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C2030-102 IBM Big Data Architect

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C2030-102 exam Dumps Source : IBM Big Data Architect

Test Code : C2030-102
Test Name : IBM Big Data Architect
Vendor Name : IBM
: 55 Real Questions

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IBM IBM Big Data Architect

Watson Goes any place at IBM believe 2019 | killexams.com Real Questions and Pass4sure dumps

Ginni Rometty delivering the keynote at IBM's Think 2019 picture: IBM

AI and desktop gaining knowledge of took core stage at IBM feel this 12 months, because the exhibit’s main AI bulletins served as a reminder that the business has probably the most most differentiated and competitive features for implementing AI in business operational processes available in the market. but if big Blue is to win the AI race towards AWS, Microsoft and Google Cloud in 2019 and past, it need to enhance its developer strategy and reinforce its communications, principally in areas it leads the market, comparable to in relied on AI and governance.

Let's dig a little deeper into IBM’s AI method, the main suppose announcements and what they suggest for the market.

Welcome to Chapter 2 of Digital Transformation

IBM CEO Ginni Rometty kicked off the consider event with an emphasis on how businesses are coming into "chapter two" of cloud adoption and digital transformation. This subsequent part is defined by means of enterprises scaling up their digital tasks, utilizing statistics on a mixture of ordinary IT techniques and public and private clouds, and putting AI on the core of their enterprise approaches.

Rometty took the possibility to shed some gentle on IBM's next chapter as well, following its $34 billion acquisition of purple Hat in 2018. purple Hat has breathed new lifestyles into IBM and its approach, which is now focussed on hybrid, multicloud functions. IBM claimed that ninety four p.c of agencies are the usage of a combination of public and personal cloud environments nowadays, and two-thirds are the use of multiple public cloud company. Many massive organisations stay petrified of lock-in by using the hyperscale cloud suppliers and are rightly concerned about their ability to stream information between clouds, and about making use of connectivity, management and safety among them continuously.

IBM's approach, which became evident during Rometty's keynote, is to tackle these concerns by offering a decide upon-and-mix set of functions fashioned from its middleware heritage that assist customers manage workloads spanning these environments. this is in keeping with open-source technologies akin to Kubernetes containers and OpenShift, red Hat’s container software platform.

related Article: How Will the $34B IBM Acquisition have an effect on red Hat users?

IBM’s AI approach: moving firms past Experimentation

This set the stage for an important increase to IBM’s AI approach. Rometty stated that Watson engagements now total 20,000 — a 25 % enhance from 16,000 in 2018, spanning 20 industries and eighty international locations. although, regardless of this adoption, the market remains totally experimental, with many valued clientele still undertaking proofs of theory or imposing narrow element solutions and preferring to start small. despite the fact they predict that by the conclusion of 2020, 90 p.c of huge organizations can be running pilot or production-degree machine learning purposes, very few could have thoroughly implemented the expertise inside business procedures or have a comprehensive AI strategy. here is on account of bad nice of facts, a scarcity of capabilities, and issues about have confidence in the technology.

IBM’s strategy and portfolio specializes in these core challenges and comprises a prioritization of its range of large statistics and analytical equipment, and the plumbing of AI, mirrored in Rometty’s keynote slogan "there is not any AI with out IA" (tips structure). A key product is IBM Cloud inner most for data, its oddly named platform for managing and governing machine gaining knowledge of facts that integrates data science, statistics engineering and application constructing methods into a single console and administration ambiance.

integrated with IBM Cloud inner most for information are a couple of key Watson solutions:

  • Watson Studio, a collection of design tools and a collaborative environment for statistics scientists, builders and area specialists.
  • Watson machine learning, infrastructure and capabilities operating on IBM cloud features to construct analytical fashions, neural networks and teach techniques with statistics to set up AI.
  • Watson Developer APIs, a set of internet APIs to permit builders to build purposes the use of speech processing, dialog and language, visual awareness, sentiment and behavior evaluation.
  • Watson functions, a set of prebuilt functions for ordinary makes use of comparable to in analytics, digital assistants, tips discovery and company automation. IBM also offers products for certain sectors, akin to healthcare, economic services and media and amusement.
  • IBM Releases Watson to move anywhere

    suppose’s biggest announcement was IBM Watson any place, which provides another key dimension to this portfolio. according to its corporate approach, IBM cited that it could make Watson portable across diverse public clouds, giving businesses a consistent technique to construct, installation and run AI fashions and applications in on-premises and public cloud environments akin to AWS, Alibaba, Google Cloud or Azure.

