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70-487 exam Dumps Source : Developing Microsoft Azure and Web Services
Test Code : 70-487
Test designation : Developing Microsoft Azure and Web Services
Vendor designation : Microsoft
: 113 actual Questions
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Microsoft Developing Microsoft Azure and
download the authoritative guide: Cloud Computing 2019: the usage of the Cloud for competitive advantage
See the whole checklist of machine discovering options
corporations seeking to build, educate and installation machine researching on the Microsoft Azure cloud are natural candidates for Microsoft’s AI platform. It delivers automated desktop studying, DevOps for machine gaining lore of and a device-agnostic Python SDK. The product can tug information from customized purposes in addition to BI tools, equivalent to Microsoft exceed and tap Microsoft know-how, reminiscent of Cortana Intelligence, to supply insights and actionable effects.
The interactive workspace offers a visually oriented drag-and-drop ambiance the location users tug in datasets and connect them to modules that generate computer gaining lore of features. The ambiance besides enables clients to edit and refine fashions before publishing them as an internet provider. Microsoft Azure computing device learning Studio requires no programming abilities. it's designed for complete user groups and Azure meets main compliance requirements, reminiscent of HIPAA and PCI. Gartner rated the desktop learning seller a “Visionary” in its MQ.
computing device studying Studio presents a robust set of tools designed to strengthen, install and control desktop getting to know tasks. It incorporates open supply Jupyter Notebooks, sample datasets and algorithms, and predesigned modules to back in mission progress and management. The platform allows for clients to set up functions and predictive fashions as a web provider from machine discovering Studio.
This includes Azure statistics manufacturing facility, Azure movement Analytics, Azure HDInsight, Azure records Lake and energy BI. The environment supports both supervised and unsupervised studying. The atmosphere additionally supports Python, R Script and open source Scikit-learn, TensorFlow, PyTorch, CNTK, and MXNet.
The platform additionally supports Docker containers. This produces an customary framework this is flexible and enormously scalable. laptop researching Studio gives comprehensive features throughout the whole orbit of descriptive, diagnostic, predictive and prescriptive analytic varieties.
Overview and features
company analysts, developers and facts scientists.
Graphical drag-and-drop. Command line.
Scripting Languages/formats Supported
Python, R Script and open supply Scikit-be trained, TensorFlow, PyTorch, CNTK, and MXNet. accommodates PowerShell module and PowerShell cmdlets.
Most facts formats and file kinds. Works with Jupyter Notebooks, visible Studio Code and PyCharm.
incorporates a lot of open source tools and components. Tightly integrated with Azure cloud capabilities.
Reporting and Visualization
offers stalwart visualization capabilities and logging functions for net functions.
Microsoft offers a free tier with restrained capabilities and usage time. a common project begins at $9.ninety nine per month per seat with an further $1 per studio experimentation hour. creation web API pricing are in keeping with tiers that latitude from $0 to just below $10,000 per thirty days, depending on the number of transactions, compute hours and net functions used. Overage costs additionally observe.
Microsoft Azure ML Overview and features at a glance:
seller and lines
Microsoft Azure laptop researching
ML focal point
computerized ML platform working on hosted Azure Cloud.
Key aspects and capabilities
mighty descriptive, diagnostic, predictive and prescriptive analytics tools and capabilities. robust back for open source ML tools and scripting.
high scores at Gartner Peer overview. Some complaints about assist.
Pricing and licensing
Tiered pricing in accordance with clients and utilization. tiers from near zero to tens of lots per person annually.
Microsoft has announced the generic availability of two novel Azure analytics functions - Azure statistics Lake Storage Gen2 (ADLS) and Azure records Explorer (ADX). furthermore, Microsoft besides announced the preview of Azure statistics manufacturing facility Mapping facts move.
the novel ADLS Gen2 provider combines scalability, can charge-effectiveness, and a security model with loaded analytics capabilities using the Hadoop dispensed File device (HDFS). in addition, with the HDFS valued clientele can retain both structured and unstructured facts, along with an Azure Blob File system driver (ABFS) that permits information and folders to subsist fairly addressed on the server facet – casting off the want for a fancy client-aspect driver and ensuring high constancy file system transactions.
