices in strategic verticals like health, domain-certain capabilities like analytics and protection, and IBM’s emerging applied sciences of AI and blockchain. The section also includes offerings that tackle horizontal domains like collaboration, commerce and skill. solutions utility revenues reduced three% yr over yr within the quarter.

IBM stated that in commerce area the infusion of AI into choices like client experience analytics helped SaaS signings to develop double digit in the quarter. The fresh launch of Notes Domino edition 10, which is optimized for mobile, and helps JavaScript and node.js will increase boom collaboration in 2019.

Transaction Processing software contains utility that runs mission-crucial workloads, leveraging IBM’s hardware platforms. Revenues fell 8% on a yr-over-year foundation.

IBM witnessed increase in trade verticals like fitness, key areas of analytics and security in the quarter. Watson health witnessed large-based mostly boom in Payer, company, Imaging and lifestyles Sciences domains.

all over the quarter, the Sugar.IQ application, developed by means of Medtronic in partnership with IBM, hit the market. The utility is designed to simplify and enhance day by day diabetes administration.

IBM pointed out that analytics carried out smartly within the quarter, pushed through facts science offerings and IBM Cloud inner most for records offering.

during the quarter, the enterprise introduced bias detection services and launched new Watson functions on the IBM Cloud deepest platform.

security boom was pushed through offerings in orchestration, records safety and endpoint management.

In blockchain, IBM meals believe community for meals safety went are living within the quarter. Reatiler Carrefour joined IBM’s blockchain network. The company also collectively introduced TradeLens with Maersk that addresses inefficiencies in the world deliver chain. IBM at present supports seventy five active blockchain networks.

international company functions Revenues boost

Revenues from global company services-external section have been $four.13 billion, up 0.9% from the yr-in the past quarter (up 3% at cc). Segmental revenues touching on Strategic Imperatives grew 9%. Cloud observe surged 18%. Cloud as-a-provider profits annual run fee turned into $1.9 billion.

utility management revenues declined 1% from the 12 months-in the past quarter. youngsters, global process services revenues climbed 2%. moreover, Consulting revenues improved 7% year over yr, driven via potent efficiency from IBM’s digital enterprise.

expertise capabilities & Cloud structures: Revenues Dip

Revenues from know-how features & Cloud platforms-external lowered 2% from the yr-in the past quarter (flat at cc) to $eight.29 billion. Segmental revenues bearing on Strategic Imperatives advanced 16%, pushed by way of hybrid cloud features. Cloud surged 22% from the year-in the past quarter. Cloud as-a-service income annual run fee changed into $7.5 billion.

Integration software extended 1% from the year-in the past quarter. all over the quarter, ninety five companies around the globe chosen IBM Cloud deepest offering. Infrastructure functions revenues additionally elevated 1% on a year-over-year foundation.

however, Technical guide services revenues reduced three% from the 12 months-ago quarter.

vigor & z14 drive systems Revenues

systems revenues accelerated 0.9% on a 12 months-over-yr basis (up 2% at cc) to $1.74 billion. Segmental revenues referring to Strategic Imperatives surged 5%, while Cloud revenues declined 8%.

IBM Z revenues improved 6% yr over 12 months on more than 20% MIPS boom, pushed by way of vast-primarily based adoption of the z14 mainframe.

power revenues improved 17% from the yr-ago quarter. right through the quarter, IBM launched its subsequent era POWER9 processors for midrange and high-end programs which are designed for coping with advanced analytics, cloud environments and records-intensive workloads in AI, HANA, and UNIX markets.

IBM also introduced new offerings optimizing each hardware and software for AI. management believes that items like PowerAI vision and PowerAI commercial enterprise will help drive new client adoption.

although, storage hardware revenues declined 6% as a result of weak performance in the midrange and high conclusion, partly offset with the aid of amazing boom in All Flash Arrays. IBM mentioned that pricing force within the immensely aggressive storage market is hurting revenues. The enterprise introduced its new FlashSystems with subsequent generation NVMe know-how right through the quarter.

working techniques utility revenues declined four%, whereas systems Hardware advanced 4% from the yr-ago quarter.

eventually, global Financing (includes financing and used device earnings) revenues reduced 9.1% at cc to $388 million.

working particulars

Non-GAAP gross margin remained unchanged from the year-ago quarter at forty seven.4%. This was IBM’s most fulfilling gross margin efficiency in years and was essentially pushed by way of a hundred and sixty foundation points (bps) expansion in features margin. although, negative combine in z14 mainframe and utility wholly offset this growth.

working fee declined four% 12 months over year, as a result of recognition of acquisition synergies and improving operational efficiencies. IBM continues to put money into speedy growing fields like hybrid cloud, artificial intelligence (AI), security and blockchain.

Pre-tax margin from carrying on with operations improved 50 bps on a year-over-yr basis to 19.2%.

Cognitive options and global enterprise services segment pre-tax margins increased one hundred ninety bps and 320 bps, respectively, on a year-over-yr groundwork. youngsters, know-how capabilities & Cloud structures segment pre-tax margin gotten smaller one hundred bps.

techniques pre-tax income become $209 million down 38% year over 12 months. world Financing segment pre-tax salary jumped 26.7% to $308 million.

steadiness Sheet & money movement details

IBM ended third-quarter 2018 with $14.70 billion in total money and marketable securities in comparison with $11.93 billion on the conclusion of 2nd-quarter 2018. total debt (including global financing) became $46.9 billion, up $1.4 million from the outdated quarter.

IBM stated cash circulate from operations (apart from global Financing receivables) of $3.1 billion and generated free money stream of $2.2 billion within the quarter.

in the pronounced quarter, the business back $2.1 billion to shareholders via dividends and share repurchases. on the conclusion of the quarter, the business had $1.4 billion remaining below current buyback authorization.

suggestions

IBM reiterated EPS forecast for 2018. Non-GAAP EPS is expected to be at least $13.eighty.

