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P2050-007 IBM Optimization Technical Mastery Test v1

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P2050-007 exam Dumps Source : IBM Optimization Technical Mastery Test v1

Test Code : P2050-007
Test appellation : IBM Optimization Technical Mastery Test v1
Vendor appellation : IBM
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IBM IBM Optimization Technical Mastery

IBM particulars Channel Plans For Netezza records Warehouse appliances | real Questions and Pass4sure dumps

statistics warehouse appliances

The dart will give resellers with a orbit of revenue, advertising and technical elements that IBM stated will create it less demanding to market and promote Netezza methods. IBM is additionally providing unique financing alternatives to channel companions who resell the Netezza home equipment, together with zero-% financing and all-around charge options for consumers.

while Netezza largely offered its statistics warehouse appliances direct to consumers, IBM has had its eye on the channel for promoting Netezza items on the grounds that it obtained the enterprise in November for $1.7 billion. at the Netezza consumer convention in June IBM executives unveiled a companion recruitment effort for Netezza and pointed out they prognosticate the channel to account for 50 % of Netezza sales within 4 years.

"company analytics goes mainstream and IBM's aim is to arm its partners with the correct abilities and aid to serve their shoppers retract learning of this vogue," referred to Arvind Krishna, regularly occurring supervisor of IBM assistance management, in a statement. "These [new] resources are geared to create it effortless for their companions to promptly infuse Netezza into their company model."

IBM has identified traffic analytics as one in every of its strategic initiatives and has forecast that traffic analytics and optimization products and services will generate $sixteen billion in annual revenue for the company by 2015.

Netezza's techniques are in accordance with IBM's BladeCenter servers.

Channel partners requisite to exist approved to resell IBM products that arrive under the utility value Plus (SVP) application. Authorization necessities embrace having at least two personnel who Have handed a technical mastery exam and one who has passed a income mastery examination.

Resellers who qualify for the SVP application are eligible for co-advertising cash for lead generation and other market planning guidance. IBM furthermore offers partners a potential bootcamp where group of workers can instruct on the way to deploy, control and hold Netezza methods. And SVP-member resellers can bring revenue prospects into IBM Innovation centers to examine-drive Netezza items.

starting Oct. 1 the Netezza products additionally will arrive under IBM's utility charge Incentive software, which provides economic rewards for partners who identify and advance earnings alternatives, but attain not always deal with product achievement.

On the financing facet partners can present zero-p.c financing via IBM global Financing to credit score-certified valued clientele for Netezza purchases. additionally purchasable is 24- and 36-month financing with options that let clients match payments to anticipated cash flows.

And partners can lease a Netezza gadget for twenty-four months to Hurry inside their own facts facilities for demonstration, building, checking out and practicing purposes, IBM stated.

Charlotte, N.C.-based mostly options company and IBM associate Fuzzy Logix, which supplies predictive analytics application and functions to purchasers, "will expend these components from IBM to find international company opportunities and carry higher cost services to their valued clientele," referred to COO Mike Upchurch, in a statement.

IBM Db2 query Optimization using AI | real Questions and Pass4sure dumps

In September 2018, IBM introduced a unique product, IBM Db2 AI for z/OS. This synthetic intelligence engine screens records entry patterns from executing SQL statements, uses computing device studying algorithms to settle on superior patterns and passes this assistance to the Db2 query optimizer for expend through subsequent statements.

desktop researching on the IBM z Platform

In might furthermore of 2018, IBM announced version 1.2 of its computing device learning for z/OS (MLz) product. here's a hybrid zServer and cloud software suite that ingests efficiency data, analyzes and builds models that depict the health reputation of quite a lot of indications, screens them over time and gives precise-time scoring capabilities.

a number of features of this product offering are aimed at supporting a community of model developers and bosses. for instance:

  • It supports multiple programming languages similar to Python, Scala and R. This makes it workable for facts modelers and scientists to create expend of a language with which they are typical;
  • A graphical person interface called the visual mannequin Builder courses mannequin builders without requiring incredibly-technical programming potential;
  • It contains distinctive dashboards for monitoring mannequin results and scoring features, in addition to controlling the device configuration.
  • This computing device studying suite turned into originally geared toward zServer-based mostly analytics purposes. one of the vital first glaring decisions turned into zSystem efficiency monitoring and tuning. device administration Facility (SMF) facts that are automatically generated by way of the working gadget deliver the raw information for device aid consumption similar to principal processor utilization, I/O processing, reminiscence paging and the like. IBM MLz can assemble and uphold these records over time, and construct and train models of gadget conduct, rating those behaviors, establish patterns not effectively foreseen by way of humans, advance key performance indications (KPIs) after which feed the model effects returned into the tackle to paw tackle configuration changes that can enrich efficiency.

    The next step became to implement this suite to investigate Db2 efficiency statistics. One answer, called the IBM Db2 IT Operational Analytics (Db2 ITOA) solution template, applies the computing device researching technology to Db2 operational records to profit an figuring out of Db2 subsystem health. it could actually dynamically construct baselines for key efficiency indications, provide a dashboard of those KPIs and give operational workforce true-time insight into Db2 operations.

    while regularly occurring Db2 subsystem performance is a crucial component in basic utility health and performance, IBM estimates that the DBA serve team of workers spends 25% or greater of its time, " ... fighting entry path problems which occasions performance degradation and repair influence.". (See Reference 1).

    AI involves Db2

    agree with the plight of concurrent DBAs in a Db2 atmosphere. In ultra-modern IT world they should assist one or extra massive records applications, cloud software and database functions, application setting up and configuration, Db2 subsystem and utility performance tuning, database definition and administration, catastrophe healing planning, and extra. query tuning has been in actuality since the origins of the database, and DBAs are constantly tasked with this as neatly.