Jurgen Willis, director of product management, Azure Engineering, shared in his blog publish on how Microsoft further boosts analytics efficiency for ADLS:
We implemented a hierarchical namespace (HNS) which helps atomic file and folder operations. this is essential since it reduces the overhead associated with processing massive records on blob storage. This speeds up job execution and lowers can charge as a result of fewer compute operations are required. The ABFS driver and HNS significantly enhance ADLS’ efficiency, doing away with scale and performance bottlenecks.
subsequent, to the performance boost, Microsoft additionally offers the identical powerful data safety capabilities built into Azure Blob Storage, akin to:
Encryption of records in transit and at leisure by pass of TLS 1.2
Storage account firewalls
digital community integration
position-primarily based entry security
supply: https://azure.microsoft.com/en-us/weblog/for my part-amazing-collectively-unmatched-asserting-updates-to-three-excellent-azure-statistics-capabilities/
at the moment, ADLS is purchasable in almost complete Azure areas other than US DOD significant and US DOD East. additionally, the pricing particulars for ADLS are available on the pricing web page.
With the brand novel ADX, shoppers can leverage a completely managed facts analytics carrier for real-time analysis on massive volumes of streaming facts. This service is, in accordance with the weblog establish up by using Willis, in a position to querying 1 billion records in below a second with out a modification of the statistics or metadata required. furthermore, ADX includes autochthonous connectors to Azure facts Lake Storage, Azure SQL data Warehouse, and vigour BI and comes with an intuitive query language permitting shoppers to acquire insights in minutes.
Microsoft made the design for ADX with velocity and ease in intellect – it combines two divide features that labor in tandem:
The Engine, a service answerable for processing the incoming raw data and serving person queries, and
a data administration (DM) provider, which enables the ingestion of quite a lot of forms of raw data. additionally, the DM is besides accountable for managing disasters, backpressure, and information grooming tasks when critical.
notice that each services are deployed as clusters of compute nodes (digital machines) in Azure.
source: https://azure.microsoft.com/en-us/blog/personally-notable-jointly-unmatched-asserting-updates-to-three-extremely good-azure-records-features/
ADX is at present accessible in 41 Azure areas, and pricing particulars are available on the pricing page.
With both novel features, valued clientele can hold stronger flexibility in managing unstructured information or information generated from interactions on the net, application-as-a-carrier apps, social media, cell apps, and web of issues devices. in response to John Chirapurath, regularly occurring manager of Azure statistics, blockchain, and AI at Microsoft in a VentureBeat article:
We at complete times strive to compose it very convenient for IT workforce to undertake analytics and for line-of-enterprise people to utilize and bring effectual insights using pleasing products.
finally, Microsoft additionally released a preview of a brand novel Mapping information circulation means in Azure information manufacturing facility (ADF) - a hybrid cloud-based statistics integration carrier for orchestrating and automating facts circulation and transformation. With the novel potential, consumers can visually design, construct, and control facts transformation processes with out researching Spark or having a abysmal knowing of their distributed infrastructure. currently, ADF is purchasable in 21 regions and pricing details can subsist create on the pricing web page.
No result found, try novel key phrase!synthetic Intelligence does carry a significant chance, and businesses in the manner of constructing the utility ... over the same time frame. Microsoft's Azure does hold some merits over ...
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Developing Microsoft Azure and Web Services
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Download the authoritative guide: Cloud Computing 2019: Using the Cloud for Competitive Advantage
See the complete list of machine learning solutions
Organizations looking to build, train and deploy machine learning on the Microsoft Azure cloud are natural candidates for Microsoft’s AI platform. It delivers automated machine learning, DevOps for machine learning and a tool-agnostic Python SDK. The product can tug data from custom applications as well as BI tools, such as Microsoft exceed and tap Microsoft technology, such as Cortana Intelligence, to bow insights and actionable results.