    IBM has developed new Watson microservices in Kubernetes containers the use of OpenShift, which abstracts Watson from its previous dependency on the underlying IBM cloud infrastructure. It hopes the flexibleness of Watson any place, according to open-source, will inspire extra companies to circulation past experimenting with AI through giving them extra alternatives to run AI anywhere records resides and thereby decreasing the worry of lock-in.

    IBM has staked out an important claim within the AI market with the move. In Rometty's phrases, Watson is now "probably the most open and scalable AI platform for groups on the earth" which is poles aside from 18 months ago, when Watson changed into plagued by PR problems and a recognition for being expensive, rigid and a black-field equipment. although IBM will ought to put money into integrating, configuring and optimizing Watson to work continually with all of the foremost public clouds, the flow reinvigorates its strategy after a tough few years.

    linked Article: Is the IBM Watson brand Unassailable?

    main within the Governance of synthetic Intelligence

    one other basic part of IBM's method that got here alive at believe turned into Watson OpenScale, its AI management and governance platform that contains the trust, monitoring, clarification and transparency tools launched in 2018 (see Trusting Watson). Born out of its research arm, the platform goals to address considerations about "black field" AI through giving purchasers easy methods to enhance the visibility and handle of AI techniques as well as explain results. It does this by means of monitoring the efficiency, fitness and behavior of desktop studying models at runtime.

    CCS perception has lengthy argued that corporations want extra contraptions to support them construct guardrails around AI and X-ray visibility into working systems. believe in AI — or an absence of it — is emerging as the greatest barrier to computing device getting to know adoption in organisations. for instance, in CCS perception's 2018 survey of IT determination-makers within the US and Europe, forty three % of respondents mentioned have confidence as a hurdle to adoption of their company. here's why IT choice makers positioned the means to make certain information safety, compliance and the transparency of how methods work among the many precise three necessities for their desktop studying investments in 2019, in accordance with the survey.

    The correct governance of AI will turn into crucial in establishing trust in the know-how, especially as companies put into effect AI of their operations over the next 12-18 months. Governance spans four vital domains: ethical design and bias; transparency and explainability; privateness; and security, administration and compliance. Watson OpenScale carries one of the most first instruments in the market and is at the least one year forward of the competitors during this important field.

    undertaking Debater historic experience

    IBM made a number of other key moves value noting. It announced a brand new product for company manner automation, referred to as technique Automation Intelligence with Watson. It additionally opened believe with a historic event which featured the first ever are living and public debate between IBM’s undertaking Debater and human debate champion, Harish Natarajan. according to its AI analysis in Tel Aviv, venture Debater is the first AI equipment within the fields of natural language processing, computational argumentation and reasoning, computing device listening comprehension and deep getting to know, designed to debate people on complex themes.

    Natarajan won the controversy based on the audience vote, however 60 percent felt IBM’s platform superior enriched their talents of the area as assignment Debater turned into in a position to take into account themes precisely, contextualize potential and put collectively a meaningful narrative all over the debate. The experience illustrated how speedy AI is progressing and became an additional reflection of how advantageous IBM’s analysis arm is to its enterprise as few businesses are transitioning AI research into products faster than IBM in 2019.

    linked Article: The next Frontier for IT: AI Ethics

    IBM in 2019 and past

    feel showed us that IBM has one of the most most differentiated and aggressive enterprise services for imposing AI in enterprise operational tactics out there. In improving the clarity of its company message, IBM has additionally delivered some a whole lot necessary simplification to the positioning of its range of AI items during the last 365 days, which can be finest viewed in the course of the image I took at the adventure beneath.

