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000-N07 - IBM Optimization Technical Mastery Test v1 - Dump Information

Vendor : IBM
Exam Code : 000-N07
Exam Name : IBM Optimization Technical Mastery Test v1
Questions and Answers : 30 Q & A
Updated On : April 24, 2019
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000-N07 Questions and Answers

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000-N07 IBM Optimization Technical Mastery Test v1

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000-N07 exam Dumps Source : IBM Optimization Technical Mastery Test v1

Test Code : 000-N07
Test Name : IBM Optimization Technical Mastery Test v1
Vendor Name : IBM
Q&A : 30 Real Questions

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IBM IBM Optimization Technical Mastery

Sandvik and IBM usher in the Fourth Industrial Revolution to the Mining industry with IBM Watson | killexams.com Real Questions and Pass4sure dumps

Barminco, Hindustan Zinc, Petra Diamonds and Vedanta Zinc foreign faucet into the Sandvik and IBM relationship to improve operations and safety in underground challenging-rock mining

Award-profitable OptiMine® Analytics with IBM Watson IoT for predictive protection and optimization, analyzes, learns and communicates with gadget operating heaps of feet underground

TAMPERE, Finland and ARMONK, N.Y., April 1, 2019 /PRNewswire/ -- Joint customers of IBM (NYSE: IBM) and Sandvik Mining and Rock expertise, one of the world's biggest premium mining machine producers, are tapping the powers of IoT, advanced analytics and artificial intelligence to recognise security, maintenance, productivity and operational efficiency.

The mining and rock excavation business is beneath growing power to boost the global give of minerals to fulfill the needs and expectations of a rapidly rising world inhabitants. This frequently requires extracting from increasing enhanced depths, which could make it intricate to speak and act as integral when device fails or has to be serviced.

OptiMine® Analytics transforms records into process advancements by the use of predictive insights and actionable dashboards embedded into operation administration methods. the usage of the analytics capabilities from IBM Watson IoT, this counsel management answer makes it possible for mining corporations to combine machine and utility information from disparate sources in actual-time, analyzing patterns within the information to help enrich availability, utilization and efficiency.

via a collection of IBM Design considering workshops, IBM and Sandvik work with purchasers to increase a framework to form offerings round statistics driven productivity and predictive maintenance. the use of the Watson IoT know-how, Sandvik and IBM have jointly created a platform in a position to agree to the stringent reliability and security necessities of mining operations. Predictive protection technology leveraging IoT sensor facts has additionally been introduced as part of this platform.

"Proactively selecting preservation wants before anything breaks is resulting in large can charge and time discounts," noted Patrick Murphy, president, Rock Drills & applied sciences, Sandvik. "Our award-profitable OptiMine® Analytics with IBM Watson IoT options present our purchasers a extra complete view of their operations for smarter, safer and greater productive work."

Sandvik and IBM consumers similar to Petra Diamonds and Barminco are using IoT to assist in the reduction of miner exposure to hostile work environments and boost security.

"Our excellent precedence is the security of our employees and if a laptop fails underground, we need instant perception into what is going on in that tunnel," pointed out Luctor Roode, government operations at Petra Diamonds. "With the solution from Sandvik and IBM, we have real-time records that permits us to automatically determine the root reason for the issue and act for this reason." 

"Leveraging information is turn into increasingly valuable across the mining sector. through analytics, computer learning and AI, we are seeing new percentages for increased operational effectivity," observed Paul Muller, chief executive officer, Barminco. "Our partnership with Sandvik's OptiMine® Analytics permits us to fast-song our efforts, leveraging Sandvik's entire-of-fleet data and innate computer expertise."

OptiMine® Analytics will also be used by way of Vedanta Zinc foreign's Black Mountain Mining (BMM) operations in South Africa's Northern Cape Province, to accelerate information-pushed operations for protection, effectivity and productivity for vehicles, loaders and drills. additionally, Hindustan Zinc, one of the most world's greatest integrated producers of zinc, lead and silver has tapped Sandvik to enforce a big digital transformation at its Sindesar Khurd Mine, India, to make certain all required infrastructure and structures can obtain world-category mining safety, effectivity and productiveness.