    The coronary heart of query path analysis in Db2 is the Optimizer. It accepts SQL statements from functions, verifies authority to access the records, reviews the places of the objects to exist accessed and develops a list of candidate statistics access paths. These access paths can encompass indexes, table scans, a lot of table exist a portion of strategies and others. within the statistics warehouse and Big data environments there are always extra choices available. One of those is the actuality of summary tables (now and again known as materialized question tables) that comprise pre-summarized or aggregated records, therefore enabling Db2 to uphold away from re-aggregation processing. one other selection is the starjoin entry route, middling within the information warehouse, where the order of table joins is changed for performance causes.

    The Optimizer then reviews the candidate access paths and chooses the access path, "with the bottom can charge." cost in this context potential a weighted summation of useful resource utilization including CPU, I/O, reminiscence and other elements. ultimately, the Optimizer takes the lowest can charge access direction, stores it in reminiscence (and, optionally, within the Db2 listing) and begins access course execution.

    massive information and information warehouse operations now embrace utility suites that enable the company analyst to create expend of a graphical interface to build and manipulate a miniature statistics model of the information they want to analyze. The packages then generate SQL statements in response to the clients’ requests.

    The rigor for the DBA

    so as to attain respectable analytics to your numerous records shops you requisite an excellent understanding of the information necessities, an realizing of the analytical capabilities and algorithms accessible and a high-performance statistics infrastructure. unfortunately, the number and location of information sources is expanding (each in measurement and in geography), records sizes are growing to be, and functions proceed to proliferate in quantity and complexity. How may still IT managers uphold this ambiance, particularly with essentially the most skilled and age carcass of workers nearing retirement?

    have in mind furthermore that a great a portion of decreasing the gross charge of possession of those techniques is to bag Db2 functions to Hurry quicker and more efficiently. This constantly translates into using fewer CPU cycles, doing fewer I/Os and transporting less data throughout the network. due to the fact that it's frequently tricky to even establish which functions may handicap from performance tuning, one strategy is to automate the detection and correction of tuning considerations. this is the site desktop gaining learning of and ersatz intelligence will furthermore exist used to awesome impact.

    Db2 12 for z/OS and ersatz Intelligence

    Db2 edition 12 on z/OS uses the computing device discovering facilities outlined above to collect and store SQL query text and entry route particulars, as well as actual performance-related ancient information akin to CPU time used, elapsed times and influence set sizes. This offering, described as Db2 AI for z/OS, analyzes and stores the records in computer getting to know fashions, with the mannequin evaluation effects then being scored and made obtainable to the Db2 Optimizer. The subsequent time a scored SQL remark is encountered, the Optimizer can then expend the mannequin scoring facts as enter to its entry path option algorithm.

    The outcome may still exist a reduction in CPU consumption as the Optimizer uses model scoring input to choose stronger entry paths. This then lowers CPU costs and speeds utility response instances. a Big learning is that using AI application does not require the DBA to Have information science skills or abysmal insights into question tuning methodologies. The Optimizer now chooses the example entry paths primarily based now not only on SQL query syntax and facts distribution information however on modelled and scored historic performance.

    This can exist mainly vital if you shop facts in diverse places. for instance, many analytical queries in opposition t great facts require concurrent access to positive data warehouse tables. These tables are commonly called dimension tables, and they accommodate the records aspects always used to control subsetting and aggregation. as an example, in a retail ambiance account a desk referred to as StoreLocation that enumerates each store and its belt code. Queries towards redeem revenue facts may want to amalgam or summarize revenue by means of area; therefore, the StoreLocation desk should exist used with the aid of some massive statistics queries. in this atmosphere it's middling to retract the dimension tables and replica them regularly to the huge facts utility. in the IBM world this vicinity is the IBM Db2 Analytics Accelerator (IDAA).

    Now suppose about SQL queries from each operational functions, data warehouse clients and Big information enterprise analysts. From Db2's point of view, each and every these queries are equal, and are forwarded to the Optimizer. although, in the case of operational queries and warehouse queries they may still certainly exist directed to entry the StoreLocation table in the warehouse. then again, the question from the company analyst in opposition t massive statistics tables should still probably access the copy of the table there. This effects in a proliferations of expertise access paths, and greater labor for the Optimizer. happily, Db2 AI for z/OS can deliver the Optimizer the suggestions it should create smart entry direction selections.

    the way it Works

    The sequence of movements in Db2 AI for z/OS (See Reference 2) is generally the following:

  • right through a bind, rebind, prepare or clarify operation, an SQL remark is handed to the Optimizer;
  • The Optimizer chooses the statistics entry route; because the selection is made, Db2 AI captures the SQL syntax, access path selection and query efficiency information (CPU used, and so on.) and passes it to a "studying task";
  • The researching project, which will furthermore exist achieved on a zIIP processor (a non-regularly occurring-goal CPU core that does not component into application licensing fees), interfaces with the computer studying software (MLz model capabilities) to store this advice in a mannequin;
  • as the quantity of statistics in each mannequin grows, the MLz Scoring provider (which furthermore can exist completed on a zIIP processor) analyzes the mannequin facts and scores the conduct;
  • right through the subsequent bind, rebind, prepare or clarify, the Optimizer now has access to the scoring for SQL fashions, and makes applicable changes to entry direction selections.
  • There are additionally various person interfaces that supply the administrator visibility to the popularity of the accrued SQL observation performance statistics and mannequin scoring.


    IBM's laptop discovering for zOS (MLz) offering is getting used to extremely grand impact in Db2 version 12 to expand the efficiency of analytical queries in addition to operational queries and their associated applications. This requires management attention, as you should examine that your traffic is prepared to consume these ML and AI conclusions. How will you measure the costs and advantages of the expend of desktop studying? Which IT serve group of workers Have to exist tasked to reviewing the outcome of mannequin scoring, and perhaps approving (or overriding) the results? How will you review and justify the assumptions that the application makes about access direction choices?