    IBM's AI Portfolio

    a much cry from 18 months in the past, IBM can now point to powerful differentiators in proposing open, hybrid and multicloud functions, governance and applied AI for industries, as well as having a broad portfolio working from programs to functions which is supported via a ambitious analysis arm and Massachusetts Institute of technology partnership that are feeding its manufacturing facility of new AI products at an increasing rate.

    youngsters, IBM's approach is never excellent and it nonetheless has work to do in enhancing its advertising and messaging, exceptionally within the areas it leads, equivalent to relied on AI and governance. Key product names tend to confuse and don’t accentuate the cost proposition enough. And despite improvements in how Watson is marketed, it remains an inconsistent company used commonly throughout the enterprise.

    in particular, IBM will additionally need to increase its approach for developers. This area received little attention at suppose 2019. crimson Hat's 8 million open-supply developers should be a significant increase to its Apple partnership, as will the flexibility in its approach with Watson any place, however IBM will should provoke upon the developer group about why its AI equipment are the superior.

    usual, suppose revealed some positive steps forward in IBM’s AI strategy. but these advancements could be vital if IBM is to win the AI wars and business AI market in 2019 and beyond.

    Nicholas McQuire is vice chairman, enterprise analysis and synthetic intelligence analysis at CCS insight. He has over 15 years' event in commercial enterprise know-how advisory functions, most recently as managing director of the world commercial enterprise Mobility Alliance.


    DESY and IBM strengthen huge facts architecture for science | killexams.com Real Questions and Pass4sure dumps

    X-ray scan of biological cells. credit: Britta Weinhausen/institution of Göttingen

    IBM these days announced it is taking part with Deutsches Elektronen-Synchrotron (DESY), a number one country wide analysis middle in Germany, to velocity up administration and storage of big volumes of x-ray information. The planned huge records and Analytics architecture in accordance with IBM software described technology can handle more than 20 gigabyte per second of facts at peak performance and help scientists international benefit faster insights into the atomic structure of novel semiconductors, catalysts, biological cells and other samples.

    DESY's 1.7 mile-lengthy PETRA III accelerator is a brilliant microscope that hurries up electrically charged particles virtually to the speed of easy – approximately 186,000 miles per second – and sends them via a tight magnetic slalom course to generate probably the most brilliant x-ray radiation of its type. This synchrotron radiation is used through greater than 2,000 scientists every year to verify the interior constitution of quite a lot of substances with atomic resolution. A key problem during this manner is storing and coping with large volumes of X-ray facts. .

    "a customary detector generates an information move of about 5 Gigabit per second, which is about the statistics volume of 1 finished CD-ROM per second," referred to Dr. Volker Gülzow, head of DESY IT. "And at PETRA III they would not have just one detector, but 14 beamlines outfitted with many detectors, and they are at present being prolonged to 24. All this big facts need to be stored and dealt with reliably."

    IBM application defined Storage expertise code identify Elastic Storage permits DESY to employ to save and deal with the large data flowing from PETRA III each 2d. credit score: DESY

    DESY is addressing this huge records challenge with the aid of IBM research and IBM software defined Storage expertise code name Elastic Storage that can scale conveniently to store and tackle greater than 20 Gigabyte of facts flowing each 2d from PETRA III. Elastic Storage can deliver scientists with excessive-pace entry to increasing volumes of analysis statistics. This structure will permit DESY to advance an open ecosystem for research and present analysis-as-a-service and cloud options to its users international.

    "IBM's utility described storage technologies can give DESY the scalability, velocity and agility it requires to morph into a real-time analytics provider issuer." pointed out Jamie Thomas, everyday supervisor Storage and utility described methods, IBM. "IBM can take the experience won at DESY and switch it to different fields of facts intensive science corresponding to astronomy, climate analysis and geophysics and design storage architectures for the evaluation of data generated by disbursed detectors and sensors."

    The scalability of the gadget can help DESY and a couple of foreign partners which are presently constructing the X-ray laser European XFEL, a research gentle supply with a view to generate even more statistics. "We expect about 100 Petabyte per yr from the european XFEL," noted Dr. Gülzow. it's comparable to the yearly facts quantity produced at the world's largest particle accelerator, the tremendous Hadron Collider (LHC) at the research center CERN in Geneva.

