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70-475 Design and Implement Big Data Analytics Solutions

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70-475 exam Dumps Source : Design and Implement Big Data Analytics Solutions

Test Code : 70-475
Test Name : Design and Implement Big Data Analytics Solutions
Vendor Name : Microsoft
: 42 Real Questions

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Microsoft Design and Implement Big

IBM, Mastercard, Microsoft, and Others Plan To provide The vigour Of identification again To The people | Real Questions and Pass4sure dumps

this article in Finextra reports the ideas laid out in Mastercard’s new white paper “Restoring have confidence in a Digital World.” The paper identifies 10 principles that Mastercard considers the bedrock of an id management solution, however doesn’t offer any specifics related to the answer it has prior to now introduced it’s building with Microsoft when it states “we are creating a brand new digital identification equipment that works for each person. One it is greater cozy, more inclusive, extra handy, and does a stronger job of holding people’s privateness.” Late final year Mastercard introduced it changed into working with Microsoft to build a solution for this very identical issue on the Microsoft Azure cloud platform.

Mercator will free up a record within the close future that provides a deep dive into the applied sciences and leading open implementations of Digital identity which are built on the design precept of giving the power of controlling identity counsel again to the individuals and additionally will consider how such a huge shift in vigor might also subsequently affect latest markets.

despite the fact, already clear is that while Mastercard may be playing coy involving the repute of its personal implementation, each IBM and Microsoft are all in on digital identity and have already made commitments to certain open implementations, together with the Hyperledger Indy venture and the Sovrin basis. here is what Finextra needed to say about Mastercard’s white paper:

“Now Mastercard, which is additionally a associate on the Apple Card, is offering a purchaser charter-based mostly device it says can support to fix have faith within the digital world. The payments gigantic has set out 10 ideas on information rights and possession, confidentiality, consent, transparency, protection and inclusion that quantity to a simple particular person appropriate: ‘I own my identification and that i manage my id information.’

The business says that its model is set privacy-by means of-design and doesn't mixture id records. Digital interactions will involve minimal statistics trade and ensue best when vital, with users in handle and their identity bound to their mobilephone.

Ajay Bhalla, president, cyber and intelligence solutions, Mastercard, says: “The big query for digital interactions in a hyper-linked age is: how do you have confidence somebody you don’t recognize, can’t see and isn’t present in grownup?

‘this is an area we’ve been exploring for some time, in dialogue with a number of distinctive groups. It’s with this insight that they imagine a global where an individual’s id and the devices working on their behalf can be verified instantly, safely and securely, the place access is received with out passwords and records is exchanged only with consent.’ “

read the total paper

Overview by Tim Sloane, VP, payments Innovation at Mercator Advisory community


Article identify

IBM, Mastercard, Microsoft, and Others Plan To provide The power Of identity again To The individuals


The paper identifies 10 principles that Mastercard considers the bedrock of an id administration solution, however doesn’t offer any specifics regarding the solution it has up to now introduced it’s building with Microsoft


Tim Sloane

publisher name


publisher brand

Open Compute undertaking and Azure: hardware meets software | Real Questions and Pass4sure dumps

Microsoft has been a member of the Open Compute assignment given that 2014, donating many of the necessities for its Azure facts centers to the project. It’s the place Microsoft develops its Olympus servers and its Sonic networking software. So it’s always charming to go along to the annual OCP Summit to see what’s occurring on earth of open hardware design, and to see what features of Azure’s underlying infrastructure are being exposed to the area. here’s what I discovered this 12 months.

Public clouds like Azure have a really distinctive set of problems from most on-premises programs. They have to flow terabytes of data around their networks, devoid of hindering equipment performance. As further and further clients use their features, they should flow extra statistics within the community on hyperlinks that don’t guide greater-bandwidth connections. That’s a big problem, with three possible options:

  • Microsoft could spend tens of millions of bucks on inserting new connectivity into its statistics centers.
  • It may take a performance hit on its capabilities.
  • It might use application to remedy the difficulty.
  • With the substances of Microsoft analysis and Azure, Microsoft made the obtrusive alternative: It got here up with a new compression algorithm, undertaking Zipline. at present in use in Azure, assignment Zipline offers twice the compression ratios of the primary Zlib-L4 64KB algorithm. That’s a significant raise, essentially doubling bandwidth and storage potential for little or no capital can charge. Having proved its worth on its own network and in its personal hardware, Microsoft is donating the Zipline algorithm to OCP for anyone to put into effect and use.

    but challenge Zipline is greater than application. To work on the pace it has to work, it has to be applied as hardware. Kushagra Vaid, prevalent manager of Azure Hardware Infrastructure, gave me particulars about Zipline and how it works. The mission began by using analyzing many interior statistics units from throughout Azure, using statistics from a mixture of workloads. although the information changed into distinctive, the underlying binary had similar patterns, letting Microsoft improve a common compression algorithm that may work across no longer best static records however additionally streamed facts.

