managing processing data

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Published By: Microsoft Azure     Published Date: Apr 11, 2018
Spend more time building great apps and less time managing server infrastructure. Get your solutions to market faster using Azure Functions, a fully managed compute platform for processing data, integrating systems, and building simple APIs and microservices. In this e-book you’ll find use cases, hands-on steps, and tutorials for quickly configuring your own serverless environments. Explore best practices for Functions, and learn how to: Develop event-based handlers on a serverless architecture. Test, troubleshoot, and monitor Azure functions. Automate administrative tasks from development through to deployment and maintenance. Integrate Functions with other Azure services. Build stateful serverless apps and self-healing jobs using Durable Functions. Download the 325-page serverless computing e-book and get access to dozens of step-by-step recipes for quickly building serverless apps.
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Microsoft Azure
Published By: Snowflake     Published Date: Jan 25, 2018
Compared with implementing and managing Hadoop (a traditional on-premises data warehouse) a data warehouse built for the cloud can deliver a multitude of unique benefits. The question is, can enterprises get the processing potential of Hadoop and the best of traditional data warehousing, and still benefit from related emerging technologies? Read this eBook to see how modern cloud data warehousing presents a dramatically simpler but more power approach than both Hadoop and traditional on-premises or “cloud-washed” data warehouse solutions.
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Snowflake
Published By: Dell EMC     Published Date: Oct 12, 2015
This business-oriented white paper explains four options for starting your Hadoop journey. This paper also outlines the benefits of Hadoop and highlights some of the many use cases for this new approach to managing, storing and processing big data.
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Dell EMC
Published By: HPE Intel     Published Date: Feb 19, 2016
The rising demands for capturing and managing video surveillance data are placing new pressures on state and local governments, law enforcement agencies, and education officials. The challenges go beyond the expanding costs of equipment, storage, software and management time. Officials must also lay the right foundation to scale their capabilities, improve performance and still remain flexible in a rapidly evolving ecosystem of surveillance tools. Find out what state, local government and education IT leaders need to know, and what steps you can take to: • Improve performance and ROI on cameras-per-server for the dollars invested • Optimize and simplify the management of daily surveillance processing, including the integration of facial recognition, redaction and analysis software • Fortify reliability and dependability to reduce the risk of surveillance data retrieval failures.
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HPE Intel
Published By: Zebra Technologies     Published Date: Sep 22, 2017
Whether you’re scanning products, medicine, parts or shipping labels, your data capture needs are dramatically shifting. Traceability demands more data in smaller spaces; mobile payments are on the rise; scanning multiple barcodes consumes valuable time, and there’s less tolerance for inefficiency – capabilities only imaging technology can ful?ll.
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future of technology, imaging scanners, barcode technology, inventory management, fast checkouts, managing processing data, barcode readers, camera-based scanners, 1d barcodes, omni-directional reading, enhanced scanner range, data capture, 2d barcodes, high density scanner, scanner identity verification, optical character recognition, barcode capabilities, 1d to 2d scanner, omnichannel, qr code measurement
    
Zebra Technologies
Published By: Red Hat, Inc.     Published Date: Jul 10, 2012
Today, as IT departments struggle to design and implement solutions capable of managing exponential data growth with strict requirements for application scale and performance, many of them are turning to in-memory data grids (IMDGs).
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it departments, data growth, managing data growth, application scale, application performance, in-memory data grids, imdgs, big data, data volume, data velocity, data variability, data management, data collection, data processing, data scaling, data storage systems, data access, data solutions, data challenges, management tooling
    
Red Hat, Inc.
Published By: Datastax     Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
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evolution, big data, technology, datastax, nosql
    
Datastax
Published By: Dell EMC     Published Date: Oct 08, 2015
This business-oriented white paper explains three options for starting your Hadoop journey. This paper also outlines the benefits of Hadoop and highlights some of the many use cases for this new approach to managing, storing and processing big data.
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Dell EMC
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