    DESY is one of the world's main accelerator facilities and a member of the Helmholtz association. It develops, builds and operates colossal particle accelerators used to examine the constitution of remember. DESY is housed in Hamburg and Zeuthen in Germany and is home to 3000 scientists from over 40 international locations a yr.

    explore further: solar telephone degradation followed without delay for the primary time


    u.s. : IBM strikes $700M cope with Santander to speed up transformation | killexams.com Real Questions and Pass4sure dumps

    Feb 15, 2019 (Euclid Infotech Ltd via COMTEX) -- IBM and Banco Santander introduced a 5-yr international expertise agreement valued at approximately $700M to allow Santander group to accelerate and deepen its business transformation.

    The contract - while featuring annual discounts for the bank on IT spend - will greatly permit Santander group to adapt against the open, flexible and up to date IT atmosphere it requires to materialize the pivotal function that expertise and digital capabilities play in its company approach. along with that modernization experience, primary to supply new efficiencies to the bank's operations, the agreement will additionally increase Santander's means to bring creative capabilities to its valued clientele.

    To that conclusion, Santander should be able to enrich its capabilities and applications with IBM's most imaginative and disruptive technologies, similar to AI, blockchain and big information, all supported by using security superior solutions. the usage of IBM Watson, as an example, Santander is incorporating AI capabilities to enhance client journey, boost department advisors knowledge and boost employee productivity.

    The contract strengthens IBM's role as one among Santander community's leading transformation partners. In that position, IBM is featuring further solutions and knowledge aimed to fundamentally aid Santander strategic purpose of building essentially the most superior IT structure of the monetary sector.

    The basis of that structure is the event against a hybrid, multicloud environment. To put in force Santander's hybrid cloud method, the financial institution created its own Cloud Competence core. IBM is participating with the core in the definition of the methodologies and techniques to accelerate that transformation experience. additionally, the financial institution is using various applied sciences together with IBM DevOps options and IBM API join, aimed to increase, iterate and launch new or upgraded applications and digital capabilities tons greater rapidly.

    IBM is additionally contributing to a key requirement of Santander's transformation process: to make certain they conform with the optimum level of business safety as distinct by means of the us executive for information, purposes and capabilities. the use of IBM security equipment, in areas like cellular functions and incident response, will assist Santander's to make stronger the protection of its purchasers and operations.

    "This contract will allow us to have a global accomplice with the most appropriate technology to aid speed up the IT transformation. They consider this contract with IBM represents an excellent assist to their strategy of constant development, whereas retaining their investments in know-how. IBM's technology will supply the bank with the flexibleness crucial to aid the consistently evolving business of a financial institution," says David Chaos, Santander international CIO.

    "Santander community is leveraging IBM applied sciences to assist their protection and regulatory work, and to rapidly strengthen new capabilities that meet emerging consumer demand by means of tapping into IBM's exciting technology and business advantage," mentioned David Soto, IBM normal supervisor for Santander community.


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    IBM Big Data Architect

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    Hortonworks, IBM, Red Hat Collaborate to Help Accelerate Containerized Big Data Workloads for Hybrid Architectures | killexams.com real questions and Pass4sure dumps

    Hortonworks Data Platform, Hortonworks DataFlow, Hortonworks DataPlane and IBM Cloud Private for Data bring comprehensive enterprise data platforms to Red Hat OpenShift

    NEW YORK, Sept. 10, 2018 /PRNewswire/ -- Strata Data Conference - Hortonworks (HDP), IBM (IBM) and RedHat (RHT) today announced an Open Hybrid Architecture Initiative, a new collaborative effort the companies can use to build a common enterprise deployment model that is designed to enable big data workloads to run in a hybrid manner across on-premises, multi-cloud and edge architectures.

    Hortonworks logo. (PRNewsFoto/Hortonworks)

    More

    As the initial phase of the initiative, the companies plan to work together to optimize Hortonworks Data Platform, Hortonworks DataFlow, Hortonworks DataPlane and IBM Cloud Private for Data for use on RedHat OpenShift, an industry-leading enterprise container and Kubernetes application platform. This can enable users to develop and deploy containerized big data workloads, ultimately making it easier for customers to manage data applications across hybrid cloud deployments. In addition, IBM and Hortonworks will extend their joint work to integrate key services offered through Hortonworks DataPlane with IBM Cloud Private for Data.

