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Since the start of the pandemic, organizations representing a cross-section of industries have mobilized to adopt digital technologies to gain insights from their data and unlock cloud-based innovation. With the Microsoft Cloud, customers are reimagining ways to deliver patient care and provide access to critical services, secure their digital environments to scale and maintain business operations, extend frontline worker productivity, enhance employee experiences, and encourage new forms of business engagement and interaction.

At Microsoft Ignite, customers shared how accelerating their digital transformation with us as their partner has enabled them to better navigate the ongoing pandemic. They explained that while no single approach to digital transformation works for every company or industry, their journey to embrace technology has created the opportunity to retool their business model, improve operational and business performance and meet ambitious goals that drive industry-leading innovation.

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The growth we saw this past quarter further emphasized the role Microsofts comprehensive cloud plays in our customers digital transformation. Novartis shared through its multi-year research and development collaboration with Microsoft how they are using AI to accelerate the discovery, development and commercialization of medicines. Wejo announced continued progress in building its suite of data assets on Azure to enable near real-time data exchange and the ability to deliver new solutions to the broader mobility sector. Johnson & Johnson announced its digital manufacturing transformation with tools such as AI, IoT and Microsoft Cloud for Manufacturing capabilities to improve agility, reduce cost of ownership and improve disaster recovery. We partnered with Kyndryl to bring to market advanced solutions on Azure and accelerate hybrid cloud adoption, modernize applications and processes and to support mission-critical workloads. CVS Health selected Microsoft as a preferred cloud provider to customize care, empower frontline workers and digitize operations. We also shared news of our Xandr acquisition from AT&T to shape the digital ad marketplace with an emphasis on strong data governance and consumer privacy practices. And just today, we announced with FedEx a new cross-platform logistics solution for e-commerce aimed at increasing merchant competitiveness and improving the shopping experience so brands can better fulfill, ship and service customer orders.

St. Lukes University Health Network nurtures a commitment to innovation with Microsoft tools.

Healthcare organizations are digitally transforming to advance patient care and secure personal health data

Israel-based Maccabi Healthcare Services is improving the patient experience with Teams and Power Apps to enable care workers to manage critical healthcare-related communication and workflows. HCA Healthcare is ensuring personal health information and the devices and systems caregivers rely on each day remain secure using Microsoft Defender for Endpoint, and the NHS has built a more responsive and scalable system architecture using Azure to help increase security, performance and operations. St. Lukes University Health Network is more easily connecting people to their doctors and consolidating its data to communicate directly with patients. Lancet Laboratories has modernized its supply chain management solution across South Africa by migrating to Dynamics 365, and Orizon is migrating to Azure to modernize its data infrastructure to speed up care and further protect the data of 16 million Brazilian patients. And, with the support of Microsoft partner Pegasus One, IN.S.P.I.RE Global LLC is using Azure services to create a health and wellness platform that offers guidance on follow-up visits and coordinated care.

In Washington state, King County delivers critical services using Microsoft Power Apps portals.

The public sector is increasingly turning to the cloud to maintain access to services and secure its environments

The New Zealand Department of Internal Affairs is helping residents affirm their identities and access services more easily by centralizing its identity service across 56 public agencies. The University of Miami is boosting security improvements for its on-premises environment and scaling its virtual network using Azure VMWare. The Dominican Republic, via its Ministry of the Presidency, will be the first Caribbean country to be part of the Microsoft Government Security Program aimed at improving protection and defense against cyberthreats. Japans Ministry of Economy, Trade and Industry is using Power Platform to digitize administrative procedures, enhance government services and drive data-driven policy decisions, and the King County Department of Information Technology is taking a low code-first strategy to help residents gain access to needed services by building more than 200 solutions. With help from FunctionOne, the Court of Justice of So Paulo is creating a more inclusive environment for employees with disabilities by implementing Microsoft 365 tools and developing a chatbot.

Johnson Controls exceeds enterprise training expectations with a scalable solution built on Power Platform.