"Sensors and monitoring programs for asset management is simply the starting when it involves how artificial intelligence will disrupt the mining business," stated Jay Bellissimo, everyday manager, Cognitive manner Transformation, IBM world enterprise features. "growing an answer that turns the statistics into actionable insights is a delicate matter. It requires an interdisciplinary effort spanning across mining know-how, application engineering and statistics science. IBM and Sandvik are now on path to help transform the mining price chain with the fusion of cognitive capabilities into miners business and working procedures."

Story continues

Sandvik has been delivering solutions within the mining automation enterprise for many years, with self sufficient operations in more than 60 mines on six continents. This footprint is a huge asset to the technique optimization solutions in greater and better demand. For its part, IBM has been working with leading mining valued clientele to infuse cognitive capabilities of their enterprise and operating approaches, growing the Cognitive cost Chain for Mining. This multidisciplinary strategy leverages and expands on the concepts of the fourth industrial revolution via helping miners obtain new effectivity rate reductions, while not having to make tremendous-scale capital investments.  

Sandvik community Sandvik is a high-tech and international engineering community providing items and services that raise customer productiveness, profitability and security. We hang world-main positions in chosen areas – equipment and tooling techniques for steel slicing; machine and equipment, service and technical solutions for the mining business and rock excavation within the development industry; items in superior stainless steels and special alloys as well as items for industrial heating. In 2018, the neighborhood had about forty two,000 personnel and revenues of about one hundred billion SEK in more than 160 international locations within carrying on with operations.

Sandvik Mining and Rock expertise Sandvik Mining and Rock technology is a company enviornment inside the Sandvik community and a world leading business enterprise of equipment and tools, carrier and technical solutions for the mining and development industries. application areas consist of rock drilling, rock chopping, crushing and screening, loading and hauling, tunneling, quarrying and breaking and demolition. In 2018, revenue had been approximately forty three billion SEK with about 15,000 employees in continuing operations.

About IBM For more assistance about IBM capabilities please consult with: https://www.ibm.com/features

Contact:Jeannine Kilbride1-860-997-6277jkilbri@us.ibm.com

IBM company emblem. (PRNewsfoto/IBM)

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

In September 2018, IBM announced a new product, IBM Db2 AI for z/OS. This artificial intelligence engine displays statistics access patterns from executing SQL statements, uses computer gaining knowledge of algorithms to decide upon top of the line patterns and passes this suggestions to the Db2 question optimizer to be used by using subsequent statements.

machine gaining knowledge of on the IBM z Platform

In may also of 2018, IBM announced edition 1.2 of its laptop gaining knowledge of for z/OS (MLz) product. this is a hybrid zServer and cloud utility suite that ingests efficiency facts, analyzes and builds models that signify the health repute of various indicators, monitors them over time and offers actual-time scoring capabilities.

a couple of features of this product providing are geared toward helping a neighborhood of model developers and managers. for example:

  • It supports distinctive programming languages equivalent to Python, Scala and R. This makes it possible for statistics modelers and scientists to use a language with which they are universal;
  • A graphical user interface referred to as the visual model Builder publications model builders with out requiring tremendously-technical programming competencies;
  • It contains distinct dashboards for monitoring mannequin consequences and scoring services, in addition to controlling the gadget configuration.
  • This desktop learning suite become at the beginning aimed toward zServer-based mostly analytics applications. some of the first evident choices was zSystem efficiency monitoring and tuning. gadget management Facility (SMF) statistics which are immediately generated by means of the working equipment provide the raw facts for equipment resource consumption comparable to imperative processor utilization, I/O processing, memory paging etc. IBM MLz can assemble and keep these records over time, and build and instruct fashions of gadget conduct, ranking those behaviors, determine patterns no longer quite simply foreseen by using humans, advance key efficiency symptoms (KPIs) and then feed the mannequin effects back into the equipment to affect system configuration adjustments that may improve efficiency.