    Enterprises are undergoing massive business model transformations, powered by the ability to process and analyze new types and tremendous amounts of data. As a result, many are moving to hybrid cloud environments that leverage lightweight microservices in the most efficient manner possible.

    Hortonworks and IBM previously announced a collaboration to help businesses accelerate data-driven decision-making. Today's news builds upon that foundation with the intent to bring big data workloads to a modern and container-based foundation, enabling customers to deploy Hortonworks and IBM platforms into a hybrid cloud environment powered by Red Hat OpenShift. The initiative includes the following:

  • Hortonworks plans to certify Hortonworks Data Platform, Hortonworks DataFlow and Hortonworks DataPlane as Red Hat Certified Containers on Red Hat OpenShift and looks forward to achieving "Primed" designation. In addition, Hortonworks will enhance HDP to adopt a cloud-native architecture for on-premises deployments by separating compute and storage and containerizing all Hortonworks Data Platform and Hortonworks DataFlow workloads. This allows customers to more easily adopt a hybrid architecture for big data applications and analytics, all with the common and trusted security features, data governance and operations that enterprises require.
  • IBM, which announced plans earlier this year to extend IBM Cloud Private platform and middleware to the OpenShift platform, has begun the Red Hat OpenShift certification process for IBM Cloud Private for Data, and has achieved "Primed" designation as the first phase. The move will help provide the vast OpenShift community of developers and users – which include IBM and Hortonworks clients – fast access to robust analytics, data science, machine learning, data management and governance capabilities, fully supported across hybrid clouds.
  • "Kubernetes is the de facto container orchestration system and they have been working in this ecosystem since the project's infancy to help make it ready for all, and especially the enterprise in Red Hat OpenShift. Today they are thrilled that Hortonworks and IBM Cloud Private's data portfolio have selected Red Hat OpenShift as the trusted Kubernetes platform for big data workloads," said Ashesh Badani, vice president and general manager, Cloud Platforms, Red Hat. "By building and managing their applications via containers and Kubernetes with OpenShift, customers and the big data ecosystem have opportunities to bring this next generation of big data workloads to the hybrid cloud and deliver the benefits of an agile, efficient, reliable, multi-cloud infrastructure."

    "The work that Red Hat, IBM and Hortonworks are doing to modernize enterprise big data workloads via containerization is aimed at helping customers to take advantage of the agility, economics and scale of a hybrid data architecture," said Rob Bearden, chief executive officer of Hortonworks. "The innovations resulting from this collaboration can enable the seamless and trusted hybrid deployment model needed today by enterprises that are undergoing significant business model transformation."

    In addition to competitive and data challenges, organizations are also scrambling to bring applications once designed for public cloud behind the firewall for greater control, lower costs, greater security and easier management. In fact, in a recent IDC Cloud and AI Adoption Survey[1], more than 80 percent of respondents said they plan to move or repatriate data and workloads from public cloud environments behind the firewall to hosted private clouds or on-premises locations over the next year, because the initial expectations of a single public cloud provider were not realized.

    Story continues

    "As these dynamics continue, they'll work to slow innovation and hinder companies' progression to enterprise AI," said Rob Thomas, general manager, IBM Analytics. "Scaling the ladder to AI demands robust data prep, analytics, data science and governance, all of which are easily scaled and streamlined in the kind of containerized, Kubernetes-orchestrated environments that we're talking about today."

    About Hortonworks Hortonworks is a leading provider of enterprise-grade, global data management platforms, services and solutions that deliver actionable intelligence from any type of data for over half of the Fortune 100.  Hortonworks is committed to driving innovation in open source communities, providing unique value to enterprise customers. Along with its partners, Hortonworks provides technology, expertise and support so that enterprise customers can adopt a modern data architecture.

    Hortonworks and HDP are registered trademarks or trademarks of Hortonworks, Inc. and its subsidiaries in the United States and other jurisdictions. All other trademarks are the property of their respective owners. For more information, please visit www.hortonworks.com.

    Hortonworks' Forward-Looking Statements This press release may contain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended.