From smart spaces to factory floors, manufacturing organizations are building cloud infrastructures to scale operations and keep employees connected

Global manufacturer Advantech is keeping its networks and facilities in Asia, Europe, the U.S. and Australia highly secure and compliant by deploying Microsoft Security solutions, and Rudin is monitoring unmanaged devices for threats and targeted attacks across its smart buildings. In Mexico, CEMEX is using Azure to significantly improve performance of its SAP applications. AMD is using high-performance computing to maximize production timelines and speed delivery. Supported by Infosys, Norwegian global supplier Jotun Group is modernizing key business applications to run on Azure, resulting in better app performance, less app downtime and reduced cost. Using Power Apps, Johnson Controls built a class of enterprise-level training solutions that can track, measure and analyze progress on learning outcomes and key initiatives. Austrian furniture manufacturer Blum is keeping factory floor employees connected to the larger company by adopting Microsoft Viva.

Zurich Insurance gets future-ready with Microsoft 365 tools that modernize customer service.

Financial services companies are embracing cloud solutions to maintain business operations and respond to customer needs

Bankingly is democratizing access to financial resources across rural Latin America through web services and mobile applications developed on Azure. Interac is powering the future of digital payments in Canada by migrating core software applications to the cloud and reliably scaling its solutions, and United Arab Emirates-based Mashreq Bank is using Azure for its hybrid solution to gain better insights into customers and optimize the digital banking experience. Netherlands-based Rabobank is using Microsoft Defender for Cloud to manage its hybrid, multi-cloud environment and to protect data and information. Investors Bank is maintaining business continuity and enabling a digital-forward, omnichannel strategy by migrating to the cloud with help from Applied Information Sciences. Zurich Insurance Germany is maintaining security, compliance and the ability to protect customer data while also equipping employees with productivity tools, and Techcombank is adapting to a remote work model to keep business operations running smoothly for employees and customers across Vietnam.

Daimler looks to optimize supply chain processes and reduce downtime with Dynamics 365.

From virtual tire development to interactive movie posters to flight crew communication, the Microsoft Cloud is driving innovation across every industry

Belgium-based Bridgestone EMIA is using high-performance computing to increase the sustainability, efficiency and agility of its virtual tire development process, and Daimler Trucks North America is bringing together actionable insights and optimizing operations across the supply chain using Dynamics 365. Axpo, Switzerlands largest renewable energy producer, is creating a single access point for its grid assets using Azure services and Power BI. German energy company Uniper is creating a unified solution to standardize management of its data estate using Azure Arc, and Finnish telecommunications company Nokia is using the technology to deploy, operate and monitor applications running in its customers preferred cloud. With partner Accenture, Disney Studios StudioLAB is developing and piloting interactive movie posters leveraging Azure to enable the virtual setup and monitoring of content and data analytics. Peloton is using Azure and its AI capabilities to develop live subtitles so members who are deaf or hard of hearing can more easily engage in classes. U.K. retailer Marks & Spencer is using Teams as its productivity platform for frontline workers and office-based employees, and United Airlines is using collaboration apps to improve core operational processes and boost communications between operations teams and flight crews.

How our customers are adapting underscores technologys critical role during times of unpredictability and change. Amid the previous quarters pandemic-related challenges, we kept pace with our customers evolving needs, innovating through our partner ecosystem to harness the Microsoft Cloud in support of their business outcomes. That is our purpose and will remain so even once we are all beyond the pandemic. As always, I feel tremendously privileged to work with the customers who have chosen to partner with Microsoft, and I am excited as their trusted technology advisor about what is on the digital horizon.

Tags: AI, Azure, Azure Arc, Azure Cognitive Services, Azure HPC, Azure IoT, Azure Purview, Azure Synapse Analytics, Cloud Computing, COVID-19, customers, Dynamics 365, Dynamics 365 Remote Assist, healthcare, Healthcare Bot, HoloLens, IoT, manufacturing, Microsoft 365, Microsoft Cloud, Microsoft Ignite, Microsoft Inspire, Microsoft Power Platform, Microsoft Teams, Microsoft Viva, mixed reality, partners, Power BI, PowerApps, Retail, Surface, Surface Go 2, Synapse

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Building resiliency and spurring innovation: customers are using the Microsoft Cloud to advance industries and keep business moving forward - The...

Margaret Lee

Margaret is senior vice president and general manager of digital service and operations management for BMC Software, Inc. She has P&L responsibility for the companys full suite of BMC Helix solutions for IT service management and IT operations management.

Big data and the internet-of-things go hand in hand. With the continued proliferation of IoT devices one prognosticator estimates there will be 64 billion IoT devices online by 2025 enterprises are faced with extreme data volumes.