    In other words, how neatly did you know your records, its distribution, its integrity and your existing and proposed entry paths? this could assess the site the DBAs disburse their time in supporting analytics and operational application performance.

    # # #

    Reference 1

    John Campbell, IBM Db2 fantastic EngineerFrom "IBM Db2 AI for z/OS: boost IBM Db2 utility efficiency with laptop discovering"

    Reference 2

    Db2 AI for z/OS

    See each and every articles through Lockwood Lyon

    IBM: an extended Work-In-growth | real Questions and Pass4sure dumps

    No result discovered, are trying unique key phrase!in spite of this, looking from the technical charting standpoint ... the SVP and CFO of IBM, preeminent in the income appellation that the enterprise has been in search of to enrich its "body of workers optimization productiveness ...

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    Retiring Mainframe Programmers: Should I Care? | real questions and Pass4sure dumps

    Key Takeaways
  • Mainframe developers are not just retiring, they are expiring -- and youthful developers Have tiny interest in mainframe careers.
  • Mainframe programmers Have exist treated love bus drivers whose only job is to consistently dart huge amounts of data.
  • It’s not the mainframes that are aging; mainframes out compete Microsoft and Linux on features love performance, scalability, security, and reliability.
  • Refactor code into reusable modules, with tests, and adopt agile practices.
  • There is no ROI for modernizing mainframe applications in terms of quarterly results.
  • We retract Uber, browse Pinterest, route tweets, and update Facebook. They hear every day about instant millionaires and the growing number of billionaires that built the latest gadgets in their high-tech world. But they ignore the fact that over 70% of each and every traffic transactions are processed on mainframes. Their visual and audio world is presented with tools hastily slapped together by youthful hotshots yet the reality is that the chairs they sit on, the paychecks they cash, the health care they utilize are available through data managed by mainframes. That’s right, over 80% of manufacturing, banking, and healthcare industries are on mainframes.

    We hear so much hype about monetization of unique markets that they fail to confess the weight of mainframe code. Well, there’s this tiny issue… most mainframe developers are baby boomers who are approaching or past retirement. The harsher side to this reality is that the aren’t just retiring, they are expiring. (Short prayer for Jim Stanicki and John Stalher who were two exemplary mainframe developer friends of mine that died in the terminal few years.)

    I aroma Rewrite

    Shouldn’t those customary mainframe applications just exist rewritten? It ain’t that easy. Yeah, I know, you’ve heard about rewrites for years. But the understanding why most of those Visual Basic, dBase III, and PHP apps (that’s right, I’m maxim they weren’t mainframe apps) were rewritten every 5 years is because they weren't written that well to originate with. Meanwhile, the mainframe apps Have been running well for decades. The recur On Investment (ROI) for rewrites of mainframe applications just hasn’t been there. Case in point: In the mid ‘80s I wrote a traffic system for Hanover Brands Inc. that is still in expend today.

    But then there’s this retiring and expiring thing. Why not just champ the bullet and attain the rewrite?

    Rewrites are never light and, for huge applications, they are often failures. Just a few weeks ago, I did a rewrite of a little, itty, bitty, PHP application to Ruby and Rails. Now, I’m pretty grand with Ruby and OK with PHP but, even though it was just over a thousand lines, I still missed stuff. Mainframe Cobol and RPG applications are a wee bit more complex. It is common for an RPG program to exist ten, and Cobol to exist twenty, thousand lines long. Multiply that by hundreds and hundreds of programs and you Have an application that has a mega-million lines. Worse that that, many of those programs were written before modular programming techniques became available. Typically, each and every variables in one of these behemoths are global. I remember, dozen years or so ago, I had a jest-quest in articles and seminars of a Diogenes-like search for a local variable in mainframe code. Diogenes never organize an honest man and I had problems finding local variables in circa-70s code.

    RPG specifically can exist crazy arduous to read and understand. For years RPG could only expend six character variable names. Actually, its was worse than that. RPG had a bug where if you used the very column appellation in two different tables, they would partake the very reminiscence space. So RPGers used two to four of those precious six character column names to identify the system and table they were associated with. The bug was fixed decades ago and today the variable and database column appellation length supports at least thirty two characters. But six character variable names are still prevalent in RPG programs.

    Somewhere around 1992 I gave a presentation on Cobol modularizing techniques to the team of Circuit City coders of which I was a member. After the presentation, one of Circuit City’s best Cobol programmers said she didn't perceive the benefit of modularizing Cobol.

    Understand that I can bag in a fist fight with other Ruby developers over a discussion on whether a system should exist no more than 6 or 9 lines long. In Ruby development, wanton expend of global variables might bag you fired. So I kindly of chuckle when I recall working on these 10-20,000 line programs. Maintaining Cobol and RPG monstrosities is often more voodoo than mastery. You try something that you Have a gut feel will labor and you light incense, sprinkle holy water, and pray to a variety of gods that your change will work.

    The prevalent progress practices of Cobol and RPG propagates expend of outdated syntax. They are talking hideous code. Often thousands of lines of code in one program Have been commented out. Many sections are completely unused. Looking at some of this code is love walking into a hoarder's house -- it's full of useless junk. To push the analogy perhaps too far -- the more junk that piles up the more haphazard of rot and, yeah, reek (and they talk of code smells.) The thing is: processes and materials you expend everyday rush through this customary rotting code the maintainers of which are retiring and expiring.


    Let me exist honest… The understanding I migrated my career away from the mainframe progress workspace is velocity -- or the lack thereof. progress practices and toolsets for RPG and Cobol Have languished. Test driven development, source control, modern editors, refactoring, agility… for years I proselytized such concepts in articles and seminars and not only was I, for the most part, ignored, but I couldn’t find projects to labor on that followed such practices.