The interactive workspace offers a visually oriented drag-and-drop environment where users tug in datasets and connect them to modules that generate machine learning functions. The environment besides allows users to edit and refine models before publishing them as a web service. Microsoft Azure Machine Learning Studio requires no programming skills. It is designed for complete user groups and Azure meets major compliance standards, such as HIPAA and PCI. Gartner rated the machine learning vendor a “Visionary” in its MQ.
Machine Learning Studio offers a robust set of tools designed to develop, deploy and manage machine learning projects. It incorporates open source Jupyter Notebooks, sample datasets and algorithms, and predesigned modules to aid in project progress and management. The platform allows users to deploy applications and predictive models as a web service from Machine Learning Studio.
This includes Azure Data Factory, Azure Stream Analytics, Azure HDInsight, Azure Data Lake and Power BI. The environment supports both supervised and unsupervised learning. The environment besides supports Python, R Script and open source Scikit-learn, TensorFlow, PyTorch, CNTK, and MXNet.
The platform besides supports Docker containers. This produces an overall framework that is flexible and highly scalable. Machine Learning Studio provides comprehensive features across the complete orbit of descriptive, diagnostic, predictive and prescriptive analytic types.
Overview and Features
Business analysts, developers and data scientists.
Graphical drag-and-drop. Command line.
Scripting Languages/Formats Supported
Python, R Script and open source Scikit-learn, TensorFlow, PyTorch, CNTK, and MXNet. Accommodates PowerShell module and PowerShell cmdlets.
Most data formats and file types. Works with Jupyter Notebooks, Visual Studio Code and PyCharm.
Accommodates numerous open source tools and components. Tightly integrated with Azure cloud services.
Reporting and Visualization
Offers stalwart visualization capabilities and logging functions for web services.
Microsoft offers a free tier with limited capabilities and usage time. A measure project starts at $9.99 per month per seat with an additional $1 per studio experimentation hour. Production web API pricing are based on tiers that orbit from $0 to just under $10,000 per month, depending on the number of transactions, compute hours and web services used. Overage rates besides apply.
Microsoft Azure ML Overview and Features at a Glance:
Vendor and features
Microsoft Azure Machine Learning
Automated ML platform running on hosted Azure Cloud.
Key Features and capabilities
Strong descriptive, diagnostic, predictive and prescriptive analytics tools and capabilities. stalwart back for open source ML tools and scripting.
High ratings at Gartner Peer Review. Some complaints about support.
Pricing and licensing
Tiered pricing based on users and usage. Ranges from near zero to tens of thousands per user annually.
Microsoft today announced a slew of novel capabilities for Azure Maps, its enterprise geospatial suite. The additions comprise a software progress kit (SDK) for Android, cloud-based services, map tiles, and integration with Azure lively Directory. Additionally, several services — including Route Range, collect Search Polygon, and Satellite and Hybrid Imagery — hold moved from public preview to generic availability.
“The mobility space is at the forefront of the most involved challenges faced by cities and urban areas today. The movement of people and things is as much a driver of occasion as it is an agent of chaos, aggravating existing challenges of traffic, pollution, and unbalanced livelihoods,” Chris Pendleton, principal PM manager at Azure Maps, wrote in a blog post. “The services we’re introducing are designed exclusively for the needs of the modern enterprise customer — powerful, real-time analytics and seamless cross-screen experiences, fortified by robust security services.”
First up is an enhanced map canvas with a set of natural earth map tiles, and a novel image compositor that Microsoft says makes interactions more “aesthetic” and “powerful” by enabling the rendering of raster maps with annotated points, lines, and polygons. besides making its debut in preview is the aforementioned Android SDK, which comes with rendering maps and traffic, drawing tools, event handling, and a variety of map canvases; it besides supports Azure Maps services such as Search and Routing.
Azure Maps Web SDK 2.0, a web-based module for accessing Azure Maps, is launching alongside the Android SDK. In addition to Azure lively Directory integration (more on that later), it introduces stroke gradients (i.e., the aptitude to fill a line with a gradient of colors to array transition from one segment of a line to the next), a Shaded Relief map style that shows the contours of the Earth, and polygon fill patterns and autochthonous control for shapes, borders, and fills.