Managing these volumes, and yielding actionable insights from them, is key to transforming business for an era in which data is as vital as sunshine.

One area where the IoT data deluge can provide insights is through anomaly detection. Like traditional business applications and IT infrastructure, IoT can be monitored for issues in the physical devices to which theyre connected.

For example, when IoT devices are used to help modernize and automate processes in industrial or manufacturing settings, anomalies could be a sign that a particular piece of machinery needs maintenance. An early heads-up to a potential problem can help reduce unplanned downtime.

But corralling all that data can be a challenge as getting it moved from the device into a central compute platform can be problematic. Do you really need to send all the data from every device?

Edge computing can help overcome data overload and make IoT anomaly detection more effective. Exploring that practice in depth provides an illuminating look into emerging network architectures and how they will propel businesses in the future.

There are two prominent anomaly detection strategies integrated into IoT cases, each with advantages and drawbacks.

Static thresholds have the advantage of automating routine decision-making and alerting, giving it some advantage over traditional strategies. But to use static thresholds, administrators need domain knowledge thresholds at the right levels. And these levels dont change according to conditions, making them difficult to maintain in ever-changing environments.

Methods based on machine learning (ML), either supervised or unsupervised, add intelligence to automated anomaly detection. By continuously learning time-series data behavior, the system becomes more adaptive to data changes and can better handle changing environments.

However, the volume of data generated by IoT devices will continue to increase over time, driving related increases in network bandwidth, storage volume and compute requirements. As a result, the use of centralized resources, even cloud, for real-time IoT data processing is becoming more and more expensive and lengthening the latency in data processing.

Edge computing provides a more effective way to leverage ML-based anomaly detection. By shifting critical data processing workloads closer to the data source (IoT devices), you can reduce workloads on the cloud, ensure zero-latency data processing, improve response time and decrease network load and cloud costs.

Edge computing can be also used to monitor machine health in real time to detect anomalies that might indicate a failure in a system. Zero-latency data processing makes it possible to report major incidents in near-real time and prevent system failures.

Edge computing can be deployed with a number of architectures, including 100% edge computing and hybrid models that combine edge and cloud computing. For the purposes of illuminating edge architectures for anomaly deployment, the latter is shown here in Figure 1.

In this model, the IoT gateway collects and receives data from IoT devices using various IoT data protocols and pushes data to a messaging layer. Data processing components at the edge pull data from the messaging layer, process it and send insights to the cloud for centralized alerting and reporting. A monitoring and management system reports operational issues to the cloud and ensures that components are synchronized with the configuration data centrally managed from the cloud.

Edge computing components can be deployed together in a single-board computer like Raspberry Pi or across multiple devices in the same data center for greater scalability. The choice depends on scalability requirements.

Figure 2 shows an architecture for implementing edge computing for anomaly detection. This model adds intelligence to the generic architecture described previously.

In this model, an intelligent IoT gateway acts as a time-series data router. The messaging layer has separate queues for each anomaly detection method. Based on the anomaly detection methods being applied to specific time series, the gateway makes routing decisions and puts data into the respective queues. Dynamic routing decisions are driven by the configuration. Configuration changes are made at the cloud, and the monitoring and management system applies them.

Anomaly detection processors fetch data from the respective queues, detect anomalies and report them to the cloud. These processors also store data in a time-series database.

In this example, an offline training scheduled job periodically fetches bulk data from the time- series database, compresses data and sends it to the cloud to train ML models for supervised anomaly detection. The job also fetches ML models from the cloud and stores them in an ML models database. A supervised ML anomaly detector fetches ML models from the models database.

The monitoring and management system reports operational issues to the cloud and ensures that components are in sync with the configuration data centrally managed from the cloud.

For the foreseeable future, most enterprises will adopt a hybrid IT approach that includes both centralized and edge computing as part of an even more complex IT landscape.

The next step is to use edge computing to collect, apply analytics, and act. The days of centralized compute engines and lagging insights are numbered. Today, we are living in a world where we can collect, analyze and act on data where its generated in an instant.

This is where we can apply intelligent automation to find ways to orchestrate important edge data with central data pipelines for the required insights for automated action, instantaneously.