    The essential word in my terminal paragraph was agility. Because mainframe application progress practices lack agility they are behind to conform to market demands. Often, the tarnishing of these customary apps and the impending retirement of uphold staff occasions unique hot-shot C-level executives to imply the procurement of costly ERP systems or complete rewrites. And we’ve each and every heard horror stories about such projects.

    Modern Machines

    Understand that the mainframes are not antiquated. They are not the System 360 and AS/400 of yesteryear but the IBM z/OS and IBM i 64-bit operating systems with reliability and scalability that Linux and Windows can’t approach. They furthermore Have a lower total cost of ownership for intricate data centers. You scale mainframes horizontally, rather than vertically. Those mainframes can Hurry the latest software as well. Case in point: you can Hurry thousands of Docker images on one mainframe. DB2 for i is arguably the best database on the planet. As to smarting technology, A few years ago I was on a team the moved Ruby and Rails to the the indigenous IBMi operating system. Banking applications Hurry on mainframes primarily for security reasons. And it was a banker that funded the Rails port to the IBM i platform. There are huge advantages to mainframes: ranging from huge horizontal growth to the ultimate in security and very close to 100% reliability. It may exist exact that IBM is selling less mainframes but they are doing quite well upgrading and expanding the existing machines as they Have astronomical horizontal scalability.

    What is aging is not the machines but mainframe applications and application programmers.

    So, They Are Screwed?

    Absolutely, just love they were when they hit year 2000 and everything crashed. It didn’t. They were just fine. They were fine because management finally started taking the two-digit to four-digit year thing seriously. If management begins to retract the mainframer skills loss thing seriously, they will exist fine.

    Let me summarize my solution to the retiring and expiring mainframe coders thing before going into more detail:

  • Modernize the database
  • Refactor application code
  • Train existing mainframers on agile and as trainers
  • Coerce smart people into a career in mainframe development
  • Convert existing code into APIs
  • Modernize the Database

    Modernizing the database is step one. A wealth of data kept in the world’s best database and operating systems is hidden behind applications that are twenty to forty years old. Many of the mainframe databases were created before today's well known database normalization and optimization techniques were created. At tiny as ten years ago I achieve a web front finish on a table that was clearly housed, at one point, in a card deck. There are tools and available techniques that allow you to mock the customary database schema’s structure so legacy programs may continue to Hurry with tiny or no modification. From sustain I know that refactoring the database is not that difficult to do.

    Refactor Application Code

    I made a Big stink earlier about the condition of mainframe code. Know that mainframe code can exist refactored to the point that progress can exist much more agile. Understand that I am not talking rewrite. Refactoring is the process of restructuring existing code without changing its behavior. The C-level executives should not Have tocsin of the downtime that would exist probable with a massive rewrite.

    The first step to refactoring is to achieve code under source control. I highly recommend git. Perhaps the mainframe code is already managed by a source control package but my sustain with mainframe source control packages is that they propagate sluggish progress and dissuade common refactoring strategies. As soon as the code is in git, remove the commented out code -- it’s source control’s job to retain customary versions of code.

    The second step to refactoring is updating the progress environments. Many mainframers still expend green-screen editors even though powerful IDEs Have been available for at least two decades. These modern IDE are bundled with refactoring tools.

    The third step is to set up a unit testing strategy. Unit tests typically Have very specific and minute tests for program behavior. They don’t Have time for that. What I recommend is to supervene the Approvals Testing strategy developed by Llewellyn Falco ( The basic concept of Approvals Testing is that you retract snapshots of condition before and after execution of a routine. That snapshot could exist anything from a database query result, to a PDF, to a CSV. exist creative.  With the snapshot stored, you modify the routine and expend the before and after images to verify that the refactoring did not change behavior. You may finish up using a testing infrastructure that uses Java or Ruby or Python to invoke the mainframe routines but this layer will not exist complex.

    With a unit testing strategy constructed, the refactoring should originate with making variable names readable and understandable. Then start to whack away at reducing the expend of global variables as you dart into modularization. Duplicate code is rampant in mainframe code so expend tools to find that duplicate code and then create common modules for them.

    Empower Existing Developers

    The golden key to a refactoring strategy is your best mainframe developer(s). And now I’m going to bag a bit nasty:  Mainframe developers Have been treated by their employers love bus drivers. Management feels it is the programmer’s job to dart data from point to point and, when something breaks, they are expected to twiddle with the engine until they can bag back on the bus and originate affecting data again. From my personal experience, they are often underappreciated and underpaid. Many of these mainframers Have no degree and deal with C-level executives with Ivy-league MBAs that look to lack the ability to account the ROI for more than this next quarter.

    These mainframers requisite to exist empowered. The will requisite retraining on agile progress practices and they furthermore requisite to become trainers themselves. They will requisite assistance in the refactoring and the later creation of modular APIs. And then there’s the issue of retiring and expiring so it will exist portion of the empowered mainframer’s job to manage the training of unique developers.

    If one of your existing mainframers doesn’t stand-out as a project lead, fade out and bag one. The problem is that many of the folks out there that Have more than enough ability to serve Have moved on. They’ve moved on to management, or training or, love me, they’ve moved on to other programming languages and platforms. The problematic thing with these people is that, decades ago,  they grew tired of the revolving door of C-level executives who turned down their recommendations for modernization. Many of these ex-mainframers may simply show you to buy an ERP,  give Oracle a call, or attain a complete rewrite (which they know from sustain will probably exist a failure.) So exist prepared to wheel and deal with these guys.

    Where might you find these ex-mainframers? Troll Linkedin for those folks that are attempting to screen mainframe sustain yet Have excellent communication skills and sustain with unique technologies and agile. fade to Java, Ruby, JavaScript conferences and talk to the folks that are over 50. Based on their age, they probably are ex-mainframers but they are furthermore well versed in unique tech and, more importantly, agile development. 

