DOCSLIB.ORG

EVOLVING from CHRONIC DISEASE MANAGEMENT to PREVENTATIVE CARE: Healthcare Iot Data at the Edge

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
EVOLVING from CHRONIC DISEASE MANAGEMENT to PREVENTATIVE CARE: Healthcare Iot Data at the Edge 1 WHITE PAPER EVOLVING FROM CHRONIC DISEASE MANAGEMENT TO PREVENTATIVE CARE: Healthcare IoT Data at the Edge The healthcare industry has deployed Edge and Internet of identifying opportunities to derive actionable insights from Things (IoT) technologies across the care continuum for the Edge and IoT network and data, leveraging distributed over a decade. Initially, healthcare providers focused on analytics, Edge computing, 5G, artificial intelligence (AI), financial IoT use cases enabled by RFID sensors, such as and machine learning technologies. Investments are being inventory management. Today, with Edge and IoT devices prioritized for initiatives to streamline operational workflows generating enormous quantities of data from physician- for efficiency, safer patient care experiences, and ultimately, patient encounters and wearables, health leaders are the ability to better understand and predict care outcomes. WHITE PAPER | 2 The continued miniaturization of sensors has led to more computational capabilities and smarter connected devices. Intelligent devices at the Edge create valuable analytics opportunities by generating “small data,” which – in contrast to “big data” – provides individual data points analyzed at the Edge to deliver instantaneous insights enabling a treatment decision, behavior change, or alarm trigger. Each connected device or IoT sensor at the Edge generates small data points. When analyzed using big data analytics, these individual points reveal unexpected trends, patterns, and insights to improve care delivery. Caregivers COMPUTER VISION AT THE can proactively detect changes in the patient’s condition. HEALTHCARE EDGE Envision moving from disease management to disease Computer vision uses a camera as a sensor in the prevention, which encourages individuals to live healthier hospital, in an out-patient facility, or at home. lives and reduces overall healthcare costs. Powerful machine learning capabilities automate data analysis and pattern recognition, identify anomalies, and trigger responses. HEALTHCARE EDGE INTELLIGENCE THROUGH DISTRIBUTED ANALYTICS Computer vision can improve patient wellness in a Distributed analytics unlocks healthcare Edge and IoT data variety of ways – from identifying a patient in to see beyond episodic patient visits, creating a continuous extreme distress in an Emergency Room (ER) real-time patient record – 24/7/365 – with healthcare waiting room, to monitoring patient behaviors by providers gaining the tools to shift from a reactive to a confirming specific motions, such as the hand-to- proactive approach in support of value-based care. mouth motion of taking a pill. This type of motion capture is especially useful when conducting gait Leading healthcare providers are investing in distributed analysis to determine if a patient is a potential fall analytics to: risk. Sensors can also confirm the patient is performing prescribed physical therapy exercises • Improve patient safety and monitor recovery. and doing them correctly. Physicians can track Computer vision solutions can monitor acute patient progress over time to identify when and why safety and longer-term medical compliance to reduce progress stagnates. readmissions. Examples include: cameras and sensors that monitor patient and staff compliance with hand For use cases such as visitor and staff safety, sanitization policies to reduce infection rates, devices patient sitters, and pain monitoring, healthcare that ensure discharge instructions are followed organizations can leverage the Dell Technologies through physical therapy instruction and range of IoT Solution for Safety and Security, powered by motion monitoring, telesitters to improve patient safety Intel, a software-defined infrastructure system and reduce fall risk in post-acute care step-down with tightly integrated compute, storage, patients, and connected pill bottles that confirm networking, and virtualization resources to help medical adherence. improve system performance and lower total cost of ownership. It is purpose-built to a complex • Expand chronic disease management and camera-on-cloud infrastructure with support for preventative medicine. Sensors and devices enable demanding mixed data sources including video, continuous patient monitoring – alerting healthcare audio, barometric pressure, and more. providers to clinically meaningful changes and predicting potential candidates for early intervention. WHITE PAPER | 3 Examples include: smart mirrors that use intelligent • Manage pharmaceuticals and improve drug supply hardware and software to identify subtle, yet clinically chain safety. Edge and IoT devices and sensors can relevant changes in physique and appearance, FDA reduce the risks inherent in the highly vulnerable approved devices and sensors that provide in-home healthcare supply chain including temperature-related chronic disease (e.g. heart failure) monitoring, and and counterfeit risks. Examples include: devices that consumer wearables such as