The data volumes and velocity of a modern IoT implementation call for scalable, efficient, real-time anomaly detection. Edge computing makes it possible to leverage machine learning for IoT anomaly detection while avoiding high cloud costs and processing latency. By using the architecture described above, you can detect and resolve IoT failures quickly to ensure optimal service for your organization.

Feature image via Pixabay

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Anomaly Detection: Glimpse into the Future of IoT Data The New Stack - thenewstack.io

Mumbai: Google on Monday announced plans to open a new office in Pune this year, that will hire professionals for building advanced enterprise cloud technologies.

Expected to open in the second half this year, the facility will hire people for Cloud product engineering, technical support and global delivery centre organisations.

The company said it has kicked off recruitments, alongside rapidly growing teams in Gurugram, Hyderabad and Bengaluru.

As an IT hub, our expansion into Pune will enable us to tap top talent as we continue to develop advanced cloud computing solutions, products and services for our growing customer base, said Anil Bhansali, VP of Cloud Engineering in India.

The hires will be responsible for building advanced enterprise cloud technologies in collaboration with Google Clouds global engineering teams, providing real-time technical advice, and delivering product and implementation expertise that customers turn to Google Cloud for as their trusted partner.

Google Cloud has hired some key industry people in recent months in India, including former AWS veteran Bikram Singh Bedi as Managing Director, Google Cloud India.

In November last year, the company hired senior IBM executive Subram Natarajan as Director of Customer Engineering for its India operations.

Google last year opened it second Cloud region in the country in Delhi-NCR and close to the government quarters to further serve businesses of all sizes especially the public sector.

Original post:
Google Cloud to open new India office later this year - The Siasat Daily

Global Cognitive Cloud Computing Market research report 2021 is detailed industries reason about on the present state of the industry which studies advanced strategies for business growth and defines important factors such as top players, value, key regions, growth rate, SWOT analysis i.e., Strength, Weakness, Opportunities and Threat to the organization and others. The report provides the present scenario and the growth forecasts of the global Cognitive Cloud Computing Market. To analyze the market scope, the report presents an inclusive description of the market by the method of examining, combination and summary of data from numerous sources.

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The report offers to global Cognitive Cloud Computing market with respect to segmentation of the global market. Various macro- and microeconomic factors influencing growth of global market have been included in this report. Analysis of drivers, restraints, opportunities and trends of the global Cognitive Cloud Computing market have been propounded in this report. Opportunities available for prominent players operating in the global market have been propounded in this report. All this information included in the report makes it most-creditable and go-to forecast of global Cognitive Cloud Computing market.

Competitive analysis:

It covers inclusive and strategic inputs from global leaders to help users understand the strength and weaknesses of the key leaders. Expert analysts in the field are following players who are profiled as prominent leaders in the Cognitive Cloud Computing market. The report also covers the competitive strategy adopted by these market leaders to the market value. Their research and development process were explained well enough by experts in the global Cognitive Cloud Computing market to help users understand their working process.

The Top Major Players are: Google, Inc., IBM Corporation, Amazon Web Services, Inc., Apple, Inc., Attivio, Inc., Baidu, Inc., BMC Software, Inc., Clarifai, Inc, CognitiveScale, IPsoft Inc.

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Regional Classification

The Cognitive Cloud Computing market is divided into five areas, each with its own development possibilities and current trends: Latin America, North America, Asia Pacific (APAC), Europe, Middle East and Africa. The report was created through extensive research and analysis, as well as examination of numerous elements that may influence regional growth, such as each regions economic, political, environmental, technical, and social condition. It also includes a complete analysis of each regions recognized player, production and revenue, as well as the top influencing elements, critical data and data segmented both regionally and globally.

Method of Research

The purpose of this sections research is to examine the Cognitive Cloud Computing market over the course of the review period using several validated metrics based on Porters Five Force Model. As a result, a thorough examination of the market aids in identifying and emphasizing the markets primary strengths and weaknesses as it progresses. Furthermore, the study was created using a combination of primary and secondary research, including interviews, surveys, and observations from seasoned analysts, as well as reliable paid sources, trade magazines, and industry body databases. Beyond important points in the industrys value chain, the study includes a complete qualitative and quantitative assessment based on data gathered from industry analysts and market players.

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Global Cognitive Cloud Computing Market 2021 Trends and Forecast 2029 | Major Key player Google, Inc., IBM Corporation, Amazon Web Services, Inc.,...