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C4070-603 IBM System z Sales Solutions V6

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C4070-603 exam Dumps Source : IBM System z Sales Solutions V6

Test Code : C4070-603
Test appellation : IBM System z Sales Solutions V6
Vendor appellation : IBM
: 86 existent Questions

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IBM IBM System z Sales

IBM launches IBM Z, a revamped mainframe with pervasive statistics encryption | killexams.com existent Questions and Pass4sure dumps

IBM is making a pot huge on pervasive encryption with a brand original mainframe dubbed IBM Z that might furthermore land original workloads amid records breaches.

The company has rolled out the IBM Z, its subsequent-generation mainframe that's able to dealing with 12 billion encrypted transactions a day. The ordinary thought is that IBM Z will encrypt consummate facts consummate of the time and reduce the storm floor for businesses about ninety two %.

With the mainframe repositioning, IBM is asking to juice sales of its stalwart z system lineup. on the heart of IBM Z is an encryption engine for you to encrypt information associated with any application, cloud provider or database.

The timing is facile given the surge in data breaches and rules such as the european's universal facts insurance policy legislation. Mainframes are still regularly occurring in fiscal services.

As eu's widespread records protection law (GDPR) looms, tech providers able pitches | Video: Tech companies birth lining up their GDPR pitches |

"We deem this can breathe broadly adopted across fiscal services, govt, retail and shuttle and transportation," spoke of Ross Mauri, conventional supervisor of IBM Z. "The encryption is captious for consummate industries. This original device allows for a customer to encrypt consummate records on the mainframe. This role rose to the proper regardless of industry or country. security is a board degree issue."

IBM referred to it co-designed the IBM Z with a hundred and fifty shoppers together with protection experts and chief safety officers. The final time IBM respun the mainframe changed into when it virtualized Linux and open supply software about 15 years in the past.

Make no mistake. Mainframe earnings beget a significant beget an impact on on IBM's hardware company. there'll certainly breathe an better cycle, but what's doubtful is whether IBM can expand the attain of the IBM Z with its approach to encryption. Mauri observed IBM to this point has preached and collaborated with the base, but the enterprise brings on anywhere from 5 to fifteen original Z consumers a quarter.

Mauri spoke of the core of the equipment--utility, hardware and firmware--is always in progress about 3 years. Engineers had been engaged on the ground technologies for IBM Z for five years. "shoppers beget been engaged for greater than 2 years," illustrious Mauri.

huge Blue additionally mentioned it plans to build six IBM Cloud Blockchain records centers with IBM Z as the encryption engine. those IBM Cloud Blockchain statistics centers launched in original york, London, Frankfurt, Sao Paolo, Tokyo and Toronto to cater to the economic services sector. Mauri illustrious more blockchain centers can breathe added.

Blockchain explained in undeniable English | Why Blockchain ushers in the second technology of the cyber web | government's e reserve to imposing blockchain technology

"There are six that they beget now constructed and more in the future," referred to Mauri. "We located them world wide for latency and more for laws and data locality."

  • The pervasive encryption mode contains:
  • statistics is encrypted at relaxation and in flight wherever it resides. in addition, records can furthermore breathe encrypted in bulk given improvements in the silicon committed to the cryptographic algorithms.
  • IBM Z protects hundreds of thousands of encryption keys with tamper responding hardware that self destructs at any token of intrusion.
  • Encrypted utility programming interfaces so developers can build functions and functions.
  • As for pricing, IBM unveiled three container pricing fashions. Pricing for brand original microservices and purposes may furthermore breathe co-found in keeping with pleasant of carrier necessities. software edifice and test environments should breathe tripled so faculty can furthermore breathe raised without a license enhance. and there's pricing model for fee techniques, which is in accordance with the quantity of funds now not capability.

    These original pricing fashions may breathe available with the aid of the cease of the year for z/OS V2.2 and z/OS V2.3.

    IBM Z might breathe in a position to uphold 12 billion encrypted transactions a day, two million Docker containers and 1,000 concurrent NoSQL databases via thrice the memory of the z13 and 3x faster I/O and transaction processing.


    IBM to carry Docker commercial enterprise version for Linux on IBM techniques | killexams.com existent Questions and Pass4sure dumps

    AUSTIN, Texas, April 19, 2017 /PRNewswire/ -- IBM (NYSE: IBM) announced today at DockerCon17 plans to consequence Docker enterprise edition (EE) available for Linux on IBM z programs, LinuxONE and vigor systems to provide companies with advanced efficiency and adaptability in setting up and deploying company-critical purposes across a hybrid cloud atmosphere.