IBM still anticipates 2018 free cash move of $12 billion.

Story continues

How Have Estimates Been moving considering that Then?

in the past month, investors have witnessed a downward fashion in sparkling estimates.

VGM ratings

at the present, IBM has a typical growth ranking of C, notwithstanding it's lagging slightly on the Momentum rating front with a D. youngsters, the stock became allotted a grade of A on the value side, inserting it in the right quintile for this funding strategy.

basic, the stock has an aggregate VGM rating of B. in case you aren't focused on one strategy, this score is the one you should be attracted to.

Outlook

Estimates had been broadly trending downward for the stock, and the magnitude of those revisions shows a downward shift. especially, IBM has a Zacks Rank #3 (hang). We expect an in-line return from the stock within the following few months.

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IBM Db2 query Optimization the usage of AI | killexams.com Real Questions and Pass4sure dumps

In September 2018, IBM announced a brand new product, IBM Db2 AI for z/OS. This synthetic intelligence engine displays information entry patterns from executing SQL statements, uses computing device gaining knowledge of algorithms to decide upon top of the line patterns and passes this assistance to the Db2 query optimizer to be used via subsequent statements.

machine learning on the IBM z Platform

In might also of 2018, IBM announced edition 1.2 of its machine learning for z/OS (MLz) product. here is a hybrid zServer and cloud utility suite that ingests performance information, analyzes and builds models that signify the health status of numerous indicators, screens them over time and offers real-time scoring capabilities.

a few facets of this product offering are geared toward supporting a community of mannequin builders and bosses. as an instance:

  • It supports varied programming languages comparable to Python, Scala and R. This permits facts modelers and scientists to make use of a language with which they are conventional;
  • A graphical user interface known as the visual model Builder publications model developers with out requiring totally-technical programming competencies;
  • It comprises distinct dashboards for monitoring mannequin effects and scoring functions, as well as controlling the system configuration.
  • This computing device researching suite changed into at the start geared toward zServer-based analytics functions. some of the first evident decisions turned into zSystem efficiency monitoring and tuning. system administration Facility (SMF) statistics which are automatically generated through the operating equipment deliver the uncooked data for equipment resource consumption similar to valuable processor usage, I/O processing, reminiscence paging and so on. IBM MLz can collect and save these statistics over time, and build and instruct models of device conduct, ranking those behaviors, determine patterns not effortlessly foreseen through humans, increase key efficiency symptoms (KPIs) and then feed the model outcomes returned into the device to have an effect on device configuration alterations that can improve performance.

    The subsequent step turned into to implement this suite to analyze Db2 efficiency records. One answer, known as the IBM Db2 IT Operational Analytics (Db2 ITOA) answer template, applies the machine gaining knowledge of expertise to Db2 operational information to profit an understanding of Db2 subsystem fitness. it may possibly dynamically construct baselines for key performance warning signs, give a dashboard of these KPIs and give operational group of workers actual-time insight into Db2 operations.

    while standard Db2 subsystem efficiency is a crucial component in average software fitness and performance, IBM estimates that the DBA help body of workers spends 25% or extra of its time, " ... fighting access path complications which trigger performance degradation and repair have an impact on.". (See Reference 1).

    AI involves Db2

    consider the plight of up to date DBAs in a Db2 atmosphere. In state-of-the-art IT world they have to guide one or extra huge data functions, cloud software and database services, software installation and configuration, Db2 subsystem and utility performance tuning, database definition and administration, disaster healing planning, and extra. query tuning has been in existence given that the origins of the database, and DBAs are usually tasked with this as well.

    The heart of question path analysis in Db2 is the Optimizer. It accepts SQL statements from applications, verifies authority to entry the facts, studies the places of the objects to be accessed and develops an inventory of candidate statistics entry paths. These access paths can consist of indexes, table scans, a considerable number of desk join methods and others. within the records warehouse and large statistics environments there are constantly further selections available. One of those is the existence of abstract tables (from time to time referred to as materialized query tables) that comprise pre-summarized or aggregated facts, as a result enabling Db2 to stay away from re-aggregation processing. an extra alternative is the starjoin entry direction, normal in the statistics warehouse, where the order of desk joins is modified for performance factors.

    The Optimizer then reviews the candidate access paths and chooses the access route, "with the bottom can charge." can charge in this context skill a weighted summation of resource utilization together with CPU, I/O, reminiscence and other components. finally, the Optimizer takes the lowest can charge entry route, retailers it in reminiscence (and, optionally, in the Db2 directory) and starts off access course execution.

    large facts and facts warehouse operations now include application suites that allow the company analyst to use a graphical interface to build and manipulate a miniature information model of the facts they want to analyze. The programs then generate SQL statements in accordance with the users’ requests.

    The difficulty for the DBA

    with the intention to do good analytics in your varied facts shops you want a very good figuring out of the statistics requirements, an realizing of the analytical services and algorithms accessible and a excessive-performance information infrastructure. unfortunately, the number and placement of facts sources is increasing (both in dimension and in geography), facts sizes are transforming into, and purposes proceed to proliferate in quantity and complexity. How should IT managers guide this ambiance, in particular with the most experienced and mature team of workers nearing retirement?

    remember also that a large a part of decreasing the overall cost of ownership of these programs is to get Db2 purposes to run sooner and extra effectively. This usually translates into using fewer CPU cycles, doing fewer I/Os and transporting much less facts across the network. considering that it is commonly complicated to even identify which applications may improvement from efficiency tuning, one strategy is to automate the detection and correction of tuning concerns. this is the place desktop researching and synthetic intelligence can be used to top notch effect.