    Forward-looking statements provide current expectations of future events based on certain assumptions and include any statement that does not directly relate to any historical or current fact.  They may include (without limitation) information regarding their expectations, goals or intentions regarding their offerings, technology, partnerships, activities, future performance, their adoption of or involvement with others' offerings, and others' adoption of or involvement with their offerings.  Forward-looking statements are subject to known and unknown risks and uncertainties and are based on potentially inaccurate assumptions that could cause actual results to differ materially from those expected or implied by the forward-looking statements. If any such risks or uncertainties materialize or if any of the assumptions prove incorrect, their results could differ materially from the results expressed or implied by the forward-looking statements they make. Information on factors that could affect their financial results and the forward-looking statements in this press release are included in their Form 10-K filed on March 15, 2018, our Quarterly Report on Form 10-Q for the quarter ended June 30, 2018 filed on August 9, 2018, or in other filings they make with the Securities Exchange Commission from time to time, particularly under the caption Risk Factors. All forward-looking statements in this press release are made as of the date hereof, based on information available to us as of the date hereof, and we undertake no obligation, and do not intend, to update these forward-looking statements. 

    About IBM  For more about IBM Analytics visit www.ibm.com/analytics.

    About Red Hat, Inc. Red Hat is the world's leading provider of open source software solutions, using a community-powered approach to provide reliable and high-performing cloud, Linux, middleware, storage and virtualization technologies. Red Hat also offers award-winning support, training, and consulting services. As a connective hub in a global network of enterprises, partners, and open source communities, Red Hat helps create relevant, innovative technologies that liberate resources for growth and prepare customers for the future of IT. Learn more at http://www.redhat.com.

    Red Hat's Forward-Looking Statements Certain statements contained in this press release may constitute "forward-looking statements" within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements provide current expectations of future events based on certain assumptions and include any statement that does not directly relate to any historical or current fact. Actual results may differ materially from those indicated by such forward-looking statements as a result of various important factors, including: risks related to the ability of Red Hat to compete effectively; the ability to deliver and stimulate demand for new products and technological innovations on a timely basis; delays or reductions in information technology spending; the integration of acquisitions and the ability to market successfully acquired technologies and products; risks related to errors or defects in Red Hat offerings and third-party products upon which Red Hat offerings depend; risks related to the security of Red Hat offerings and other data security vulnerabilities; fluctuations in exchange rates; the effects of industry consolidation; uncertainty and adverse results in litigation and related settlements; the inability to adequately protect Red Hat intellectual property and the potential for infringement or breach of license claims of or relating to third party intellectual property; changes in and a dependence on key personnel; the ability to meet financial and operational challenges encountered in their international operations; and ineffective management of, and control over, Red Hat's growth and international operations, as well as other factors contained in Red Hat's most recent Quarterly Report on Form 10-Q (copies of which may be accessed through the Securities and Exchange Commission's website at http://www.sec.gov), including those found therein under the captions "Risk Factors" and "Management's Discussion and Analysis of Financial Condition and Results of Operations". In addition to these factors, actual future performance, outcomes, and results may differ materially because of more general factors including (without limitation) general industry and market conditions and growth rates, economic and political conditions, governmental and public policy changes and the impact of natural disasters such as earthquakes and floods. The forward-looking statements included in this press release represent Red Hat's views as of the date of this press release and these views could change. However, while Red Hat may elect to update these forward-looking statements at some point in the future, Red Hat specifically disclaims any obligation to do so. These forward-looking statements should not be relied upon as representing Red Hat's views as of any date subsequent to the date of this press release.

    Red Hat and OpenShift are trademarks or registered trademarks of Red Hat, Inc. or its subsidiaries in the U.S. and other countries.

    Media contact:

    Michelle Lazzar, Hortonworkscomms@hortonworks.com(408) 884-9861

    [1] IDC, Cloud Repatriation Accelerates in a Multicloud World, doc #US44185818, August 2018

     

    View original content to download multimedia:http://www.prnewswire.com/news-releases/hortonworks-ibm-red-hat-collaborate-to-help-accelerate-containerized-big-data-workloads-for-hybrid-architectures-300709451.html


    Containers key for Hortonworks alliance on big data hybrid | killexams.com real questions and Pass4sure dumps

    NEW YORK -- Hortonworks forged a deal with IBM and Red Hat to produce the Open Hybrid Architecture Initiative. The goal of the Hortonworks alliance is to build a common architecture for big data workloads running both on the cloud and in on-premises data centers.