    Microsoft Outlook on net receives smarter: AI features save time developing conferences | Real Questions and Pass4sure dumps

    Microsoft is rolling out new updates to Outlook on the internet to provide office 365 clients meeting insights, suggested replies with a meeting, wise time guidance, and advised locations. 

    the brand new points are aimed toward saving time and boosting productivity for Outlook clients at work and may be rolling out over the following couple of weeks, based on Microsoft Outlook product manager Gabriel Valdez Malpartida. 

    The meeting Insights characteristic in Outlook taps Microsoft Graph to advocate counsel that Microsoft's machines think may be advantageous for a worker's next assembly, in addition to assist variety and discover counsel about past meetings, such as files shared by way of e mail or stored in SharePoint and OneDrive. 

    The function should still additionally surface central emails on a selected meeting topic, content material shared during a gathering, meeting notes, and content material shared after a gathering. 

    "assembly Insights are personalised for each and every grownup who receives them, so not everyone in the meeting will necessarily see the same recommended content. assembly Insights will simplest reveal you content material to which you have got entry," Microsoft notes.

    SEE: 30 things make sure to certainly not do in Microsoft office (free PDF)

    Microsoft's tackle counseled replies is gaining a third suggested response on the backside of an electronic mail dedicated to scheduling a meeting. The "time table a meeting" button can be clicked to bring up a form designed to without delay create a meeting request from the message. 

    Outlook on the net will additionally now suggest days and instances to arrange meetings in keeping with when attendees are free to fulfill. This may still aid laborers who nevertheless to-and-fro over e mail to prepare a meeting, or those who use Microsoft's FindTime function to let individuals vote on the ultimate time.   

    Outlook additionally positive factors a advised-places feature that presents tailor-made counsel for the place to fulfill, regardless if or not it's a conference room at work or a public area. 

    The business details the adjustments to Outlook on the internet in a brand new guide web page, which includes directions for turning off suggested replies and switching to traditional Outlook on the internet.   


    Open the meeting experience in calendar and scroll all the way down to see assembly Insights.

    picture: Microsoft

    the new aspects comply with Microsoft's big design and feature update to Outlook on the internet remaining September, which added predictive search, recommended replies, faster event advent in the calendar, and counseled conference rooms. 

    extra on Microsoft's Outlook

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    Design and Implement Big Data Analytics Solutions

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    Is Big Data The Key To Redesign-To-Cost Implementation? | real questions and Pass4sure dumps

    PTC published a fascinating study on the impact of big data on product design. Their white paper illustrated a number of ways that big data can play a valuable role in the evolution of new product design and implementation.

    “Big data is going to impact many industries, and product design is no exception. That’s in part because engineers will increasingly design sensors and communication technology into their products—like the Google car. In fact, some expect 50 billion devices to be attached to the internet by 2020! There are a number of ways design engineering might change as a result of IoT and the big data it enables.”

    However, the post focused mostly on traditional manufacturing and product design applications of big data. In actuality, big data can be more valuable for new manufacturing solutions, including re-design to cost.

    How is Big Data Playing a Role in Re-design to Cost Strategies?

    Re-design to cost applies to an existing solution (product or service) that is already on the market. The objective of this approach is to develop the most optimal solution possible in terms of costs and perceived value. To do this, a whole process is organized around the entire cost of the solution, while maintaining or even improving the perceived value and reducing unnecessary costs.

    This would be very difficult to deploy without a good data strategy in place. Big data enables brands to better assess and control costs. They can use predictive analytics to understand the cost of materials used in their projects, as well as the evolving logistics of marketing and other functions.

    The vast majority of a product’s costs, between 80% and 90%, are determined during the product design phase. According to James McCannon, a data logistics expert for a leading manufacturer that they spoke with, big data helps by providing a clearer picture of the variables that come into play, such as:

  • Delays,
  • Major changes in the design of a sub-assembly,
  • Changes in specifications during the project,
  • Marketing choices at the end of the project,
  • READ

    Here's How To Use Big Data To Optimize WordPress Performance

    Companies collect data sets around all of these functions. This makes it easy for them to develop effective controls and implement the best systems to control and automate the design and manufacturing process.