    Docker EE, a original edition of Docker's container administration platform, is designed to give developers and techniques directors a streamlined approach to building, operating and operating purposes at scale.

    Docker EE for IBM's servers provides groups with a versatile alternative for setting up and deploying purposes across their hybrid cloud infrastructure that combines public and private cloud elements. LinuxONE, z programs and energy techniques deal with business-critical purposes operating on the deepest clouds of main businesses consummate over the world.

    "Docker enterprise edition is built-in, licensed and supported to deliver businesses with essentially the most relaxed container platform for running enterprise-important applications in production at scale," referred to Roger Egan, senior vice chairman of revenue for Docker. "Availability for z methods, LinuxONE and vigour programs helps cover the whole software give chain by using together with the programs regularly at the coronary heart of an organization's IT infrastructure."

    The providing pairs Docker EE with the superior speed and scale of IBM's commercial enterprise servers. LinuxONE and z programs can uphold up to 1 million Docker containers on a single system. These programs even beget the industry's maximum degrees of security and feature advanced cryptographic accelerators developed into the hardware to encrypt facts whereas keeping extravagant levels of efficiency. vigour methods can uphold convey quicker throughput for advanced analytics and reduced latency for more responsive apps working in containers.

    "organizations necessity how to velocity edifice for core purposes devoid of sacrificing reliability, performance and security," talked about Mike Desens, vice chairman of offering administration for z techniques and LinuxONE. "groups can now select capabilities of the capabilities of z methods, LinuxONE and energy systems while profiting from the pliability of Docker enterprise edition to immediately create, check and hasten purposes."

    For extra about IBM systems, search counsel from here.

    Contact:Joe guy Collier IBM Media Relationsjgcollie@us.ibm.com +1 248 990 4707

    source IBM

    related links

    https://www.ibm.com


    IBM is speeding up encrypted transactions with its tremendous-quick IBM Z mainframe | killexams.com existent Questions and Pass4sure dumps

    IBM IS HELL BENT on dashing issues up at the moment. simply a number of months in the past, the solid introduced it's working to carry its cognitive computing product Watson to the helpdesk to extend the velocity of tech help. Now, in its pursuit of super-fast statistics switch, the company has printed plans to accelerate the tech behind encrypted transactions.

    Touted as "the next generation of the world's strongest transaction equipment", the brand original mainframe is called IBM Z and is interestingly capable of running greater than 12 billion encrypted transactions per day.

    the brand original device additionally claims to insert a leap forward encryption engine that makes it viable to encrypt consummate transactional data associated with any software, cloud service or database, which means less agonize about cyber crooks and card thieves going crazy after taking your card particulars.

    "IBM Z's original information encryption capabilities are designed to address the global epidemic of records breaches, an incredible component in the $eight trillion cyber crime beget an consequence on on the world economy through 2022," defined IBM.

    "Of the greater than nine billion data data lost or stolen considering that 2013, simplest 4 p.c were encrypted, making the immense majority of such data liable to organised cyber crime rings, status actors and employees misusing access to sensitive guidance."

    The IBM Z equipment, powered by the firm's CMOS mainframe know-how, is powered by means of what IBM calls "the industry's fastest microprocessor", operating at 5.2GHz, with a whopping 32TB of memory, and a original scalable apparatus structure that is said to bring a 35 per cent capability raise for tolerable workloads when compared to the primitive generation.

    linked: IBM makes quantum computing step forward with 'quickest' 17-qubit processor

    "[It's] probably the most gigantic re-positioning of mainframe expertise in additional than a decade," IBM noted. "where the platform embraced Linux and open source software, IBM Z now dramatically expands the protecting cryptographic umbrella of the area's most advanced encryption expertise and key coverage."

    The apparatus furthermore features cryptographic capabilities that lengthen across any statistics, networks, external gadgets or whole applications - such as the IBM Cloud Blockchain carrier - and not using a software changes and no impact on company provider stage agreements, IBM referred to. µ


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    IBM System z Sales Solutions V6

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    IBM sees cognitive solutions, tech services and cloud platform revenue declines | killexams.com existent questions and Pass4sure dumps

    IBM's third quarter revenue missed expectations as its cognitive solutions and technology services and cloud platforms units saw declines from a year ago.

    Big Blue reported earnings of $2.94 a participate on revenue of $18.8 billion, down 2 percent from a year ago. Non-GAAP earnings were $3.42 a share.