    Db2 12 for z/OS and artificial Intelligence

    Db2 version 12 on z/OS uses the laptop getting to know facilities outlined above to collect and keep SQL query textual content and access course particulars, as well as specific performance-linked ancient counsel comparable to CPU time used, elapsed instances and outcome set sizes. This providing, described as Db2 AI for z/OS, analyzes and stores the records in desktop gaining knowledge of fashions, with the mannequin evaluation results then being scored and made obtainable to the Db2 Optimizer. The subsequent time a scored SQL commentary is encountered, the Optimizer can then use the mannequin scoring facts as enter to its access path option algorithm.

    The effect should be a discount in CPU consumption because the Optimizer uses mannequin scoring enter to choose better access paths. This then lowers CPU charges and speeds application response instances. a big advantage is that the use of AI application doesn't require the DBA to have statistics science abilities or deep insights into query tuning methodologies. The Optimizer now chooses the most advantageous entry paths primarily based now not only on SQL query syntax and facts distribution statistics however on modelled and scored historical efficiency.

    This can also be especially essential in case you store data in distinctive areas. for instance, many analytical queries in opposition t massive facts require concurrent access to certain data warehouse tables. These tables are frequently called dimension tables, and they include the statistics elements always used to control subsetting and aggregation. as an instance, in a retail ambiance believe a desk referred to as StoreLocation that enumerates every keep and its place code. Queries against save revenue information may additionally need to combination or summarize income by place; therefore, the StoreLocation desk should be used by some big statistics queries. in this ambiance it's normal to take the dimension tables and replica them consistently to the big information application. in the IBM world this vicinity is the IBM Db2 Analytics Accelerator (IDAA).

    Now feel about SQL queries from each operational functions, facts warehouse clients and big information company analysts. From Db2's viewpoint, all these queries are equal, and are forwarded to the Optimizer. youngsters, within the case of operational queries and warehouse queries they may still absolutely be directed to access the StoreLocation table in the warehouse. however, the query from the enterprise analyst towards huge records tables should still doubtless access the replica of the table there. This results in a proliferations of abilities entry paths, and more work for the Optimizer. fortunately, Db2 AI for z/OS can provide the Optimizer the assistance it should make wise entry course choices.

    how it Works

    The sequence of pursuits in Db2 AI for z/OS (See Reference 2) is frequently right here:

  • right through a bind, rebind, put together or clarify operation, an SQL statement is handed to the Optimizer;
  • The Optimizer chooses the data access path; because the option is made, Db2 AI captures the SQL syntax, access course option and question efficiency information (CPU used, and many others.) and passes it to a "gaining knowledge of assignment";
  • The researching task, which may also be executed on a zIIP processor (a non-popular-purpose CPU core that doesn't factor into software licensing costs), interfaces with the desktop discovering software (MLz model functions) to store this information in a mannequin;
  • as the volume of information in each mannequin grows, the MLz Scoring service (which can also be carried out on a zIIP processor) analyzes the mannequin statistics and scores the behavior;
  • all through the next bind, rebind, put together or clarify, the Optimizer now has entry to the scoring for SQL models, and makes acceptable alterations to access path decisions.
  • There are additionally a number of person interfaces that give the administrator visibility to the reputation of the collected SQL remark performance information and model scoring.

    summary

    IBM's computing device researching for zOS (MLz) offering is getting used to excellent impact in Db2 edition 12 to increase the efficiency of analytical queries as well as operational queries and their associated purposes. This requires administration attention, as you need to assess that your company is ready to eat these ML and AI conclusions. How will you measure the expenses and benefits of the usage of computer getting to know? Which IT assist workforce ought to be tasked to reviewing the result of model scoring, and perhaps approving (or overriding) the outcomes? How will you review and justify the assumptions that the application makes about access route decisions?

    In other words, how smartly do you know your facts, its distribution, its integrity and your latest and proposed access paths? this could investigate where the DBAs spend their time in aiding analytics and operational utility efficiency.

    # # #

    Reference 1

    John Campbell, IBM Db2 extraordinary EngineerFrom "IBM Db2 AI for z/OS: increase IBM Db2 utility efficiency with computer learning"https://www.worldofdb2.com/activities/ibm-db2-ai-for-z-os-raise-ibm-db2-application-performance-with-ma

    Reference 2

    Db2 AI for z/OShttps://www.ibm.com/support/knowledgecenter/en/SSGKMA_1.1.0/src/ai/ai_home.html


    Settling In With IBM i For The lengthy Haul | killexams.com Real Questions and Pass4sure dumps

    February 11, 2019 Timothy Prickett Morgan

    If nothing else, the IBM i platform has exhibited spectacular toughness. One might even say legendary longevity, in case you want to take its heritage the entire means lower back to the device/3 minicomputer from 1969. this is the true starting aspect in the AS/four hundred family tree and here's when big Blue, for terribly sound criminal and technical and marketing explanations, decided to fork its items to handle the unique needs of large enterprises (with the gadget/360 mainframe and its comply with-ons) and small and medium corporations (beginning with the system/3 and relocating on throughout the device/34, system/32, system/38, and equipment/36 within the Nineteen Seventies and early 1980s and passing in the course of the AS/400, AS/400e, iSeries, gadget i, and then IBM i on power systems platforms.