    What Are the Other Roles of Big Data in the Process?

    Sagepub has written several pieces on the relevance of big data in the product design process. Conggang Yu and Lusha Zhu’s piece “Product design pattern based on big data-driven scenario” was one of the most compelling.

    However, these papers tend to focus too heavily on a single aspect of the process. There are other implementations that are even more important.

    This analysis is used to define the functions required to meet actual customer needs and their relative importance and valuation, in other words the cost associated with each of these functions.

    The value analysis allows an objective cost breakdown of the product/service through the definition of the target costs of the components, while respecting the functional specifications.

    These two analyses require an overview of the product and use different levers to reduce, change or delete a function with the same or higher performance level.

    These levers are based on the entire product value chain, which must be considered as a whole, and include in particular:

  • A redesign work as such of the product/service. This can involve questions that are sometimes basic, but not part of the teams’ practices, or an analysis of the competition that can lead to some good practices.
  • Ensure the efficiency and optimization of the production chain, particularly with regard to the quantities produced, but also possible synergies with other products in the range or standardization of components.
  • Review the purchasing strategy and choice of suppliers based on objective cost design in order to identify possible higher margins on certain components.
  • Redefining marketing specifications may be necessary to validate the right need of customers.
  • Supply chain optimization can also be a major cost reduction lever, sometimes within a few millimeters of a package in a different position.
  • READ

    How Virtual Assistants Use Data Analytics To Save Clients Money

    Overlooking only one level of the value chain can lead to large unnecessary and, moreover, easily reducible costs if considered in the project as a whole. The redesign to cost work therefore requires the collaboration of the various entities of the company among themselves but also with their suppliers.

    Although historically applied to products, redesign to cost can also be applied to services or processes.

    In Sum, Big Data is an Essential Component to Re-design to Cost Implementation

    Numerous studies have emphasized the importance of big data for design, manufacturing and logistics management. However, most of the topics have focused on traditional design applications of big data. There are other ways to utilize big data, such as with improving re-design to cost management and other ways to streamline design and manufacturing for lower costs.

    Ministry of Electronics and IT, Government of India C-DAC Synergises R&D Strategizes to Accelerate Technology Revolution | real questions and Pass4sure dumps

    2-day Technology Conclave will start from 4th & 5th April at C-DAC Innovation Park, Panchavati, Pashan, Pune between9.00 a.m. to 6.30 p.m.

    Centre for Development of Advanced Computing (C-DAC) to hosts two days Technology Conclave on 4th and 5th April 2019 at Pune in the emerging areas of Advanced Computing with major thrust on Exascale Computing, Microprocessor and Quantum Computing, AI & Language Computing, IoE and Dependable and Secure Computing and Next Generation Applied Computing.

    Dr. Hemant Darbari, Director General said, 'C-DAC with its focus in Advanced Computing is uniquely positioned to establish dependable and secure Exascale Ecosystem offering services in various domains. As their nation embarks upon its most revolutionary phase of Digital Transformation, C-DAC has committed itself to explore and engage in the avant-garde visionary areas excelling beyond in the present areas of research transforming human lives through technological advancement.

    Eminent experts of international repute from MeitY, Niti Ayog, C-DAC, DRDO, IISc, IIT, AIIMS, research labs and industry like FICCI, Intel, Nvidia, Atos, Mellanox, NetApp, DDN will deliberate on the focussed research areas and provide deep insights through their synergetic ideas. Association with the industries and start-ups through collaborative innovation model is targeted for carving out implementable development solution strategies for India's specific problems. Demonstration of technologies and applications will be showcased at exhibits.

    C-DAC as one of the implementing agencies of the National Supercomputing Mission (NSM) is involved in developing indigenous HPC technologies, products and solutions, Application development, R & D, Human Resource Development leading to self-reliance in the long run. On the Exascale application front, C-DAC is engaged in multiple scientific and engineering domains like Weather Prediction, Computational Biology, Molecular Dynamics, Aerospace Engineering, Seismic Analysis, Nano Science, Astrophysics, Financial Simulations, Big Data Analytics to name a few. Key elements of Exascale Computing include HPC Systems Design, HPC interconnect & network design, HPC System Software & Middleware, devising special purpose computing and addressing challenges pertaining to power consumption and reliability.