    The next step turned into to put in force this suite to analyze Db2 efficiency facts. One answer, known as the IBM Db2 IT Operational Analytics (Db2 ITOA) answer template, applies the computer gaining knowledge of expertise to Db2 operational information to benefit an figuring out of Db2 subsystem fitness. it could possibly dynamically construct baselines for key performance warning signs, give a dashboard of those KPIs and provides operational staff true-time perception into Db2 operations.

    whereas universal Db2 subsystem efficiency is a vital factor in universal software fitness and efficiency, IBM estimates that the DBA guide workforce spends 25% or greater of its time, " ... fighting entry path complications which trigger performance degradation and service impact.". (See Reference 1).

    AI comes to Db2

    agree with the plight of contemporary DBAs in a Db2 ambiance. In modern IT world they have to aid one or more big statistics functions, cloud utility and database services, application installation and configuration, Db2 subsystem and software efficiency tuning, database definition and management, catastrophe healing planning, and more. question tuning has been in existence due to the fact that the origins of the database, and DBAs are continually tasked with this as neatly.

    The heart of query direction evaluation in Db2 is the Optimizer. It accepts SQL statements from applications, verifies authority to entry the records, studies the areas of the objects to be accessed and develops a list of candidate information access paths. These access paths can include indexes, table scans, numerous table be a part of strategies and others. within the facts warehouse and massive information environments there are usually additional choices accessible. One of these is the existence of summary tables (on occasion referred to as materialized question tables) that contain pre-summarized or aggregated information, as a result permitting Db2 to evade re-aggregation processing. one more option is the starjoin entry course, ordinary within the records warehouse, the place the order of table joins is modified for performance causes.

    The Optimizer then reviews the candidate access paths and chooses the entry direction, "with the lowest cost." charge during this context ability a weighted summation of aid utilization including CPU, I/O, memory and different materials. finally, the Optimizer takes the bottom cost entry path, outlets it in reminiscence (and, optionally, in the Db2 listing) and begins access direction execution.

    huge information and data warehouse operations now consist of application suites that enable the business analyst to use a graphical interface to construct and manipulate a miniature records mannequin of the data they are looking to analyze. The applications then generate SQL statements in keeping with the clients’ requests.

    The issue for the DBA

    in order to do respectable analytics to your numerous information stores you want an outstanding realizing of the records necessities, an realizing of the analytical functions and algorithms purchasable and a excessive-efficiency facts infrastructure. sadly, the number and location of information sources is expanding (both in size and in geography), data sizes are becoming, and functions continue to proliferate in quantity and complexity. How should still IT managers support this ambiance, primarily with essentially the most experienced and mature group of workers nearing retirement?

    take into account additionally that a huge part of cutting back the overall cost of possession of these methods is to get Db2 functions to run quicker and greater successfully. This continually interprets into the usage of fewer CPU cycles, doing fewer I/Os and transporting less information throughout the community. for the reason that it is regularly difficult to even determine which applications may advantage from efficiency tuning, one approach is to automate the detection and correction of tuning issues. here's the place desktop researching and artificial intelligence can be used to exquisite impact.

    Db2 12 for z/OS and artificial Intelligence

    Db2 edition 12 on z/OS makes use of the computing device gaining knowledge of facilities outlined above to collect and keep SQL query textual content and access direction particulars, in addition to specific efficiency-connected historic suggestions akin to CPU time used, elapsed times and outcome set sizes. This offering, described as Db2 AI for z/OS, analyzes and outlets the information in machine learning models, with the mannequin analysis effects then being scored and made attainable to the Db2 Optimizer. The subsequent time a scored SQL statement is encountered, the Optimizer can then use the mannequin scoring records as enter to its access path option algorithm.

    The outcome may still be a discount in CPU consumption because the Optimizer makes use of mannequin scoring enter to select stronger entry paths. This then lowers CPU charges and speeds application response instances. a big potential is that the usage of AI application does not require the DBA to have facts science abilities or deep insights into query tuning methodologies. The Optimizer now chooses the gold standard entry paths based no longer simplest on SQL query syntax and data distribution facts however on modelled and scored historic performance.