    It has been an extended run certainly, and many purchasers who have invested within the platform started means again then and there with the early types of RPG and moved their purposes forward and altered them as their organizations advanced and the depth and breadth of corporate computing modified, relocating on up via RPG II, RPG III, RPG IV, ILE RPG, and now RPG free form. Being on this platform for even three decades makes you a relative newcomer.

    there is a longer run forward, on the grounds that we believe that the agencies that are still working IBM i programs are the real diehards, those who haven't any intention of leaving the platform and that, at the least based on the survey data we now have been privy too, are meaning to continue investing in, and even extend their investments in, the IBM i platform.

    thus far, we aren't in a recession and heaven inclined there will not be one, so the priorities that IBM i shops have don't seem to be those that they had a decade in the past throughout the height of the exceptional Recession. lower back then, as changed into the case in pretty much all IT businesses, IBM i stores have been hunkering down and had been making an attempt to cut expenses in all approaches possible, including deferring device enhancements and migrations as well as reducing returned on other initiatives. simplest 29 p.c of the 750 IBM i retail outlets that participated in the 2019 IBM i industry Survey, which HelpSystems did again in October 2018, have been concerned about decreasing IT spending. here's a remarkably low level, and that i feel is indicative of how rather effective the economic system is – excepting one of the vital fits and begins we noticed at the conclusion of 2018 and right here in early 2019 that make us frightened and will beginning putting force on issues. listed below are the correct issues as culled from the survey:

    dealing with the increase in statistics and in identifying the analytics to chew on that data ranked a little bit higher on the 2019 IBM i marketplace Survey than did decreasing costs, and that i suppose over the long haul these issues will become extra essential than modernizing applications and dealing with the IBM i skills shortages which are a perennial be concerned. each of these concerns are being solved as new programmers and new equipment to make new interfaces to database functions have become extra normal and as technologies reminiscent of free kind RPG, which looks more like Java, Python, and php, are being extra largely deployed and, importantly, can also be picked up more right now by using programmers skilled with these different languages.

    Given the character of the client base, it looks not going to me that security and high availability will now not proceed to be fundamental issues, despite the fact that the IBM i platform is among the most comfortable platforms on this planet (and never just since it is vague, however since it is exceedingly intricate to hack) and it has more than a few excessive availability and disaster recovery tools (from IBM, Syncsort, Maxava, and HelpSystems) purchasable for those that are looking to double up their programs and protect their applications and facts. The bar is regularly bigger than fundamental backup and restoration for a lot of IBM i stores within the banking, assurance, manufacturing, and distribution industries that dominate the platform. These organizations can’t have protection breaches, and that they can’t have downtime.

    there's a astonishing amount of steadiness within the IBM i customer base that we consider, at this point, is reflective in the steadiness of the IBM i platform and large Blue’s own perception that it wants a healthy IBM i platform to have an basic in shape vigour methods company. all of us recognize that the vigour programs hardware enterprise has simply became in five quarters of earnings increase – whatever we discussed currently in establishing our own profits model for the vigor systems business – but what we did not be aware of, and what make sure you understand, is that in the 2nd and third quarters of 2018, the IBM i portion of the business grew vastly faster than the ordinary vigour programs enterprise, and the handiest cause that this did not occur in the final quarter of 2018 is that sales of IBM i machinery in this autumn 2017 turned into quite effective and represented a extremely hard examine. The aspect is, the IBM i business has been elevating the vigour techniques class common. (These guidelines about the IBM i company come compliments of Steve Sibley, vp and providing supervisor of Cognitive programs at IBM.)

    IBM’s own economic stability of the energy platform – which has been bolstered with the aid of a movement into Linux clusters for analytics and high performance computing simulation and modeling as well as via the adoption of the HANA in-memory database by means of SAP purchasers on massive iron machines including Power8 and now Power9 systems – helps IBM i clients believe extra confident in investing within the current IBM i platform. The contemporary evidence from a number of different surveys, not simply the one achieved by using HelpSystems each year, means that agencies are with the aid of and massive either continuing to make investments in the platform or even in some circumstances are planning to raise their spending on the IBM i platform in 2019.

    As you could see, the sample of funding plans for the IBM i platform, as proven in the chart above, has not modified very a whole lot at all during the past 4 years. it's a remarkably stable pattern with however a little wiggling here and there that can also no longer even be statistically big. simply beneath a quarter of IBM i stores have suggested during the past four years that they plan to raise their funding in the platform in each yr, and just beneath half say that they're maintaining regular. This doesn't imply that the identical businesses, yr after year, are investing extra and different groups are staying pat, year after 12 months. it's way more possible that every handful of years – extra like 4 or five – shoppers improve their systems and expand their ability, and they then sit down tight. The ask yourself is that the cut up isn’t showing a ways fewer corporations investing and far greater sitting tight. That more than a tenth of the retail outlets don’t know what their plan is as each and every prior 12 months comes to a close is a bit of demanding, however it is sincere and indicates that a good portion of shops produce other priorities other than hardware and operating system enhancements. we have noted this before and we are able to say it once again: We think that the americans who reply to surveys and browse weekly publications concentrated on the IBM i platform are the most active stores – those extra prone to live particularly latest on hardware and utility. So the pace of adoption for new technologies, and the fee of investment, may still be larger than within the genuine base, a great deal of which doesn't exchange much in any respect.

    So if we had to regulate this records to take on the complete base, there might possibly be far fewer websites that are investing extra funds, much more organizations that are sitting tight, and perhaps fewer sites which are taking into consideration relocating off the IBM i platform. I feel the distribution of statistics is doubtless some thing like 10 % of retailers don't have any concept what they're doing investment sensible with IBM this yr, 5 percent are pondering moving some or all of their purposes to one more platform, perhaps 10 percent are investing more this year, and the final 75 % are sitting tight. this is only a guess, of route. so far as we are able to tell, the cost of attrition – what number of websites we in fact lose every 12 months – just a tad over 1 percent. So the cost of move of functions off the platform, or incidences of unplugging IBM i databases and purposes, may no longer be anywhere close as excessive in the usual base because the data above suggests. what's alarming, most likely, is that the cost of moving some or all functions off the platform is balanced in opposition t people who say they're going to enhance investments. perhaps these are hopeful survey takers, and people who consider it's handy to circulate locate it is not and those that feel they're going to find the cash to invest will not.