    Once you know what you are looking for you might not Have to study too far. This paragraph may exist cleave because my editor is an ex-mainframer and an Agile coach. He probably will cleave this paragraph because he left his mainframe bus driver job years ago. fade find a person love him to manage your mainframe modernization project. [EDITOR: No - I left it in because I agree]

    Coerce Smart People Into Becoming Mainframers

    Colleges aren't teaching Cobol and RPG. There are blog posts and articles on Skill Loss that imply colleges requisite to add mainframe course and otherwise attract millennials to careers in mainframes.

    I don’t think millennials are the solution. I would not imply a career in mainframe progress to any youngster. There are far less jobs available and the behind progress velocity makes for a less satisfying career.  My suggestion is 1) retrain existing non-IT staff and 2) coerce folks in their 30s and 40s into a mainframe career. Both of those suggestions sound crazy but I question the capabilities of a youthful IT graduate that is willing to originate their career on a mainframe.

    The technical learning required to exist a mainframe developer is more focused than the polyglot, multi-platform, programmer of today’s vogue developer. What companies requisite is not someone with NodeJS and functional programming skills but traffic acumen, a crave to learn, and, quite simply, smarts. There are plenty of smart people with non-IT mid-career blues that would exist willing to Have the opportunity to potentially double their salary after a year of on the job retraining. One belt to tap would exist retired military.

    Convert Code into APIs

    The final step in a mainframe modernization process is to gyrate your refactored code into APIs. The will them exist reusable software components. Often the parameter list of mainframe code will exist so intricate that it might look that creating an API for it would exist impossible. For those you create one or more wrapper programs (which can exist written with Cobol or RPG or your unique language of choice.) One technique I liked to expend was to create SQL Stored Procedures that wrapped the legacy modules. With SQL Stored Procedures available, anybody with an SQL interface (JDBC-, ODBC-driver or whatever) can expend those routines.

    With legacy code available via an API (SOAP, REST, or otherwise) and unit tests for everything, progress can exist fully agile. unique code can exist written in whatever language you choose. And, yeah, you can hire millennials.

    The more sensitive and intricate programs that prove up tall on your churn reports can then exist slated for conversion to a unique language.

    Mainframe Agility

    Mainframe applications, while being crazy accountable for each and every but half-a-century, are brittle with little, if any, automated tests, and the mainframe workforce either does not know about refactoring strategies or hasn’t had the C-Level management backing to start it. In short the code is not adaptable to changing traffic requirements. Existing mainframe programmers are retiring at an alarming rate and the workforce is not being replenished.

    Moving off the mainframe is far from the most optimal solution. Complete rewrites or converting to an ERP is costly and fraught with peril. The mainframe boxes themselves are not aging. In fact they outcompete Microsoft and Linux on features love performance, scalability, security, and reliability. It’s not the machines but applications and programmers that are aging.

    Modernize that database, refactor that code, become agile, shore up programming staff with internal training. And finally, where it shows benefit, start to dart your newly modularized code into a unique language.

    The thing is: these solutions are relative on C-level executive buy in. For them to attain that they requisite to study past quarterly results and think about what the next two to five years will bring as they lose their undervalued mainframe developers.

    About the Author

    Don Denoncourt is a developer for He has been coding since before Windows and Linux, much less the Internet. In the early nineties, Don moved from RPG and Cobol to C and C++. He adopted Java before it was real: 1996. After coding his way through the proliferation of Java frameworks (including Struts, Spring, and EJB) Don pined for the Convention-over-Configuration framework of Ruby and Rails. Don did Groovy and Grails before finally affecting to Rails in 2011. Don enjoys writing and has published a pair of books and hundreds of technical articles. Don has been working from home since terminal century. When Don is not working, he loves spending time with his 3 grandchildren. To uphold his mind young, Don reads and listens to novels in Italian. And, to uphold his carcass young, Don is an avid off-road and street unicyclist.

    Your usher to the top Big data certifications today | real questions and Pass4sure dumps



    Data and Big data analytics are rapid becoming the lifeblood of any successful business. Getting the technology privilege can exist challenging, but pile the privilege team with the privilege skills to undertake Big data initiatives can exist even harder.

    Not surprisingly, that challenge is reflected in the rising exact for Big data skills and certifications. According to research by IT research firm Foote Partners, both noncertified advanced data analytics skills and certified Big data skills Have gained value in recent years: with 74 advanced data analytics related skills and certifications rising in middling value by 6 percent in 2015, followed by 116 advanced data analytics related skills and certifications increasing 4.8 percent overall in market value in 2016. Additionally, Foote Partners research organize 123 related certified and noncertified Big data skills seeing a 0.3 percent gain in value in the first quarter of 2017.

    Organizations are on the hunt for data scientists and analysts with expertise in the techniques required to analyze Big data. They furthermore requisite Big data systems architects to translate requirements into systems, data engineers to build data pipelines, developers who know their way around Hadoop clusters and other technologies, and systems administrators and managers to tie everything together.

    [ Find out the hottest data and analytics trends today. | bag ahead with the top certs for Big data, project management, agile, and the cloud. | bag weekly career tips by signing up for their CIO Leader newsletter. ]

    These skills are in tall exact and are relatively rare. Individuals with the privilege coalesce of sustain and skills can exact tall salaries. The privilege certifications can help.

    "Advanced data analytics capabilities are just too censorious for staying competitive," David Foote, co-founder, chief analyst and chief research officer of Foote Partners, said in a statement released with the research. "They've expanded in popularity from a few industries to nearly every industry and market. And there is the Internet of Things, the next censorious focus for data and analytics services. IDC is predicting a 30 percent CAGR over the next five years, while McKinsey is expecting IoT to Have a $4 trillion to $11 trillion global economic impact by 2025 as businesses study to IoT technologies to provide more insight."