    Wall Street was expecting IBM to report third quarter earnings of $3.40 a participate on revenue of $19.1 billion.

    ibm-q3-snapshot.png

    IBM has been heavily focused on growing artificial intelligence as a business. Beyond Watson, IBM has been positioning itself as a management layer for both AI and cloud. Meanwhile, Ginni Rometty, speaking at the Gartner Symposium/ITXpo in Orlando said about AI:

    "We beget to usher these technologies into the world," Rometty said. "They will change 100% of jobs, and that is a scary thing ... They will supplant some number of jobs, but not consummate jobs."

    Also: The AI, machine learning, and data science conundrum: Who will manage the algorithms? | IBM launches tools to detect AI fairness, warp and open sources some code | What is cloud computing? Everything you necessity to know

    On the gleaming side of the third quarter, IBM said it is expanding its outrageous margins with its best performance in three years. Rometty talked up the company's strategic imperatives and engage of technologies such as AI, blockchain, analytics and security.

    While its cognitive and cloud units had overall sales declines, IBM did note that its as-a-service hasten rate is now $11.4 billion.

    By the numbers:

  • Cognitive solutions saw revenue of $4.1 billion, down 6 percent from a year ago. Watson health, security and analytics showed growth. That unit furthermore includes transaction processing software. Z middleware struggled in the quarter and cloud revenue fell 2 percent.
  • Technology services and cloud platforms delivered third quarter revenue of $8.3 billion, down 2 percent from a year ago. Cloud revenue grew, but infrastructure services, technical uphold services and integration software brought the unit down.
  • Global trade services saw revenue of $4.1 billion, up 1 percent from a year ago as consulting rebounded. Digital strategy and cognitive process transformation drove gains.
  • Systems revenue was $1.7 billion, up 1 percent, and Power and IBM Z fared well.
  • As for the outlook, IBM said it will deliver non-GAAP earnings of at least $13.80 a participate for 2018.

    The following charts highlight the affecting pieces within IBM and the overall mix.

    ibm-q3-segment-revenue.png

    ibm-q3-segment-revenue.png

    ibm-q3-strategic-imperatives.png

    ibm-q3-strategic-imperatives.png

    ibm-q3-by-product.png

    ibm-q3-by-product.png


    IBM Db2 Query Optimization Using AI | killexams.com existent questions and Pass4sure dumps

    In September 2018, IBM announced a original product, IBM Db2 AI for z/OS. This artificial intelligence engine monitors data access patterns from executing SQL statements, uses machine learning algorithms to elect on optimal patterns and passes this information to the Db2 query optimizer for exhaust by subsequent statements.

    Machine Learning on the IBM z Platform

    In May of 2018, IBM announced version 1.2 of its Machine Learning for z/OS (MLz) product. This is a hybrid zServer and cloud software suite that ingests performance data, analyzes and builds models that limn the health status of various indicators, monitors them over time and provides real-time scoring capabilities.

    Several features of this product offering are aimed at supporting a community of model developers and managers. For example:

  • It supports multiple programming languages such as Python, Scala and R. This allows data modelers and scientists to exhaust a language with which they are familiar;
  • A graphical user interface called the Visual Model Builder guides model developers without requiring highly-technical programming skills;
  • It includes multiple dashboards for monitoring model results and scoring services, as well as controlling the system configuration.
  • This machine learning suite was initially aimed at zServer-based analytics applications. One of the first obvious choices was zSystem performance monitoring and tuning. System Management Facility (SMF) records that are automatically generated by the operating system provide the raw data for system resource consumption such as central processor usage, I/O processing, memory paging and the like. IBM MLz can collect and store these data over time, and build and train models of system behavior, score those behaviors, identify patterns not readily foreseen by humans, develop key performance indicators (KPIs) and then feed the model results back into the system to affect system configuration changes that can better performance.

    The next step was to implement this suite to dissect Db2 performance data. One solution, called the IBM Db2 IT Operational Analytics (Db2 ITOA) solution template, applies the machine learning technology to Db2 operational data to gain an understanding of Db2 subsystem health. It can dynamically build baselines for key performance indicators, provide a dashboard of these KPIs and give operational staff real-time insight into Db2 operations.

    While generic Db2 subsystem performance is an needful factor in overall application health and performance, IBM estimates that the DBA uphold staff spends 25% or more of its time, " ... fighting access path problems which antecedent performance degradation and service impact.". (See Reference 1).

    AI Comes to Db2

    Consider the plight of modern DBAs in a Db2 environment. In today's IT world they must uphold one or more Big data applications, cloud application and database services, software installation and configuration, Db2 subsystem and application performance tuning, database definition and management, catastrophe recovery planning, and more. Query tuning has been in being since the origins of the database, and DBAs are usually tasked with this as well.