    What we do understand is that if the cost of application attrition changed into anyplace close as high as these surveys imply, then the IBM i company would not be turning out to be, however shrinking. And we are aware of it is not shrinking, so we think there is a disconnect between planning and reality, both on the upside and the draw back.

    if you drill down into the facts for the 2019 IBM i market Survey, there have been 13 % of outlets that noted they might be relocating some functions to a new platform, and another 9 p.c that spoke of they had been going to circulation all of their purposes off IBM i. (This quantity is in keeping with the fresh ALL400s survey accomplished via John Rockwell.)

    Anyway, good good fortune with that.

    Porting applications from one platform to a different, of purchasing a brand new suite on that new platform, is an really difficult task. It is not like attempting to exchange a tire while riding down the road, as is a standard metaphor, but fairly like attempting to take the tire off one automobile moving down the highway and setting up it on a further vehicle riding beside it in the adjacent lane without crashing either motor vehicle or smashing into any person else on the highway. Optimism abounds, but when push involves shove, very few groups are attempting one of these maneuver, and once they do, it is always as a result of there is a corporate mandate, more times than not brought about by means of a merger or acquisition, that pits another platform towards IBM i working on power programs. corporations that say they are making this type of stream off IBM i are sanguine for their personal own reasons, possibly, however they are not necessarily functional about how long it might take, what disruption it's going to cost, and what optimum advantage, if any, may be realized.

    if you do the maths on the chart above, eight-tenths of the base has no theory how lengthy a circulate will take, yet another 1.7 p.c thinks it'll take greater than five years, and 3 percent say it is going to take between two years and five years. simplest 3.four percent of the overall base say they could do it in under two years. We consider all of these numbers are optimistic, and the businesses who may conveniently leave OS/400 and IBM i already did a long time in the past and those which are remain have a harder time, not a less complicated time, moving. If this have been now not true, the IBM i base could be a hell of a lot smaller than the 120,000 shoppers we think are available, in line with what big Blue has advised us during the past. this is the difference between concern or pressure or way of life and the reality of attempting to flow a business off one platform and onto a different. These moves are all the time a lot more durable than they look on the front conclusion, and we suspect most of the benefits also don’t materialize for those who do soar structures.

    at the common attrition expense suggested via this survey information – 9 p.c flow off the platform in somewhere between twelve months and more than five years, with most corporations no longer being capable of see more than five years into the longer term it truly is a neat trick – the put in base would decrease dramatically. it's complicated to assert how far because of the wide selection of timeframes in the survey. If it turned into 9 p.c of the base inside two years – name it four.5 percent of the bottom per 12 months – then inside a decade the standard base would shrink from a hundred and twenty,000 IBM i websites international right down to about seventy two,000. this could dramatic indeed. however at a 1 percent attrition expense per year, the bottom is still at 107,500 entertaining consumers (now not sites and not put in machines, both of which can be greater) via 2029. We believe there is every probability that the attrition price will in reality gradual and drop beneath 1 percent as IBM demonstrates dedication to the energy methods platform and its IBM i working device. There are always some new purchasers being added in new markets, to be certain, but the bleed expense (in spite of the fact that it is small) continues to be likely an order of magnitude greater than the feed rate.

    once they do consider about making the flow, IBM i stores comprehend exactly the place they wish to go, and this answer has been gradually altering through the years: Linux as an alternative choice to IBM i is on the upward thrust and home windows Server as an option is on the wane. in the latest survey, 52 % of the corporations that observed they were relocating all or some of their applications to another platform noted they had been picking windows Server, while 34 % chose Linux. This displays the relative recognition of home windows Server and Linux in the datacenters of the world at large, and might be tipped just a little more closely in opposition t Linux compared to the leisure of the area. apparently, 10 percent of those polled who referred to they have been relocating have been taking a look at AIX structures, and a different 4 % have been going upscale to equipment z mainframes – as not going as this may seem to be. platforms tend to roll downhill; they don't always defy gravity like that.

    The element about such surveys is that they display intent, not motion. We regularly intend to do a lot more than we really can accomplish, and moving systems after spending a long time of building up potential isn't constantly a extremely smart movement until the platform is in precise difficulty – just like the Itanium programs from Hewlett Packard enterprise running OpenVMS or HP-UX or the HP 3000s operating MPE or the Sparc programs from Oracle running Solaris. These had been as soon as first rate structures with huge installed bases and giant revenue streams, however now, IBM is the ultimate of those Unix and proprietary platforms with its energy techniques line. And it is via a ways the greatest and for bound the just one displaying any boom.

    connected reviews

    The IBM i Base Did certainly flow On Up

    The IBM i Base Is able to move On Up

    investment And Integration symptoms For IBM i

    security nonetheless Dominates IBM i discussion, HelpSystems’ 2018 Survey exhibits

    The IBM i Base no longer As Jumpy because it Has Been

    The Feeds And Speeds Of The IBM i Base

    IBM i Priorities For 2017: Pivot To defense

    IBM i developments, concerns, And Observations

    IBM i Survey gets stronger As Numbers grow

    the place Do these IBM i Machines Work?

    finding IBM i: A online game Of forty Questions

    it is time to tell Us What you're up to

    IBM i industry Survey: The significance Of Being Earnest

    What’s Up in the IBM i industry?