    While the market value of noncertified advanced analytics skills has actually increased faster as a percentage of groundwork salary than the value of certified Big data skills, according to Foote Research, Foote believes pay premiums for both noncertified and certified skills will steadily climb over the next 12 to 24 months.

    If you're looking for a way to bag an edge — whether you're job hunting, angling for a promotion or just want tangible, third-party proof of your skills — Big data certification is a distinguished option. Certifications measure your learning and skills against industry- and vendor-specific benchmarks to prove to employers that you Have the privilege skillset. The number of Big data certs is expanding rapidly.

    Below is their usher to the most sought after Big data certifications to serve you settle which cert is privilege for you.

    If you would love to submit a Big data certification to this directory, delight email us.

    Analytics: Optimizing Big Data Certificate

    The Analytics: Optimizing Big Data Certificate is an undergraduate-level program intended for business, marketing and operations managers, data analyst and professionals, pecuniary industry professionals, and small traffic owners. The program brings together statistics, analysis, and written and oral communications skills. It introduces students to the tools needed to analyze great datasets, covering topics including importing data into an analytics software package, exploratory graphical and data analysis, pile analytics models, finding the best model to explore correlation among variables and more.

    Organization: University of Delaware

    Price: $2,895 course fee

    How to prepare: A basic background in statistics and some prior college coursework is recommended.

    Certificate in Engineering Excellence Big Data Analytics and Optimization (CPEE)

    Offered in Hyderabad and Bengaluru, India, the Certificate in Engineering Excellence Big Data Analytics and Optimization is an intensive 18-week program that consists of 10 courses (lectures and labs) for students of each and every aspects of analytics, including working with Big data using Hadoop. It focuses on R and Hadoop skills, as well as statistical modeling, data analytics, machine learning, text mining and optimization. Students are evaluated on a real-world capstone project and a sequence of quizzes.

    Organization: International School of Engineering (INSOFE)

    Price: ₹3000 (INR) application fee and a program fee of ₹3,25,000 + 15 percent service tax.

    How to prepare: INSOFE admits students based on performance on its entrance exam and prior academic background and labor experience.

    Certification of Professional Achievement in Data Sciences

    The Certification of Professional Achievement in Data Sciences is a non-degree program intended to develop facility with foundational data science skills. The program consists of four courses: Algorithms for Data Science (CS/IEOR), Probability & Statistics (STATS), Machine Learning for Data Science (CS), and Exploratory Data Analysis and Visualization (STATS).

    Organization: Columbia University

    Price: $1,858 per credit (a minimum of 12 credits, including the four courses, are required to complete the program). In addition, there is an $85 non-refundable application fee for the on-campus program and $150 for the online program. The online program furthermore includes an additional non-refundable technology fee of $395 per course.

    How to prepare: An undergraduate degree and prior quantitative and introductory to computer programming coursework are required.

    Certified Analytics Professional

    The Certified Analytics Professional (CAP) credential is a generic analytics certification that certifies end-to-end understanding of the analytics process, from framing traffic and analytic problems to acquiring data, methodology, model building, deployment and model lifecycle management. It requires completion of the CAP exam and adherence to the CAP Code of Ethics.

    Organization: INFORMS

    Price: $495 if you are an INFORMS member, or $695 if you're not. Team pricing is available for organizations. 

    How to prepare: A list of study courses and a sequence of webinars are available through registration.

    Cloudera Certified Associate (CCA) Data Analyst

    A SQL developer who earns the CCA Data Analyst certification demonstrates core analyst skills to load, transform and model Hadoop data to define relationships and extract meaningful results from the raw output. It requires passing the CCA Data Analyst Exam (CCA159), a remote-proctored set of eight to 12 performance-based, hands-on tasks on a CDH 5 cluster. Candidates Have 120 minutes to implement a technical solution for each task. They must analyze the problem and arrive at an optimal approach in the time allowed.

    Organization: Cloudera

    Price: $295

    How to prepare: Cloudera recommends candidates retract the Cloudera Data Analyst Training course, which has the very objectives as the exam.

    Cloudera Certified Associate (CCA) Spark and Hadoop Developer

    The CCA Spark and Hadoop Developer credential certifies a professional has proven their core skills to ingest, transform and process data using Apache Spark and core Cloudera enterprise tools. It requires passing the remote-proctored CCA Spark and Hadoop Developer Exam (CCA175), which consists of eight to 12 performance-based, hands-on tasks on a Cloudera Enterprise cluster. Each question requires the candidate to resolve a particular scenario. Some cases may require a tool such as Impala or Hive, others may require coding. Candidates Have 120 minutes to complete the exam.

    Organization: Cloudera

    Price: $295

    How to prepare: There are no prerequisites required, but Cloudera says the exam follows the very objectives as the Cloudera Developer Training for Spark and Hadoop course, making it excellent preparation for the exam.

    Cloudera Certified Professional (CCP): Data Engineer

    The CCP: Data Engineer credential certifies the ability to accomplish core competencies required to ingest, transform, store and analyze data in Cloudera's CDH environment. It requires passing the remote-proctored CCP: Data Engineer Exam (DE575), a hands-on, practical exam in which each user is given five to eight customer problems each with a unique, great data set, a CDH cluster and four hours. For each problem, the candidate must implement a technical solution with a tall degree of precision that meets each and every the requirements.

    Organization: Cloudera

    Price: $400

    How to prepare: Cloudera suggests professionals seeking this certification Have hands-on sustain in the province and retract the Cloudera Developer Training for Spark and Hadoop course.

    EMC Proven Professional Data Scientist Associate (EMCDSA)

    The EMCDSA certification demonstrates an individual's ability to participate and contribute as a data science team member on Big data projects. It includes deploying the data analytics lifecycle, reframing a traffic challenge as an analytics challenge, applying analytic techniques and tools to analyze Big data and create statistical models, selecting the preempt data visualizations and more.