    Central to the new Hortonworks alliance initiative is the use of Kubernetes-managed containers. Such container-based data schemes for the cloud increasingly appear to set the tone for big data architecture in future data centers within organizations.

    Hortonworks' deal was discussed as part of the Strata Data Conference here, where computing heavyweight Dell EMC also disclosed an agreement with data container specialist BlueData Software to present users with a reference architecture that brings cloud-style containers on premises.

    Big data infrastructure shifts

    Both deals indicate changes are afoot in infrastructure for big data. Container-based data schemes for cloud environments are starting to show the way that data will be handled in the future within organizations.

    The Hortonworks alliance hybrid initiative -- as well as Dell's and other reference architecture -- reflects changes spurred by the multitude of analytics engines now available to handle data workloads and the growing move of big data applications to the cloud, Gartner analyst Arun Chandrasekaran said in an interview.

    "Historically, big data was about coupling compute and storage together. That worked pretty well when MapReduce was the sole engine. Now, there are multiple processing engines working on the same data lake," Chandrasekaran said. "That means, in many cases, customers are thinking about decoupling compute and storage."

    De-linking computing and storage

    Essentially, modern cloud deployments separate those two elements, Chandrasekaran said. This approach is seeing greater interest in containerizing big data workloads for portability, he noted.

    We are decoupling storage and compute again. Arun Murthychief product officer and co-founder, Hortonworks

    The shifts in architecture toward container orchestration show people want to use their infrastructure more efficiently, Chandrasekaran said.

    The Hortonworks alliance with Red Hat and IBM shows a basic change is underway for the Hadoop-style open source distributed data processing framework. Cloud and on-premises architectural schemes are blending.

    "We are decoupling storage and compute again," said Arun Murthy, chief product officer and co-founder of Hortonworks, based in Santa Clara, Calif. "As a result, the architecture will be consistent whether processing is on premises or on cloud or on different clouds."

    The elastic cloud

    This style of architecture pays heed to elastic cloud methods that let users spin up big data clusters when needed for processing jobs and take them offline when they aren't.

    Strata Data Conference 2018 This week's Strata Data Conference in New York included a focus on Hortonworks' deal with IBM and Red Hat, an agreement between Dell EMC and BlueData, and more.

    "In public cloud, you don't keep the architecture up and running if you don't have to," Murthy said in an interview.

    That's compared with how Hadoop systems typically get deployed in the data center, where clusters are often configured and left in place to sit ready for high-peak workloads.

    For Lars Herrmann, general manager of the integrated solutions business unit at Red Hat, based in Raleigh, N.C., the Hortonworks alliance project is a step toward bringing in a large class of data applications to run natively on the OpenShift container platform. It's also about deploying applications more quickly.

    "The idea of containerization of applications allows organizations to be more agile. It is part of the trend they see of people adopting DevOps methods," Herrmann said.

    Supercharging on-premises applications

    For its part, Dell EMC sees spinning up data applications more quickly on premises as an important part of the reference architecture it has created with help from BlueData.

    "With the container approach, you can deploy different software on demand to different infrastructure," Kevin Gray, director of product marketing at Dell EMC, said in an interview at the Strata conference.

    The notion of multi-cloud support for containers is popular, and Hadoop management and deployment software providers are moving to support various clouds. At Strata, BlueData made its EPIC software available on Google Cloud Platform and Microsoft Azure. EPIC cloud support was already available on the AWS cloud.

    Big data evolves to singular architecture

    Tangible benefits will accrue as big data architecture evolves IT shops to a more singular environment for data processing on the cloud and in the data center, said Mike Matchett, principal consultant and founder of IT industry advisory firm Small World Big Data.

    "Platforms need to be built such that they can handle distributed work and deal with distributed data. They will be the same on premises as on the cloud. And, in most cases, they will be hybridized, so the data and the processing can flow back and forth," Matchett said in an interview at the conference.

    Some special optimizations will still be required for performance reasons, Matchett added. And IT managers will have to make decisions based on different workloads as to where particular analytics processing will be done, he said.