    IBM i marketplace Survey Fills in the Blanks


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    IBM-Bigdata-Analytics

    There is a difference between knowledge and understanding. Knowledge typically comes down to knowing facts while understanding is the application of knowledge to the mastery of systems. You can know a lot while understanding very little. Just as an example, IBM’s Watson artificial intelligence system that defeated the TV Jeopardy champs a few years ago knew all there was to know about Jeopardy questions but didn’t really understand anything. Ask Watson to apply to removing your appendix its knowledge of hundreds of medical questions and you’d be disappointed and probably dead. That’s the problem with most analytics, which is why it can be a hard sell.

    The answer to this problem, we’re told, is not just machine learning but Deep Machine Learning, the difference between the two being that plain old machine learning is a statistical process that could be (and used to be) replicated by hand, while the deeper variety looks several generations deep in a longitudinal analysis that quickly grows too big for mere mortals to comprehend. Deep machine learning will, theoretically, find all the interconnections and dependencies that until now we’ve had to rely on domain experts to provide, yet even then it can only happen if you happen to be gathering the right data.

    With regular machine learning, when IBM talks about Watson looking inside your business and finding answers, well that can only really happen if a few PhDs are attached to the software. But with deep machine learning the idea is that the machine can do it all. No PhDs required, which would be quite a breakthrough. And so all the big companies fighting over the future of IT are building new circuits -- hardware -- for deep machine learning. Google and IBM have made recent announcements about theirs. Microsoft told me a couple weeks ago that they have similar hardware working in their lab. It’s a space race.

    And it’s also at least five years from being real on any commercial scale.

    Until deep machine learning is common and fast we’ll be stuck with more mundane analytics. So no, Watson isn’t going to be crunching your company numbers soon and spitting out the right answers or even the right questions to ask. We’re simply not there yet.

    Which brings us to a curious thing happening at IBM. Not closing the I.M. Pei-designed lab in Somers, New York that was announced last week. That campus has been half-empty for years. Nor am I talking about the continuation of IBM’s brutal GTS layoffs, which reportedly killed another 14,000+ IBM jobs last week. What I am talking about here is the reorganization of IBM’s analytics business unit that was announced internally two weeks ago. You won’t find a news story about it… until now.

    The analytics reorg labelled "One Team, One Platform" wasn’t technically a Resource Action (forced layoff). It was explained as a streamlining of business processes to improve efficiency. Citing similar moves at Google, IBM’s analytics group would no longer have employees working from home and the number of official analytics office locations worldwide would decrease from 200 to 30. People will soon be working and meeting physically together, some of them for the first time. This is good, right?

    Yet the reorg is wildly unpopular within the ranks for one important reason: If for some reason affected IBMers need to keep working from home or they can’t or won’t move to their designated IBM office location, well then they are deciding to quit in the view of IBM, which means they are out of the company with no severance -- no package.

    Analytics general manager Rob Thomas, who announced the reorg, has been uniformly described to me by IBMers from that division as "an idiot", which may be some internal IBM technical term, I don’t know.

    The reorg, which tellingly requires some orthodox Jewish IBMers working in Israel to reverse history and relocate to either Germany or Poland, will inevitably result in a significant reduction in head count yet not have to be accounted for as one. These are stealth layoffs.

    Remember that the future of IBM is supposed to be all about CAMSS (cloud, analytics, mobile, security, social) and analytics is the A in CAMSS. In one moment IBM says analytics is strategic, that they are investing and hiring in the area, yet at the same time the company is taking actions that will inevitably lead to the loss of at least some employees who are vital to the unit.

    It’s the blindness of this reorg that amazes me. Heads will go no matter what, but in this case the specific heads won’t be decided by the company but by the workers, themselves. The best workers will be the most employable and therefore the quickest to go. If analytics is so strategic how can IBM allow that to happen?

    I believe I know what’s happening here. Years of layoffs and unfilled positions at IBM mean that pretty much everyone remaining who isn’t in management is already very good at their jobs. There is no more fat to cut. So why not leave it up to the employees, themselves, especially if the gambit will result in very low separation expenses?

    It is unlikely that any of the IBMers who are lost in this reorg will be replaced. Rather, as has become the norm at IBM in recent years, those who are left will be expected to pick up the slack.

    Yes, but what about CAMSS? What about analytics being so strategic to the future of IBM?

    In order to understand that we have to also understand who is IBM’s customer. Peter Drucker wrote that the purpose of the corporation is "to find a customer". Well who is IBM’s customer if the company is effectively cutting one of the divisions it is relying upon for future growth?

    IBM’s customer is Wall Street.

    IBM’s products are earnings-per-share, dividends, and share buy-backs, not hardware, software or computer services.

    This morning I took a quick look at IBM‘s 1Q16 statement. It was interesting what was stated, how it was stated, and what was not stated. They signed $4.2 billion in Analytics and $2.6 billion in Cloud business. The rest of CAMSS was puny. If Analytics is doing better than the rest, why mess with it? How many billions have they spent to make $11 billion a year on cloud?

    IBM has mostly reported revenue. Part of the company’s sales culture, it is what you sign in deals that matters. But how much profit is each division making? That is how most companies are managed. IBM‘s big money maker is services and that is losing business. IBM wants to keep Wall Street off the scent and keeping reported earnings up is critical. So they’re cutting deep with no severance. This is all about buying time until the new business gains traction. However if the new business doesn’t make as much profit, that is going to be a big problem.

    This is a very scary gamble for IBM.

    What this analytics reorg means is that IBM can’t see a way to reach its near-term Wall Street product objectives without cutting heads in analytics. The division was built up in anticipation of certain sales and profit targets, those targets have not been reached, so IBM will cut expenses until the numbers look right. Forget that this reorg will actually result in less -- not more -- work being done. Forget that it makes even less likely IBM achieving its goals for analytics. Forget all of that.

    What it means is the A in CAMSS has already failed. That’s my understanding.