    This can be in particular critical in case you keep information in dissimilar areas. as an example, many analytical queries in opposition t huge information require concurrent entry to certain facts warehouse tables. These tables are commonly referred to as dimension tables, and they contain the information features usually used to manage subsetting and aggregation. for example, in a retail environment believe a desk known as StoreLocation that enumerates every keep and its vicinity code. Queries towards shop sales information might also need to aggregate or summarize earnings by using region; hence, the StoreLocation table could be used through some big information queries. during this environment it is common to take the dimension tables and copy them always to the large statistics utility. within the IBM world this place is the IBM Db2 Analytics Accelerator (IDAA).

    Now consider about SQL queries from each operational functions, statistics warehouse users and massive statistics enterprise analysts. From Db2's perspective, all these queries are equal, and are forwarded to the Optimizer. however, in the case of operational queries and warehouse queries they should still definitely be directed to entry the StoreLocation desk in the warehouse. even so, the query from the company analyst towards huge facts tables may still doubtless entry the copy of the table there. This effects in a proliferations of advantage entry paths, and extra work for the Optimizer. thankfully, Db2 AI for z/OS can deliver the Optimizer the suggestions it must make sensible entry direction choices.

    how it Works

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

  • all over a bind, rebind, put together or explain operation, an SQL observation is handed to the Optimizer;
  • The Optimizer chooses the statistics access route; because the option is made, Db2 AI captures the SQL syntax, access path alternative and query efficiency facts (CPU used, and so forth.) and passes it to a "gaining knowledge of assignment";
  • The studying project, which will also be performed on a zIIP processor (a non-regular-aim CPU core that does not component into software licensing prices), interfaces with the computer researching application (MLz mannequin services) to store this guidance in a mannequin;
  • as the quantity of facts in every model grows, the MLz Scoring carrier (which also can be finished on a zIIP processor) analyzes the mannequin statistics and rankings the habits;
  • all the way through the subsequent bind, rebind, prepare or explain, the Optimizer now has entry to the scoring for SQL models, and makes acceptable changes to entry course decisions.
  • There are additionally a lot of consumer interfaces that provide the administrator visibility to the status of the collected SQL remark performance records and mannequin scoring.

    abstract

    IBM's computing device gaining knowledge of for zOS (MLz) providing is being used to remarkable impact in Db2 edition 12 to enrich the performance of analytical queries in addition to operational queries and their associated applications. This requires management consideration, as you have to check that your enterprise is ready to consume these ML and AI conclusions. How will you measure the prices and advantages of using computer getting to know? Which IT support team of workers should be tasked to reviewing the outcome of mannequin scoring, and perhaps approving (or overriding) the effects? How will you evaluation and justify the assumptions that the application makes about access path selections?

    In other words, how well did you know your statistics, its distribution, its integrity and your present and proposed entry paths? this may check the place the DBAs spend their time in aiding analytics and operational software efficiency.

    # # #

    Reference 1

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

    Reference 2

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

    See all articles with the aid of Lockwood Lyon


    IBM particulars Channel Plans For Netezza facts Warehouse appliances | killexams.com Real Questions and Pass4sure dumps

    statistics warehouse home equipment

    The circulate will give resellers with a number sales, advertising and technical substances that IBM stated will make it less difficult to market and sell Netezza systems. IBM is additionally providing new financing alternatives to channel companions who resell the Netezza appliances, including zero-percent financing and versatile payment alternatives for purchasers.

    while Netezza largely bought its records warehouse appliances direct to purchasers, IBM has had its eye on the channel for promoting Netezza items considering the fact that it obtained the company in November for $1.7 billion. at the Netezza person conference in June IBM executives unveiled a associate recruitment effort for Netezza and noted they expect the channel to account for 50 p.c of Netezza earnings within 4 years.

    "enterprise analytics is going mainstream and IBM's purpose is to arm its partners with the correct skills and guide to assist our clients take abilities of this vogue," noted Arvind Krishna, widely wide-spread supervisor of IBM tips administration, in an announcement. "These [new&#ninety three; materials are geared to make it effortless for our partners to at once infuse Netezza into their business mannequin."