    Hortonworks, IBM, Red Hat release Open Hybrid Architecture Initiative to help boost containerized big data workloads for hybrid architectures | killexams.com real questions and Pass4sure dumps

    Hortonworks, IBM and Red Hat announced on Monday an Open Hybrid Architecture Initiative, a new collaborative effort the companies can use to build a common enterprise deployment model that is designed to enable big data workloads to run in a hybrid manner across on-premises, multi-cloud and edge architectures.

    As the initial phase of the initiative, the companies plan to work together to optimize Hortonworks Data Platform, Hortonworks DataFlow, Hortonworks DataPlane and IBM Cloud Private for Data for use on RedHat OpenShift, an enterprise container and Kubernetes application platform. This allows users to develop and deploy containerized big data workloads, making it easier for customers to manage data applications across hybrid cloud deployments. In addition, IBM and Hortonworks will extend their joint work to integrate key services offered through Hortonworks DataPlane with IBM Cloud Private for Data.

    The initiative includes Hortonworks plans to certify Hortonworks Data Platform, Hortonworks DataFlow and Hortonworks DataPlane as Red Hat Certified Containers on Red Hat OpenShift and looks forward to achieving “Primed” designation.

    In addition, Hortonworks will enhance HDP to adopt a cloud-native architecture for on-premises deployments by separating compute and storage and containerizing all Hortonworks Data Platform and Hortonworks DataFlow workloads. This allows customers to more easily adopt a hybrid architecture for big data applications and analytics, all with the common and trusted security features, data governance and operations that enterprises require.

    IBM, which announced plans earlier this year to extend IBM Cloud Private platform and middleware to the OpenShift platform, has begun the Red Hat OpenShift certification process for IBM Cloud Private for Data, and has achieved “Primed” designation as the first phase.

    The move will help provide the vast OpenShift community of developers and users – which include IBM and Hortonworks clients – fast access to robust analytics, data science, machine learning, data management and governance capabilities, fully supported across hybrid clouds.

    Enterprises are undergoing massive business model transformations, powered by the ability to process and analyze new types and tremendous amounts of data. As a result, many are moving to hybrid cloud environments that leverage lightweight microservices in the most efficient manner possible.

    Hortonworks and IBM previously announced a collaboration to help businesses accelerate data-driven decision-making. Today’s news builds upon that foundation with the intent to bring big data workloads to a modern and container-based foundation, enabling customers to deploy Hortonworks and IBM platforms into a hybrid cloud environment powered by Red Hat OpenShift.

    “Kubernetes is the de facto container orchestration system and they have been working in this ecosystem since the project’s infancy to help make it ready for all, and especially the enterprise in Red Hat OpenShift. Today they are thrilled that Hortonworks and IBM Cloud Private’s data portfolio have selected Red Hat OpenShift as the trusted Kubernetes platform for big data workloads,” said Ashesh Badani, vice president and general manager, Cloud Platforms, Red Hat. “By building and managing their applications via containers and Kubernetes with OpenShift, customers and the big data ecosystem have opportunities to bring this next generation of big data workloads to the hybrid cloud and deliver the benefits of an agile, efficient, reliable, multi-cloud infrastructure.”

    “The work that Red Hat, IBM and Hortonworks are doing to modernize enterprise big data workloads via containerization is aimed at helping customers to take advantage of the agility, economics and scale of a hybrid data architecture,” said Rob Bearden, chief executive officer of Hortonworks. “The innovations resulting from this collaboration can enable the seamless and trusted hybrid deployment model needed today by enterprises that are undergoing significant business model transformation.”

    In addition to competitive and data challenges, organizations are also scrambling to bring applications once designed for public cloud behind the firewall for greater control, lower costs, greater security and easier management. In fact, in a recent IDC Cloud and AI Adoption Survey[1], more than 80 percent of respondents said they plan to move or repatriate data and workloads from public cloud environments behind the firewall to hosted private clouds or on-premises locations over the next year, because the initial expectations of a single public cloud provider were not realized.

    “As these dynamics continue, they’ll work to slow innovation and hinder companies’ progression to enterprise AI,” said Rob Thomas, general manager, IBM Analytics. “Scaling the ladder to AI demands robust data prep, analytics, data science and governance, all of which are easily scaled and streamlined in the kind of containerized, Kubernetes-orchestrated environments that we’re talking about today.”



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