    Can Anyone Stop Amazon from Winning the Industrial Internet? | killexams.com real questions and Pass4sure dumps

    Executive Summary

    Digital natives like Amazon have already disrupted industries such as media, publishing, travel, music, and photography. But who is likely to assume leadership in creating and capturing economic value in Type 3 products (products which have physical components, “smart” components, and connectivity)? If digital natives want to develop software-enabled solutions that siphon off significant value from industrial hardware, they must overcome three barriers: the physics of the hardware, customer intimacy, and difficulty in sharing risks. Likewise, if industrial giants want to lead in the industrial internet they will need to overcome their three barriers: software talent, digital culture, and the incumbent’s dilemma. Among the tech giants, Amazon is a likely winner in the Industrial Internet, as it has successfully fused physical with digital. Amazon understands the economic laws of analog products and is not afraid of massive up-front investments and slower growth.

    Just the announcement that Jeff Bezos, Warren Buffett, and Jaime Dimon will be entering the health care space has sent shock waves for industry incumbents such as CVS, Cigna, and UnitedHealth. It also puts a fundamental question back on the agendas of CEOs in other industries: Will software eat the world, as Marc Andreessen famously quipped? Is this a warning shot that signals that other legacy industrial companies, such as Ford, Deere, and Rolls Royce are also at increased risk of being disrupted?

    To start to answer that question, let’s tally up the score. There are three types of products today. Digital natives (Amazon, Google, Facebook, Microsoft, IBM) have gained competitive advantage in the first two, and the jury is still out on the third:

  • Type 1: These are “pure” information goods, where digital natives rule. An example would be Google in search, or Facebook in social networking. Their business models benefit from internet connectivity and they enjoy tremendous network effects.
  • Type 2: These are once-analog products that have now been converted into digital products, such as photography, books, and music. Here too, digital natives dominate. These products are typically sold as a service via digital distribution platforms (Audible.com for books, Spotify for music, Netflix for movies).
  • Type 3: Then there are products where input-output efficiency and reliability of the physical components are still critical but digital is becoming an integral part of the product itself (in effect, computers are being put inside products). This is the world of the Internet of Things (IOT) and the Industrial Internet.
  • Manufacturing-heavy companies such as Caterpillar, Ford, and Rolls Royce compete in this world. An aircraft engine is unlikely to become a purely digital product any time soon! Such products have three components: physical components, “smart” components (sensors, controls, microprocessors, software, and enhanced user interface), and connectivity (one machine connected to another machine; one machine connected to many machines; and many machines connected to each other in a system).

    Digital natives have already disrupted industries such as media, publishing, travel, music, and photography. But who is likely to assume leadership in creating and capturing economic value in Type 3 products: Digital natives or industry incumbents? Ford or Tesla? Rolls Royce or IBM? Caterpillar or Microsoft? Amazon, Berkshire Hathaway and JPMorgan Chase combine or UnitedHealth?

    The Challenges for Digital Natives

    Value will no doubt be created in the era of smart, connected machines. We don’t expect Amazon or Microsoft or IBM to design, make, and market agricultural tractors, aircraft engines, or MR scanners. The question really is: Can digital natives develop software-enabled solutions that siphon off significant value from industrial hardware? The answer is “yes.” But it won’t be easy. It will require tremendous amounts of investments in building new capabilities for hardware companies like HP, Cisco, Dell, Samsung, and Lenovo; established software companies like Facebook, Google, Amazon, and Microsoft; and start-ups. In particular, there are three barriers they must overcome:

    1. The physics of the hardware. Companies like Rolls Royce design and manufacture jet engines. These are very complicated machines. There is hard science behind these machines. That’s much different than digital natives like Airbnb where marketing is more important than technical expertise.

    Industry incumbents have expertise in the material sciences, for instance. Further, scientific knowledge keeps improving over time. They have made heavy R&D investments—both basic and applied—to remain at the cutting-edge of the physics of the hardware. Much of this scientific knowledge is protected by patents.

    Mastery of hard science is a pre-requisite to develop software-based solutions on the hardware. These companies’ superior product/domain knowledge provides them the comparative advantage to model the asset’s performance and write high-end/high value-added software applications. A “pure” digital company can write commodity software applications. But it must acquire enough capabilities on the physics to write sophisticated apps that improve assets’ performance.

    2. Customer intimacy. Industrial giants have well-established brands, built strong customer relationships, and signed long-term service contracts. They’ve won the customer’s trust, which is why customers are willing to share data. Digital natives can work with industrial customers, but they have to first earn their trust; they must build capabilities to understand customer operations; they must match the industrials’ cumulative learning from customer interactions; they must learn to ask for the right data; and they have to hire experts in several verticals that can turn data into insights.

    3. Difficulty in sharing risks. Industrial incumbents have product knowledge, customer relationships, and field engineers on customer sites. Companies like Rolls Royce can, therefore, offer outcome deals where they guarantee customer outcomes (examples: zero downtime, higher speed, more fuel efficiency, zero operator error, greater reliability) and share risks and rewards with customers. It would be very hard for Amazon or Google to guarantee customer outcomes and take risks with businesses whose operations they know little about.

    The Challenges for Industrial Giants

    Can the industrial giants lead in the Industrial Internet? The answer is “yes.” But it won’t be easy for them, either. They too have three significant barriers to overcome:

    1. Software talent: The IT talent in industrial companies can execute projects oriented towards process efficiency and cost reduction. That talent is ill-suited to develop new, breakthrough software products that offer superior customer outcomes. For that end, they must be able to attract world-class innovators and software engineers. Is, say, Rolls Royce, in the same consideration set as Facebook and Google for young tech employees? Not, really. If so, how can the industrial giants compete to attract the best talent?