    IBM has identified business analytics as one in all its strategic initiatives and has forecast that business analytics and optimization items and functions will generate $16 billion in annual earnings for the enterprise by 2015.

    Netezza's methods are according to IBM's BladeCenter servers.

    Channel partners should be licensed to resell IBM items that come under the utility value Plus (SVP) program. Authorization requirements encompass having at the least two personnel who've passed a technical mastery exam and one who has handed a earnings mastery examination.

    Resellers who qualify for the SVP program are eligible for co-advertising funds for lead generation and different market planning assistance. IBM additionally offers partners a talents bootcamp where personnel can train on a way to install, control and keep Netezza methods. And SVP-member resellers can carry income potentialities into IBM Innovation facilities to verify-force Netezza items.

    beginning Oct. 1 the Netezza products also will come under IBM's software price Incentive program, which provides monetary rewards for companions who identify and develop sales alternatives, however don't always tackle product fulfillment.

    On the financing aspect companions can offer zero-% financing via IBM world Financing to credit-qualified clients for Netezza purchases. additionally purchasable is 24- and 36-month financing with alternatives that allow valued clientele healthy payments to anticipated cash flows.

    And companions can rent a Netezza gadget for twenty-four months to run inside their personal records facilities for demonstration, construction, trying out and practising purposes, IBM pointed out.

    Charlotte, N.C.-primarily based options provider and IBM partner Fuzzy Logix, which resources predictive analytics software and functions to valued clientele, "will use these elements from IBM to find international enterprise opportunities and deliver bigger price features to our clients," said COO Mike Upchurch, in a press release.


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    Your guide to the top big data certifications today | killexams.com real questions and Pass4sure dumps

    IDG

    IDG

    Data and big data analytics are fast becoming the lifeblood of any successful business. Getting the technology right can be challenging, but building the right team with the right skills to undertake big data initiatives can be even harder.

    Not surprisingly, that challenge is reflected in the rising demand 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 average 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 found 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 also need 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. | Get ahead with the top certs for big data, project management, agile, and the cloud. | Get weekly career tips by signing up for our CIO Leader newsletter. ]

    These skills are in high demand and are relatively rare. Individuals with the right mix of experience and skills can demand high salaries. The right certifications can help.

    "Advanced data analytics capabilities are just too critical 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 critical 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 look to IoT technologies to provide more insight."

    While the market value of noncertified advanced analytics skills has actually increased faster as a percentage of base 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 rise over the next 12 to 24 months.

    If you're looking for a way to get 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 great option. Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers that you have the right skillset. The number of big data certs is expanding rapidly.

    Below is our guide to the most sought after big data certifications to help you decide which cert is right for you.

    If you would like to submit a big data certification to this directory, please 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, financial industry professionals, and small business owners. The program brings together statistics, analysis, and written and oral communications skills. It introduces students to the tools needed to analyze large datasets, covering topics including importing data into an analytics software package, exploratory graphical and data analysis, building 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 all 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 series 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 work 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 also 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 general analytics certification that certifies end-to-end understanding of the analytics process, from framing business 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 series 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 take the Cloudera Data Analyst Training course, which has the same 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 solve 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 same 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 perform 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, large data set, a CDH cluster and four hours. For each problem, the candidate must implement a technical solution with a high degree of precision that meets all the requirements.

    Organization: Cloudera

    Price: $400

    How to prepare: Cloudera suggests professionals seeking this certification have hands-on experience in the field and take 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 business challenge as an analytics challenge, applying analytic techniques and tools to analyze big data and create statistical models, selecting the appropriate 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 work closely with customers and solutions architects to translate customers' business requirements into a big data solution.

    Organization: IBM Professional Certification Program

    Price: $200

    How to prepare: IBM recommends a series 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 work directly with data architects and hands-on developers to convert an architect's big data vision into reality. Data engineers understand how to apply technologies to solve 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 series 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 large datasets like the Web, social network graphs and large document repositories. The certificate usually takes one to two years to complete.