    C-DAC is executing the microprocessor development programme with 64-bit quad core out of order processor operating at 2.0GHz as the target specification with the aim to create a fully indigenous microprocessor, along with full ecosystem. C-DAC with its expertise is designing and implementing a series of microprocessors, ecosystem and the associated IP along with the SoCs targeting various application domains. Requirements of stakeholders in strategic areas of Government, Industry and User Organizations are taken into considerations. C-DAC shall also setup a dedicated resource centre making available full ecosystem to the product designer community and academic institutions. C-DAC is focusing its efforts towards development of range of processors for varied use cases such as ILP Class for image processing, I-Class for smart energy meters, R-Class for AI/ML, A-Class for secure router, M-Class for strategic applications and HP-Class for high performance applications. Quantum

    Computing is gaining traction and advancements in materials science and computer science is enabling the same towards reality. This could have huge impact for bio-informatics, strategic sector, AI and in addressing various grand challenge problems. Key activities include development of a state-of-the-art tool kit and appropriate environment to enable/ encourage developers to design, develop and validate quantum-ware using relevant Quantum Technology.

    Language Computing is the most key aspect to realize the Digital India Vision of India. C-DAC has been pursuing pioneering research in Language Technology dissolving the language barriers. Use of natural language processing systems is required for developing Multilingual Systems to realize and present the same information in a variety of languages. Application of Machine Learning for Natural Language Processing, machine translation and accurate information extraction and retrieval are promising. In the context of Indian needs this shall be applied for various Indian Languages. Devising Domain specific solutions for various domains and bounding the learning accordingly ensures very high-quality Multi- lingual solutions. Advanced methods of AI come handy to address Speech Processing. Text-to- Speech Synthesis, Voice Biometry, Summarization Techniques and Semantic Analysis are some example areas being addressed.

    In the realm of AI, C-DAC's activities envisaged can be broadly categorized into National Supercomputing Mission (NSM) based Big Data Analytics with Machine Learning, Chatbots/personal assistant in Indian Languages with domain specificity, ICT solutions for societal applications, Linguistic and NLP resource creation for 22 major Indian languages including transfer lexicon, speech corpora, annotated discourses, heritage computing and digital preservation. AI based Analytics solutions for areas like Education, Agriculture, Finance, and Healthcare are in pipeline.

    C-DAC has devised the Comprehensive Cyber security Strategy through a three-pronged approach involving, innovative defence mechanisms, novel deterrence methods and effective response & recovery. Specific R & D in Cyber Security focuses on futuristic high-impact areas addressing core research Challenges in security across wide spectrum of compute, communication & storage involving Malware analysis & End-systems, IoT, SCADA, Cloud & Virtualization, Threat Analysis, Digital Forensics, Steganography, High-speed packet processing, Hardware security, Cryptographic algorithms and post quantum cryptography. On the Blockchain front, C-DAC shall facilitate Blockchain Technology platform development by customizing the existing platform to meet the requirements of specific application domains such as e-Governance, Financial sector, tourism, energy and Strategic Sector.

    Recent advancements in Artificial Intelligence, Blockchain, Cloud/Virtualization, Bigdata analytics is radically changing the present-day application development. C-DAC is engaged in developing more intuitive, usable and decision-oriented features to get embedded in applications of various domains. GenNext Applications for various sectors like Smart cities, Health Informatics, Agriculture, Education, Energy, Banking & Finance, Strategic sector and e-Governance shall leverage capabilities from Geographic Information System, Decision Support System, Image processing, Blockchain, AI/ML/DL and effective & intuitive visualization and User Interface. Towards Interoperability and seamless integration, depending on application context and domains, implementation of specific standards is required to be incorporated according to the respective domains.

    To view, Marathi release, click here .


    Ministry of Electronics and IT, Government of India C-DAC Synergises R&D Strategizes to Accelerate Technology Revolution

    Design & Devleopment by MENAFN

    Dr. Hemant Darbari, Director General, C-DAC

    Implementing analytics for Big Data applications with PC-based control systems | real questions and Pass4sure dumps

    Control engineers can use PC-based control systems to take advantage of Big Data analytics to help them make real-time insights for their companies in the Internet of Things (IoT) era.

    Communication standards that arose first in the world of IT are at play in manufacturing environments today as are standards more commonly associated with industrial applications. Courtesy: Beckhoff AutomationDemand for companies to reach the best decisions based on real-time data insights have never been greater. The responsibility to apply the right technologies to make all this happen often falls right at the feet of controls engineers. Fortunately, there are ways for them to implement Big Data analytics that aren’t too far out of the comfort zone of programmable logic controller (PLC) programmers if they use PC-based control systems.