    2. Digital culture: Industrial businesses and digital businesses operate with completely different principles. The characteristics of hardware businesses include long product development cycle, Six Sigma efficiency, and long sales cycle. Software businesses have different characteristics: short product development cycle, flexibility, and short sales cycle. The industrials must build a digital culture based on concepts like lean, agile, simplicity, responsiveness, and speed. That’s a tall order for an established enterprise.

    3. The Incumbent’s Dilemma: Digital has the potential to disrupt industrial businesses. There are three ways digital strategy can cannibalize “core” industrial business. First, data and insights can help improve the productivity of machines; digital, therefore, has the potential to cannibalize future hardware sales. Second, data and insights increase the reliability of machines; digital therefore has the potential to cannibalize future service revenues. Third, software subscription and license might enable customers to do self-service. Current customers could terminate/renegotiate service contracts, and potential customers may not enter into service contracts at all. In short, it is very difficult for a company to disrupt itself.

    The future of the Industrial Internet will involve partnerships across a variety of players including tech companies and industrial companies. The key issue: Who will assume the leadership position to extract maximum economic value in such an ecosystem? Will industrial companies take the lead? Or will the digital natives take the lead? Both have a chance.

    If I were a betting man, I would place my bets on tech giants over industry incumbents. One factor that will favor digital companies in the industrial internet is technological/scientific breakthroughs that level the playing field for newcomers. For example, breakthroughs in battery technology made the electric cars possible. Electric cars are much simpler to design than cars with internal combustion engines, allowing Tesla and BYD to enter the market despite Ford’s decades of expertise. Since electrification and driverless cars go together, other tech companies such as Google, Baidu, Apple, and Lyft will also be able to enter the automotive market. Similar technological changes in jet engines and agricultural tractors can allow tech giants to gain foothold in these industries as well.

    More importantly, Amazon or Google have the resources to acquire the capabilities to master the physics and acquire customer relationships and compete with the industrial giants in the Industrial Internet. They have enough resources and some to buy them, if needed.

    Among the tech giants, Amazon is a likely winner in the Industrial Internet. It has successfully fused physical with digital. Amazon understands the economic laws of analog products and is not afraid of massive up-front investments and slower growth. Its acquisition of Whole Foods and experiments with Amazon Go grocery stores are an example. Amazon is the one company everyone’s scared of, even industrial giants.


    In the rush to build a social strategy, don’t pull a Tech Frankenstein | killexams.com real questions and Pass4sure dumps

    ‘Social’ has become a leading theme—if not THE leading theme—among marketers. Marketers at major brands, retailers and increasingly, even financial services companies, are dabbling in everything from social promotions tools to drive higher traffic, sales and loyalty.

    With all the opportunities that come with social comes the unwelcome challenge of matching technologies to marketing objectives. And even though marketers are getting more analytical, most don’t relish the prospect of evaluating numerous vendors and technologies to get the job done, preferring instead to turn to outside agencies to make crucial technical decisions. This may be expedient in the short term, but an outside agency will never understand your needs as well as your own internal technology experts. An outside agency works well for a quick fix, but using internal resources prepares you for the long haul.

    As marketers increasingly graduate from experimenting with point solutions to truly wanting to drive ROI from Social, they will need the help of their own “Chief Innovation Officers” to succeed. Here’s why:

    Division of Labor

    The rise of social has made it everyone’s job to implement technology. While marketers are being pushed into working at a more technical level, in most cases, it’s not what they’re best at. In fact, a recent IBM study confirmed what we all intuitively know – 65% of CMOs feel unprepared to deal with the growing channel and tech device choices. Even as marketers shift their priorities, they can’t magically shift their skill set and many find themselves in unchartered territory. They know they need help – and they’re jumping to implement outside technologies they believe will provide it.

    Fortunately, there’s software for everything — particularly for what they need most — social networking and data-tracking. Unfortunately, while these technologies are helpful to marketers who need a leg up, they’re still more effective when by managed by someone with a technical background and familiarity with a company’s information infrastructure.

    That’s where IT comes in. They have a better mastery of technological solutions, how they work at a granular level and how they fit into the organization infrastructure and how they can be developed. Furthermore, your IT staff actually enjoys dealing with vendors, application stacks, and the interoperability of cloud-based tools, whereas most marketers seem them as means to an end. Not only can marketers offload some of this non-core responsibility, but they can focus on their core business imperatives, whether it’s increasing engagement or measuring social ROI.

    Seeing the Big Picture

    Marketers must be careful to select technologies that can not only help them implement quick changes, but also scale as needs expand and the company grows. Left to their own devices, marketers run the risk of creating a Frankenstein of mismatched technologies that don’t scale.  They need more help than a stand-alone software can provide.

    On the other hand, IT is uniquely positioned to help select social platforms that can succeed in this environment. They know to set up systems that unite the different departments of the organization. When they select solutions, they have in mind not just current needs but future potential.

    Conclusion: Everybody Wins

    No one in any department has yet mastered the best way to cope with changing technological landscape. Getting a handle on it is absolutely going to require collaboration.

    IT leaders don’t necessarily have an understanding of how social media and marketing operates, but they are better equipped to process analytics in a meaningful and efficient way. Every department excels at something different, and what makes this such an exciting time is that everyone’s skills are in demand. Devising an infrastructure chock-full of technologies that will benefit the company most requires an “all-hands on deck” philosophy. So marketers,  it’s time to stop fearing your counterparts in IT and go make friends. Only when everybody plays can anybody win.

    Nadim Hossain is currently the vice president of marketing at PowerReviews, a social software company that recently acquired by Bazaarvoice and used by leading brands such as Dillards, REI, Toys “R” Us, and Staples. Follow him @nadimhossain.



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