    Organization: Stanford Center 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 knowledge of basic computer science principles and skills, at a level sufficient 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 choice 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 also 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 building applications using MongoDB. It requires a 90 minute, multiple choice 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 also 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 knowledge by learning how to gather and analyze big data in SAS. The program focuses on SAS programming skills; accessing, transforming and manipulating data; improving data quality 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 experience in SAS or another programming language is required to enroll.

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    Mainframe Services from CA Technologies | killexams.com real questions and Pass4sure dumps

    Implementation Services

    When it is time to upgrade to the latest release or implement a new solution, you want to minimize operational risk, get your mainframe team productive quickly and demonstrate a strong ROI. Our 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 work or cost, CA Services can assist to plan for, design, implement and verify a successful transition to the latest advances in mainframe management from CA Technologies.

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

    An important first step is to gain a detailed understanding of your organization’s requirements. Deployment Playbooks from CA Services help expedite implementations with proven, pre-built content. They include comprehensive questionnaires—spanning business drivers, functional requirements, governance initiatives, use cases, reliability and security concerns, operating constraints and more.

    Gathering this critical information at the outset of a project helps ensure that subsequent phases deliver results that align with your business needs. Solution Run Books from CA Services provides customized instructions covering all 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 include 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 also 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 like CA to eliminate the effort and administrative burden of working with multiple providers. CA Conversion Service delivers a consistent migration experience across departments, geographies and applications to help you realize fast 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 need to be planning for the changing workforce. M3A Services can help fill that skills gap and strengthen your knowledge base with confidence and predictability.

    CA mainframe experts deliver operational, administrative, development and implementation expertise to keep your mission-critical mainframe tools up and running. With a customer engagement framework that simplifies budgeting, reduces risk and drives innovation and improvement, our skilled resources can deliver a wide range of services beyond typical incident management and administration. Our experts also provide education and training for your staff to help 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 Support 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, use cases and configuration options. Healthchecks provide documented technical findings and a prioritized plan for improving your current CA Technologies product and solution implementations.

    Product and solution healthchecks include 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 part of your overall IT ecosystem. For large, complex 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 same time, accumulated layers of software from scores of vendors, redundant functionality, unnecessarily high 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 help you leverage your existing mainframe investments, assess ways to improve 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 our breadth of mainframe expertise, proven solutions that span IT silos and computing platforms, from mainframe to mobile, and our commitment to your mainframe management success through better utilization of software.

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

    These services offer 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 be of any duration and be 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, strong execution and prioritization is more necessary than ever. Assessment services from CA Technologies will help you accurately evaluate your current state and discover trade-offs, document considerations and prioritize opportunities for achieving a desired future state.

    CA Services offers assessments for a wide range 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)
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  • 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 business goals, performance, reliability and maintainability. CA Services delivers a comprehensive report with recommendations to do more with your mainframe solutions from CA Technologies.

    Optimization Services

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

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  • Session descriptions and details - SWPC2012 | killexams.com real questions and Pass4sure dumps

    Multithreading and multiprocessing

    Thursday and Friday, April 19-20, 2012 - @Sterre Building S9 : April 19 lecture room V1 (first floor) - April 20 Lecture room V3 (third floor).

    Georg Hager and Jan Treibig (HPC services, Erlangen Regional Computing Center, Germany)

    Chairs: Kenneth Hoste, Stijn De Weirdt

    This course gives an introduction to shared-memory parallel programming and optimization on modern multicore systems. The main focus is on OpenMP, which is the dominant shared-memory programming model in computational science, but alternative approaches are also discussed.

    After an introduction to parallelism and multicore architecture and to the most important shared-memory programming models we give a solid account of OpenMP and its use in multicore-based systems. Then we describe the dominant performance issues in shared-memory programming, like synchronization overhead, ccNUMA locality, and bandwidth saturation (in cache and memory) in order to pinpoint the influence of system topology and thread affinity on the performance of typical parallel programming constructs. Multiple ways of probing system topology and establishing affinity, either by explicit coding or separate tools, are demonstrated. The basic use of hardware counter measurements for performance analysis is discussed. Finally we elaborate on programming techniques that help establish optimal parallel memory access patterns and/or cache reuse, with an emphasis on leveraging shared caches for improving performance. Hands-on exercises allow the students to apply the concepts right away.