Additionally launching in preview is Azure Maps Spatial Operations, a service that takes location information and analyzes it in actual time to enable predictive modeling of events. Its Geofencing component lets Azure Maps users store coordinates in the shape of customizable polygons in the novel Azure Maps Data Service (up to 50MB) and create notifications with Azure Event Grid that trigger whenever an object enters, exits, or changes proximity to a geofence.
Tech firm Tagdat is already using geofencing to warn construction site visitors when entering hazardous zones, Microsoft says.
Above: The novel Shaded Relief canvas.
Image Credit: Microsoft
Buffer, another tool that’s a fraction of Spatial Operation, allows users to build an zone around points, lines, and polygons based on a given distance, while Closest Point returns the closest points between a foundation point and a given collection of points. Meanwhile, Great-Circle Distance returns the shortest distance between two points on the surface of a sphere, and Point in Polygon returns a Boolean indicating whether the location is inside a given set of Polygon and MultiPolygon geometries.
Microsoft today besides took the wraps off of Azure lively Directory integration in preview, which can subsist used to implement secure access by providing role-based access control (RBAC) and authenticate apps and Azure lively Directory users. In addition, it supports managed identities for Azure resources.
The novel Azure Maps features approach a week after Microsoft announced it would exhaust TomTom’s location-based services for cloud services enjoy Microsoft Azure, Bing Maps and Cortana.
Microsoft is giving developers novel tools for developing blockchain solutions with the introduction of the Azure Blockchain progress Kit. The first initial release comes with a focus on connecting, integrating and deploying smart contracts and blockchain networks.
‘The Azure Blockchain progress Kit is the next step in their journey to compose developing cessation to cessation blockchain applications accessible, fast, and affordable to anyone with an idea. It is built atop their investments in blockchain and connects to the compute, data, messaging, and integration services available in both Azure and the broader Microsoft Cloud to provide a robust palette for a developer to realize their vision,” Marc Mercuri, principal program manager for blockchain engineering, wrote in a post.
According to the company, the toolkit is built off of its serverless technologies, blockchain developer templates and Azure Blockchain Workbench. Some of the capabilities the kit extends includes key management, off-chain identity and data, monitoring, and messaging APIs.
“These tools hold become the first step for many organizations on their journey to re-invent the pass they conclude business. Apps hold been built for everything from democratizing supply chain financing in Nigeria to securing the food supply in the UK, but as patterns emerged across exhaust cases, their teams identified novel ways for Microsoft to assist developers fade farther, faster,” Mercuri wrote.
For connecting, the kit aims to assist organizations, people and devices to connect to the blockchain. The kit includes samples for SMS and voice interfaces, IoT device, mobile clients, backend systems and data, bots and assistants and web clients.
For integrating data and systems, the kit tackles documents and media, and smart constrict interaction. The kit includes a set of logic apps for hashing files and file related metadata, and smart contracts for files and a file registry. “Businesses are using blockchain and smart contracts to facilitate multi-party processes. Blockchain besides delivers real-time transparency of the states and events of those contracts to preempt participants,” wrote Mercuri. “End to cessation blockchain solutions require integration with data, software, and media that live ‘off chain.’ External updates and events can trigger actions on smart contracts. Smart constrict events and status changes can then trigger actions and data updates to ‘off chain’ systems and data. These external systems and AI will besides exigency the aptitude to query attestable data from smart contracts to inform action.”
In addition, the blockchain app progress kit includes integration samples for legacy apps and protocols, data, SaaS and registers. Microsoft besides announced the release of Logic Apps and flood Connectors to extend amples to Ethereum, Corda, and Bitcoin.
For deploying smart contracts and blockchain networks, the kit will provide guidance on delivering blockchain developers in DevOps. The company announced the white paper DevOps for Blockchain Smart Contracts. Accompanying the white paper will subsist an implementation lead on how to implement CI/CD for smart contracts and infrastructure as code.