    The heart of query path analysis in Db2 is the Optimizer. It accepts SQL statements from applications, verifies authority to access the data, reviews the locations of the objects to breathe accessed and develops a list of candidate data access paths. These access paths can embrace indexes, table scans, various table connect methods and others. In the data warehouse and Big data environments there are usually additional choices available. One of these is the being of summary tables (sometimes called materialized query tables) that contain pre-summarized or aggregated data, thus allowing Db2 to avoid re-aggregation processing. Another option is the starjoin access path, common in the data warehouse, where the order of table joins is changed for performance reasons.

    The Optimizer then reviews the candidate access paths and chooses the access path, "with the lowest cost." Cost in this context means a weighted summation of resource usage including CPU, I/O, memory and other resources. Finally, the Optimizer takes the lowest cost access path, stores it in memory (and, optionally, in the Db2 Directory) and begins access path execution.

    Big data and data warehouse operations now embrace software suites that allow the trade analyst to exhaust a graphical interface to build and maneuver a miniature data model of the data they wish to analyze. The packages then generate SQL statements based on the users’ requests.

    The Problem for the DBA

    In order to execute pleasurable analytics on your multiple data stores you necessity a pleasurable understanding of the data requirements, an understanding of the analytical functions and algorithms available and a high-performance data infrastructure. Regrettably, the number and location of data sources is expanding (both in size and in geography), data sizes are growing, and applications continue to proliferate in number and complexity. How should IT managers uphold this environment, especially with the most experienced and age staff nearing retirement?

    Understand furthermore that a great section of reducing the total cost of ownership of these systems is to acquire Db2 applications to hasten faster and more efficiently. This usually translates into using fewer CPU cycles, doing fewer I/Os and transporting less data across the network. Since it is often difficult to even identify which applications could benefit from performance tuning, one approach is to automate the detection and correction of tuning issues. This is where machine learning and artificial intelligence can breathe used to considerable effect.

    Db2 12 for z/OS and artificial Intelligence

    Db2 version 12 on z/OS uses the machine learning facilities mentioned above to congregate and store SQL query text and access path details, as well as actual performance-related historical information such as CPU time used, elapsed times and result set sizes. This offering, described as Db2 AI for z/OS, analyzes and stores the data in machine learning models, with the model analysis results then being scored and made available to the Db2 Optimizer. The next time a scored SQL statement is encountered, the Optimizer can then exhaust the model scoring data as input to its access path election algorithm.

    The result should breathe a reduction in CPU consumption as the Optimizer uses model scoring input to elect better access paths. This then lowers CPU costs and speeds application response times. A significant handicap is that using AI software does not require the DBA to beget data science skills or profound insights into query tuning methodologies. The Optimizer now chooses the best access paths based not only on SQL query syntax and data distribution statistics but on modelled and scored historical performance.

    This can breathe particularly needful if you store data in multiple places. For example, many analytical queries against Big data require concurrent access to unavoidable data warehouse tables. These tables are commonly called dimension tables, and they contain the data elements usually used to control subsetting and aggregation. For example, in a retail environment admiration a table called StoreLocation that enumerates every store and its location code. Queries against store sales data may wish to aggregate or summarize sales by Location; hence, the StoreLocation table will breathe used by some Big data queries. In this environment it is common to select the dimension tables and copy them regularly to the Big data application. In the IBM world this location is the IBM Db2 Analytics Accelerator (IDAA).

    Now deem about SQL queries from both operational applications, data warehouse users and Big data trade analysts. From Db2's perspective, consummate these queries are equal, and are forwarded to the Optimizer. However, in the case of operational queries and warehouse queries they should most likely breathe directed to access the StoreLocation table in the warehouse. On the other hand, the query from the trade analyst against Big data tables should probably access the copy of the table there. This results in a proliferations of potential access paths, and more toil for the Optimizer. Luckily, Db2 AI for z/OS can provide the Optimizer the information it needs to consequence smart access path selections.

    How It Works

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

  • During a bind, rebind, prepare or intricate operation, an SQL statement is passed to the Optimizer;
  • The Optimizer chooses the data access path; as the election is made, Db2 AI captures the SQL syntax, access path election and query performance statistics (CPU used, etc.) and passes it to a "learning task";
  • The learning task, which can breathe executed on a zIIP processor (a non-general-purpose CPU core that does not factor into software licensing charges), interfaces with the machine learning software (MLz Model Services) to store this information in a model;
  • As the amount of data in each model grows, the MLz Scoring Service (which furthermore can breathe executed on a zIIP processor) analyzes the model data and scores the behavior;
  • During the next bind, rebind, prepare or explain, the Optimizer now has access to the scoring for SQL models, and makes confiscate changes to access path choices.
  • There are furthermore various user interfaces that give the administrator visibility to the status of the accumulated SQL statement performance data and model scoring.