    As PC-based control platforms have evolved into the Internet of Things (IoT) era, the walls have come down in terms of what the roles are for automation controllers in machines and plants. As far back as the mid-90s, one PC-based controller could assume the combined roles of PLC, motion controller, and human-machine interface (HMI). This eliminated previously existing costs and the inefficiencies of relying on multiple hardware, software, and networking platforms. Today, it is possible for one industrial PC (IPC) to assume the roles of IoT gateway, edge computing device, and data analytics platform.

    While deploying analytics onboard machine controllers is more typical in edge computing scenarios, additional analytics code developed in the same environment also can be run concurrently in cloud services, such as Microsoft Azure or Amazon Web Services (AWS). Communication standards that arose first in the information technology (IT) world, such as message queuing telemetry transport (MQTT), are also at play in manufacturing environments today, as well as the standards associated with industrial applications like OPC UA, which means scalability is assured.

    There are many benefits to running analytics software directly on the machine controller as a supplement to higher-level, standalone platforms that may run in the cloud. However, the expertise and skillset of the typical controls engineer may not overlap heavily yet with the latest IoT technologies finding their way into manufacturing environments.

    By applying Big Data analytics tools in the same engineering platform as the one used for PLC, motion control, and HMI, engineers shorten their learning curve and stack the deck in favor of successful implementations when many are rolling out pilot projects for their first true Industrial IoT (IIoT) and Industrie 4.0 concepts. This also protects and enhances machine builders and manufacturers’ intellectual property without giving away a new revenue stream or competitive advantage to an IoT services provider or another third-party.

    Using PC-based control technology, analytics code can be run within the overall machine control code for online and offline analyses without missing any functionality or connectivity. Graphical analytics sequences are developed in a software workbench, which can be converted into IEC 61131-3 languages so the code is easy to understand by controls engineers and PLC programmers and ensures that those analytics sequences have the ability to run in the PLC for 24/7 monitoring. Fortunately, PC-based control systems are available and can adopt computer science and IT programming tools.

    This can be expanded to include any other software platform running on a PC. Further, PC-based systems can enhance analytics applications for machine learning and optimization. These powerful algorithms also can run in real-time alongside the PLC and motion control on PC-based platforms. Regardless of the mix of tools needed to do the job, conducting as much engineering work as possible in one environment is a solid advantage to ensure more efficient project development.

    Machine manufacturers who have implemented their machine application with this kind of PC-based control technology do not need new tools to run the appropriate analyses. With accompanying configuration tools, users of analytics toolsets offered in PC-based control systems can sift through the data as analytics loggers acquire it.

    Available software libraries contain function blocks for several types of cycle analysis such as data classification, minimum, maximum, and average cycle times, value integrators, etc. They also contain function blocks for threshold value monitoring, providing the ability to document the number of threshold value violations. Other function blocks can analyze signal amplitudes and store indicators such as maxima and minima.

    Many variables can be selected from a large data package in order to graphically display them, for example, with a "post-scope configuration" using software-based scope tools. The configurator also provides some algorithms from the analytics PLC library to examine the data offline for limit values or to perform runtime analyses of machine cycles. The total running time of a machine cycle—the shortest, longest, and average running times—can be determined easily. The results of any important data can be displayed on dashboards produced for the machine HMI and in dashboards viewed on other devices.

    When surveying the current IoT solutions available in PC-based control architectures, PLC programmers can create new platforms or retrofit existing systems in order to crack the Big Data puzzle. This can be done without losing control of a major aspect of modern controls design or by adding layers of complexity from standalone IoT and analytics systems.

    Daymon Thompson, automation product manager, North America, Beckhoff Automation. Edited by Chris Vavra, production editor, Control Engineering, CFE Media,


    Keywords: Big Data, IIoT, control systems

    PC-based control systems can help control engineers looking to take advantage of Big Data analytics for real-time insights.

    Applying Big Data analytics tools for programmable logic controllers (PLCs), motion control, and human-machine interfaces (HMIs) shortens the learning curve for controls engineers.

    PLC programmers can create new platforms or retrofit existing systems in order to crack the Big Data puzzle. 

    Consider this

    What other instruments and technology can be used to provide control engineers with Big Data analytics?

    ONLINE extra

    Learn more about Beckhoff’s TwinCAT product solutions here. 

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