    Georg Hager holds a PhD in computational physics from the University of Greifswald. He has been working with high performance systems since 1995, and is now a senior research scientist in the HPC group at Erlangen Regional Computing Center (RRZE). Recent research includes architecture-specific optimization for current microprocessors, performance modeling on processor and system levels, and the efficient use of hybrid parallel systems. See his blog at http://blogs.fau.de/hager for current activities, publications, and talks.

    Jan Treibig is a chemical engineer with a special focus on computational fluid dynamics and technical thermodynamics. He holds a PhD in computer science from the University of Erlangen-Nuremberg, and has worked for two years in the embedded automotive software industry as software developer, test engineer and quality manager. Since 2008 he is a postdoctoral researcher in the HPC group at Erlangen Regional Computing Center Erlangen (RRZE). His research activities revolve around low-level and architecture-specific optimization and performance modeling. He is also the author of the LIKWID tool suite, a set of command line tools created to support developers of high-performance multithreaded codes.

    Prior knowledge: UNIX/Linux skills are required, since we will be working with Linux systems in the hands-on sessions. Students should also have some programming experience with one of the dominant HPC languages: C, C++, or Fortran.

    Recommended reading:

    Info on how to subscribe.

    GPGPU: considerations for parallelizing code with CUDA

    Friday April 27, 2012 - @Het Pand - Zaal Oude Infirmerie

    Carsten Griwodz (University of Oslo, Norway)

    Chairs: Ruben De Visscher, Peter Dawyndt

    The steadily increasing demand for computing power in all sectors is today addressed by multi-core chips, to the extent that even mobile phones can now be considered multi-core computers. Along the way, a particular kind of support hardware, the graphics processing unit, has attracted programmers' attention because it provides processing power that exceeds that of the CPUs and is available at relatively low cost. When used effectively, existing GPUs can contribute several times the processing power of a CPU to the processing of resource-demanding workloads. Using them effectively, however, is a bigger challenge than using CPUs. Designed for computing and rendering the pixels of complex visual scenes as efficiently as possible, they feature wide parallel processing pipelines, with very limited means for data exchange and synchronization between threads and I/O with other units. Their architectural specialization combined with their high raw computing power require that programmers consider how to combine them with the available CPU resources and to make separate algorithmic choices for both, CPU and GPU. This course is meant to provide an insight into the challenges and potential of GPU programming using the CUDA programming framework for NVidia graphics cards as an example.

    Carsten Griwodz is the department leader at the Simula Research Laboratory and a Professor at the Department of Informatics at the University of Oslo, Norway. He is interested in issues of scalability for multimedia applications. His main research interest is the improvement of mechanisms and algorithms for media servers, interactive distributed multimedia and distribution systems. From 1993 to 1997, he worked at the IBM European Networking Center in Heidelberg, Germany. In 1997, he joined the Multimedia Communications Lab at Darmstadt University of Technology, Germany, where he received his PhD degree (Dr.-Ing.) in 2000. More information and publication list can be found at http://home.ifi.uio.no/~griff .

    Prior knowledge: General background in informatics, basic knowledge in computer architecture, basic programming skills in C or C++ and working with the command line.

    Recommended reading

  • Van Amsesfoort, S., Varbanescu, A.L., Sips, H.J. and van Nieuwpoort, R.V.: Evaluating multi-core platforms for hpc data-intensive kernels, ACM Computing Frontiers, 2009.
  • Stensland, H.K., Espeland, H., Griwodz, C. and Halvorsen, P.: Tips, tricks and troubles: Optimizing for Cell and GPU, ACM NOSSDAV, 2010.
  • Brodtkorb, A.R., Dyken, C., Hagen, T.R., Hjelmervik, J.M. and Storaasli, O.O.: State-of-the-art in heterogeneous computing. Scientific Programming (IOS Press), 2010.
  • Ian Foster: Designing and Building Parallel Programs: Concepts and Tools for Parallel Software Engineering, Addison-Wesley, 1995.
  • Hill, M.D., Marty, M.R.: Amdahl's Law in the Multicore Era, IEEE Computer, 2008.
  • NVidia: NVidia CUDA C Programming Guide 4.0, 2011.
  • NVidia: NVidia CUDA C Programming Best Practices Guide 4.0, 2011.
  • NVidia: NVidia CUDA API Reference Manual 4.0, 2011.
  • NVidia: Computer Visual Profiler User Guide 4.0, 2011.
  • Info on how to subscribe.