    Summary

    IBM's machine learning for zOS (MLz) offering is being used to considerable consequence in Db2 version 12 to better the performance of analytical queries as well as operational queries and their associated applications. This requires management attention, as you must verify that your trade is prepared to consume these ML and AI conclusions. How will you measure the costs and benefits of using machine learning? Which IT uphold staff must breathe tasked to reviewing the result of model scoring, and perhaps approving (or overriding) the results? How will you review and warrant the assumptions that the software makes about access path choices?

    In other words, how well execute you know your data, its distribution, its integrity and your current and proposed access paths? This will determine where the DBAs expend their time in supporting analytics and operational application performance.

    # # #

    Reference 1

    John Campbell, IBM Db2 Distinguished EngineerFrom "IBM Db2 AI for z/OS: Boost IBM Db2 application performance with machine learning"https://www.worldofdb2.com/events/ibm-db2-ai-for-z-os-boost-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

    See consummate articles by Lockwood Lyon


    Big Deal for Big Blue: IBM Is Buying Red Hat for $34B | killexams.com existent questions and Pass4sure dumps

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    In a bombshell scramble over the weekend, IBM announced that it would acquire Red Hat in a deal worth $34B. Big Blue announced that it would tender $190 per participate of Red Hat in a cash transaction that represents a substantial premium over the latter’s current valuation. Red Hat stock closed at just $116.68 on Friday and was down slightly terminal week after missing analyst estimates, though the company increased subscription revenue by 20 percent.

    This deal is the largest ever for an open source company and the third-largest tech deal ever.

    “The acquisition of Red Hat is a game-changer. It changes everything about the cloud market,” said IBM chair and CEO Ginni Rometty. “IBM will become the world’s #1 hybrid cloud provider, offering companies the only open cloud solution that will unlock the full value of the cloud for their businesses.

    “Most companies today are only 20 percent along their cloud journey, renting compute power to Cut costs,” she said. “The next 80 percent is about unlocking existent trade value and driving growth. This is the next chapter of the cloud. It requires shifting trade applications to hybrid cloud, extracting more data and optimizing every section of the business, from supply chains to sales.”

    IBM is clearly playing up the cloud software angle rather than Red Hat’s 25 years of promoting and developing Red Hat Enterprise Linux. The word “cloud” appears 38 times in IBM’s press release announcing the deal. The word “Linux” appears 3 times.

    It’s tricky to acquire a sense of how this will impact IBM’s product offerings, in section because IBM is rather difficult to analyze. Next Platform breaks down some of how IBM deliberately obfuscates some of its trade segment reporting by mixing software and hardware in the same categories.

    Credit: Next Platform

    IBM has made a major shove into providing cloud infrastructure with its IBM Cloud Private service, but it’s not pellucid if the company intends to shove into this space with its own hardware. While the company offers both System z and Power-derived cloud options, Next Platform reports that the bulk of the company’s offerings are apparently x86-based.

    Pushing into cloud services echoes the toil that companies like Microsoft and Amazon beget been doing, and may breathe an needful future revenue source. And Red Hat has its own subscription service generating hundreds of millions of dollars of revenue already. That’s an needful asset to IBM in and of itself — the company has been on a downward revenue trend for years. The company’s revenues fell in its most recent quarter after three quarters of growth — but those three quarters were preceded by five years of unhurried decline.

    Bets on Watson haven’t paid off to date despite huge investments, and the thinking is that IBM may breathe looking for a different angle and mode of improving its own bottom line. The company has apparently decided to consequence a huge pot on cloud services and Red Hat’s expertise in the hopes of improving its own near-term outlook. There may furthermore breathe hoped-for synergies simply in owning one of the most needful developers of Linux and ensuring that future Linux-based cloud offerings are optimally tuned for IBM’s own products. It’s not pellucid how this will impact the progress of its AI and machine learning projects; IBM has previously done toil in helping companies hasten AI and ML workloads on their own hardware.

    Now Read: IBM Unveils 19TB SSD With Everspin MRAM Data Cache, IBM Watson Recommends Unsafe Cancer Treatments, and Floating IBM Robot Ships Out to International Space Station



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