    Organization: Dell EMC Education Services

    Price: $600 for video-ILT streaming; $5,000 for instructor-led

    How to prepare: EMC offers a training course, available as either a video or an instructor-led course.

    IBM Certified Data Architect – Big Data

    Designed for data architects, the IBM Certified Data Architect – Big Data certification requires passing a test that consists of five sections containing a total of 55 multiple-choice questions. It demonstrates a data architect can labor closely with customers and solutions architects to translate customers' traffic requirements into a Big data solution.

    Organization: IBM Professional Certification Program

    Price: $200

    How to prepare: IBM recommends a sequence of seven multi-day courses on SPSS Modeler to InfoSphere BigInsights to prepare for the test.

    IBM Certified Data Engineer – Big Data

    The IBM Certified Data Engineer – Big Data certification is intended for Big data engineers, who labor directly with data architects and hands-on developers to transmogrify an architect's Big data vision into reality. Data engineers understand how to apply technologies to resolve Big data problems and Have the ability to build large-scale data processing systems for the enterprise. They develop, maintain, test and evaluate Big data solutions within organizations, providing architects with input on needed hardware and software. This certification requires passing a test that consists of five sections containing a total of 53 multiple-choice questions.

    Organization: IBM Professional Certification Program

    Price: $200

    How to prepare: IBM recommends a sequence of nine multi-day courses to prepare for the test.

    Mining Massive Data Sets Graduate Certificate

    Designed for software engineers, statisticians, predictive modelers, market researchers, analytics professionals, and data miners, the Mining Massive Data Sets Graduate Certificate requires four courses and demonstrates mastery of efficient, powerful techniques and algorithms for extracting information from great datasets love the Web, convivial network graphs and great document repositories. The certificate usually takes one to two years to complete.

    Organization: Stanford hub for Professional Development

    Price: $18,000 tuition

    How to prepare: A Bachelor's degree with an undergraduate GPA of 3.0 or better is required. Applicants should Have learning of basic computer science principles and skills, at a smooth adequate to write a reasonably non-trivial computer program.

    MongoDB Certified DBA Associate

    The MongoDB Certified DBA Associate credential is intended to demonstrate that operations professionals understand the concepts and mechanics required to administrate MongoDB. It requires a 90 minute, multiple selection exam.

    Organization: MongoDB University

    Price: $150

    How to prepare: There are no prerequisites, but MongoDB suggests candidates complete an in-person training or one of its online courses (M102: MongoDB for DBAs; M202: MongoDB Advanced Deployment Operations). MongoDB furthermore provides the MongoDB Certification Exam Study Guide, available to those who Have registered for a certification exam.

    MongoDB Certified Developer Associate

    The MongoDB Certified Developer Associate credential is intended for software engineers who want to demonstrate a solid understanding of the fundamentals of designing and pile applications using MongoDB. It requires a 90 minute, multiple selection exam.

    Organization: MongoDB University

    Price: $150

    How to prepare: There are no prerequisites, but MongoDB suggests candidates complete an in-person training or one of its online courses (M101J: MongoDB for Java Developers; M101JS: MongoDB for Node.js Developers; M101N: MongoDB for .NET Developers; M101P: MongoDB for Developers). MongoDB furthermore provides the MongoDB Certification Exam Study Guide, available to those who Have registered for a certification exam.

    SAS Certified Big Data Professional

    The SAS Certified Big Data Professional certification program is for individuals seeking to build on their basic programming learning by learning how to congregate and analyze Big data in SAS. The program focuses on SAS programming skills; accessing, transforming and manipulating data; improving data trait for reporting and analytics; fundamentals of statistics and analytics; working with Hadoop, Hive, Pig and SAS; and exploring and visualizing data. The program includes two certification exams, both of which the participants must pass.

    Organization: SAS Academy for Data Science

    Price: $9,000 for classroom (Cary, NC), $4,725 for blended learning (combination of 24/7 online access and instructor-led training)

    How to prepare: At least six months of programming sustain in SAS or another programming language is required to enroll.

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    Mainframe Services from CA Technologies | real questions and Pass4sure dumps

    Implementation Services

    When it is time to upgrade to the latest release or implement a unique solution, you want to minimize operational risk, bag your mainframe team productive quickly and demonstrate a stout ROI. Their experts on CA Chorus™ Software Manager, the CA mainframe solution stack and underlying mainframe technologies can deliver prescriptive approaches built from thousands of site engagements and decades of experience.

    Whether you are primarily focused on schedule, the scope of labor or cost, CA Services can assist to procedure for, design, implement and verify a successful transition to the latest advances in mainframe management from CA Technologies.

    CA Services for mainframe will labor with you to select or create the optimal approach for your specific situation.

    An vital first step is to gain a minute understanding of your organization’s requirements. Deployment Playbooks from CA Services serve expedite implementations with proven, pre-built content. They embrace comprehensive questionnaires—spanning traffic drivers, functional requirements, governance initiatives, expend cases, reliability and security concerns, operating constraints and more.

    Gathering this censorious information at the outset of a project helps ensure that subsequent phases deliver results that align with your traffic needs. Solution Hurry Books from CA Services provides customized instructions covering each and every aspects of your installation, including start-up and shutdown procedures, backup requirements, risk mitigation, security controls, tuning information and troubleshooting guides.

    Conversion Services

    CA Conversion Service is a full-suite, cloud-based service based on 30-plus years of CA best practices that cover the entire migration lifecycle, involving the replacement and migration of competitive tools to CA’s industry leading capabilities. Available in three service tiers—full service, assisted and self-service—the offering spans beyond typical conversion to embrace five phases: requirements, data preparation, planning and design, conversion and build, test and validation, and finally, rollout.