    Message Passing Interface

    Friday May 4, 2012 - @Het Pand - Prior zaal

    Jan Fostier (Ghent University, Belgium)

    Chairs: Tom Kuppens, Michael Vyverman

    The Message Passing Interface (MPI) is a standardized library specification for message passing between different processes. In layman's terms: MPI provides mechanisms for handling the data communication in a parallel program. It is particularly suited for computational clusters, where the workstations are connected by an interconnection network (e.g. Infiniband, Gigabit Ethernet).In this lecture, the applicability of MPI will be compared to other parallel programming paradigms such as OpenMP, Cuda and MapReduce. Next, the basic principles of MPI will be gradually introduced (Point-to-point communication, collective communication, MPI datatypes, etc). Hands-on exercises allow the participants to immediately turn the newly acquired skills into practice, using the UGent Stevin supercomputer infrastructure. Finally, some more theoretical considerations regarding scalability of algorithms are presented.

    Jan Fostier received his MS and PhD degree in physical engineering from Ghent University in 2005 and 2009 respectively. Currently, he is appointed assistant professor in the department of Information Technology (INTEC) at the same university. His main research interests are (parallel) algorithms for biological sciences, high performance computing and computational electromagnetics.

    Prior knowledge: Basic knowledge of C / C++ or Fortran is required. No prior knowledge of parallel computing is required. Every participant requires an account for the UGent HPC infrastructure.

    Recommended reading

    Info on how to subscribe.

    MapReduce and Hadoop

    Friday May 11, 2012 - @Het Pand - Prior zaal

    Robin Aly (University of Twente, the Netherlands)

    Chairs: Jan Fostier, Bart Mesuere

    This course provides a mix of theory and hands-on to manage Big Data as it is done in the data centers of large search engines. In contrast to existing grid computing and supercomputing paradigms, which both employ specialized and expensive hardware, search engines use large numbers of commodity computers. This course teaches how to carry out large-scale distributed data analysis using the programming paradigm MapReduce. This paradigm is inspired by the functions 'map' and 'reduce' as found in functional programming language such as Lisp. Students will learn to specify algorithms using map and reduce steps and to implement these algorithms in Java using Hadoop, an open source implementation for analysis tasks. The course will also introduce the language Pig Latin which can be used to specify MapReduce tasks in a declarative way. Finally, if time permits, the course will touch the NoSQL database HBase which allows structured storage of data suitable for random access.

    Robin Aly is a Post-Doc at the University of Twente in the Netherlands, where he received his PhD in Content Based Multimedia Retrieval. He has a strong background in data management and distributed data processing using innovative programming paradigms in the Hadoop framework. He teaches this framework in master courses. He co-organized the Dutch-Belgian Information Retrieval workshop 2009 and participated in the program committee of several international conferences.

    Prior knowledge: Intermediate programming skills in Java (to follow the hands-on sessions), basic knowledge in file systems, functional programming is a plus.

    Recommended reading

  • Ghemawat, S., Gobioff, H. and Leung, S.: The Google file system, In ACM SIGOPS Operating Systems Review, 2003, 37, 29-43.
  • Dean, J. and Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM, ACM, 2008, 51, 107-113.
  • Jimmy Lin and Chris Dyer: Data-Intensive Text Processing with MapReduce.
  • Olston, C., Reed, B., Srivastava, U., Kumar, R. and Tomkins, A.: Pig Latin: a not-so-foreign language for data processing. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data, ACM, 2008, 1099-1110.
  • Tom White: Hadoop: The Definitive Guide. O’Reilly Media, 2009.
  • Info on how to subscribe.


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