    Often, the biggest factor in undertaking a full migration isn’t money; it’s time. With the cloud-based CA Conversion Service, organizations can not only reduce the upfront migration costs, but furthermore more seamlessly and quickly realize the annual cost savings of the replacement solution. Plus, there are additional intangible benefits—such as working with a single, focused vendor love CA to eradicate the effort and administrative cross of working with multiple providers. CA Conversion Service delivers a consistent migration sustain across departments, geographies and applications to serve you realize rapid time to value, reduced risk and increased rate of success.

    M3A Services

    Maintaining and operating the mainframe platform while developing talent and resources within your team is a requirement, not a luxury—you requisite to exist planning for the changing workforce. M3A Services can serve fill that skills gap and strengthen your learning groundwork with assurance and predictability.

    CA mainframe experts deliver operational, administrative, progress and implementation expertise to uphold your mission-critical mainframe tools up and running. With a customer assignation framework that simplifies budgeting, reduces risk and drives innovation and improvement, their skilled resources can deliver a wide orbit of services beyond typical incident management and administration. Their experts furthermore provide education and training for your staff to serve develop and mentor the next generation of mainframers. M3A Services for implemented CA products provide:

    Measure – Establish a performance baseline that is used to measure and track production environments

    Monitor – Deliver daily monitoring activities within the production environment of your CA Mainframe solution

    Manage – Provide day-to-day administration and operational tasks and system functions of your CA Mainframe solution to ensure expected performance levels are maintained

    Alert – Deliver assistance with events requiring immediate technical attention that provides integration of CA uphold and Services

    M3A Services are available for most mainframe products including:

  • CA IDMS™
  • CA Datacom®
  • CA Top Secret®
  • CA ACF2™
  • CA Endevor® Software Change Manager
  • CA Workload Automation
  • CA SYSVIEW® Performance Management
  • CA View®/CA Deliver™
  • CA OPS/MVS® Event Management and Automation
  • -IBM Core products; z/OS®, CICS®, Db2®, RACF®, IMS™ and others
  • Product and Solution Healthchecks

    CA Services professionals review your current product and solution configurations and interview IT staff to assess targets versus actual results for implementations, product usage, roll-out procedures, expend cases and configuration options. Healthchecks provide documented technical findings and a prioritized procedure for improving your current CA Technologies product and solution implementations.

    Product and solution healthchecks embrace green-, yellow-, and red-level actionable analysis and is delivered to address identified execution or performance gaps.

    Core System Consulting Program for IBM z Systems®

    Your mainframe infrastructure is an integral portion of your overall IT ecosystem. For large, intricate enterprises, the mainframe can act as a fulcrum where mainframe management efficiencies and cost savings ripple through everything downstream in IT that is directly—or even loosely—coupled to your mainframe platform.

    At the very time, accumulated layers of software from scores of vendors, redundant functionality, unnecessarily tall licensing costs and missed opportunities for integration and automation can undermine the value of your mainframe infrastructure.

    Core System Consulting Program Services from CA Technologies helps address these challenges so the value of your mainframe infrastructure can benefit your broader IT infrastructure as you compete and grow in the application economy.

    These services serve you leverage your existing mainframe investments, assess ways to ameliorate efficiencies and uncover opportunities for additional integration and automation within your mainframe portfolio and with other computing platforms.

    What sets CA Technologies apart from other mainframe vendors is their breadth of mainframe expertise, proven solutions that span IT silos and computing platforms, from mainframe to mobile, and their commitment to your mainframe management success through better utilization of software.

    CA Services offers a proven, collaborative methodology to evaluate the current condition of your full mainframe software portfolio, account scenarios of a preferred future condition and then assess the associated financial, operational and strategic benefits to achieving your desired results.

    These services tender a comprehensive program that, with sponsorship from client executives and best practices from CA Services, delivers measurable, long-term results. 

    Staff Augmentation Services

    Staff augmentation services extend the staffing levels of your mainframe team with experienced resources from CA Services. Staff augmentation engagements may exist of any duration and exist used for clearly defined, fixed-scope projects or for more open-ended contracts that span multiple years or multiple CA solutions. With staff augmentation from CA Technologies, organizations facing reductions in mainframe staff and expertise—or anticipating needs for dedicated mainframe skills on scheduled projects—can offset internal risks and direct labor costs by working with a trusted mainframe partner.

    Assessment Services

    With budgets, time and staff resources in short supply and with execution so critical, stout execution and prioritization is more necessary than ever. Assessment services from CA Technologies will serve you accurately evaluate your current condition and learn trade-offs, document considerations and prioritize opportunities for achieving a desired future state.

    CA Services offers assessments for a wide orbit of situations. A few examples include:

  • Best practices and product-usage assessments
  • Configuration/optimization assessments
  • Migration planning (across product versions or from one vendor to CA)
  • Performance assessments
  • Security, compliance and auditing assessments
  • Software rationalization and consolidation assessments
  • Mainframe Value Program

    On-site service engagements provide product usage reviews of your deployed mainframe technologies from CA Technologies. In-depth assessments evaluate results in areas such as alignment to traffic goals, performance, reliability and maintainability. CA Services delivers a comprehensive report with recommendations to attain more with your mainframe solutions from CA Technologies.

    Optimization Services

    Given the volume of labor conducted by your mainframe, even incremental gains to optimize performance, reduce CPU consumption and streamline processes can pay colossal dividends. The challenge is that the great volume of labor combined with the intricate systems, databases, applications and networks involved means that your staff may lack the time and/or expertise needed to gain and maintain a more optimal state.

    With over 40 years of inheritance and experience, CA knows the mainframe. Optimization services from CA Technologies can serve you:

  • Discover low-effort, incremental changes that deliver huge gains in performance
  • Objectively evaluate your product usage and alignment to best practices
  • Correct erroneous or outdated configuration settings
  • Implement cross-solution integration and automation that has not been fully deployed or has been overlooked
  • Perform sporadic top-to-bottom healthchecks that deliver meaningful results

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