smart watches that track continuously monitor temperature changes in vaccines wellness indicators (e.g. respiratory patterns, sleep, and during transportation to ensure that safe temperature activity). range is maintained, RFID sensors that track medication from point of manufacture to point of • Provide researchers with new opportunities to consumption, and GPS-enabled shipping containers enhance precision medicine. Sensor-generated data, that improve inventory/waste management and combined with medical-grade software applications distinguish between goods in transit and goods stolen. make it possible to treat rare medical conditions previously too expensive to address. Examples include: Optimized analytics is also making telehealth more wearables and other sensors that are integrated into effective, as patients leverage virtual health consultations the clinical trial process to expedite study completion for condition assessments to manage chronic diseases and and improve compliance and reporting, digital to deploy remote monitoring. Keeping high-utilization, high therapeutic capabilities like applications that allow for risk patients managing multiple chronic conditions out of the automatic collection and use of individual health the emergency department through virtual health data, and built-in features that automatically remove capabilities offers the potential to further control healthcare PHI from sensor collected data before transmission to costs. Telehealth is expanding access to primary and comply with GDPR and HIPAA regulations–allowing specialty care with Centers of Medicare and Medicaid data aggregation across patient populations. Services (CMS) funding now available for telemedicine services and chronic care management, reimbursing care providers for telehealth services rendered. Figure 1: Simplify real-time insights at scale EDGE CORE CLOUD SECURITY │ MANAGEABILITY │ ANALYTICS WHITE PAPER | 4 Today, bandwidth limitations often prevent or slow data Cybersecurity tools and privacy protections must be transfer of video streams and patient-generated data from incorporated when building out an Edge and IoT wearables for central analysis. With healthcare Edge and ecosystem. With additional access points being introduced IoT analytics capabilities, physicians and specialists can into the system, we recommend addressing the security extract insights from telehealth data at the Edge – where it architecture alongside data collection and application is collected – transferring only the most clinically relevant development. Container-based security protects workloads data back to the care provider and creating opportunities through segmentation and can prevent a full system breach for effective remote care and downstream revenue. from a single-entry point. CONNECT CLOUD TO YOUR A ROADMAP TO CONNECTED HEALTH HEALTHCARE IOT EDGE Healthcare IoT solutions, sensors, and devices at the Edge, Real-time analytics at the Edge creates the opportunity to combined with analytics that turn small data into big identify, refine, and understand the data in place for the insights, are changing how care delivery is triaged, where it fastest possible insights and action. To support the is provided, and how it is monitored. Dell Technologies, in distributed network of data-driven devices, healthcare collaboration with Intel, offers a roadmap for healthcare organizations require a multi-faceted approach. providers to leverage Edge solutions to move from disease management to disease prevention. We partner with As healthcare organizations build their Edge and IoT hospitals, payers, and pharmaceutical companies to identify strategy, they need to evaluate their unique multi-cloud Edge and IoT objectives, construct a solution, and deliver approach in parallel with specific application workloads. the complete infrastructure. Depending on data classification, some data – such as the electronic medical record (EMR), laboratory information Together with our robust partner ecosystem, Dell systems (LIS), and/or clinical decision application data Technologies supports an AI-ready edge-to-core-to-cloud – may be stored on-premises. Other data may be stored in infrastructure, building a unified data repository, that allows the cloud – whether private, public, or hybrid. Healthcare for the automated labeling and tagging of data. For organizations should also consider how their data can flow applications that require immediate feedback, this data can securely and efficiently from the Edge, to the data center, be analyzed in
Load more

Recommended publications
  • Hype Cycle for Storage and Data Protection Technologies, 2020
    Hype Cycle for Storage and Data Protection Technologies, 2020 Published 6 July 2020 - ID G00441602 - 78 min read By Analysts Julia Palmer Initiatives:Data Center Infrastructure This Hype Cycle evaluates storage and data protection technologies in terms of their business impact, adoption rate and maturity level to help IT leaders build stable, scalable, efficient and agile storage and data protection platform for digital business initiatives. Analysis What You Need to Know The storage and data protection market is evolving to address new challenges in enterprise IT such as exponential data growth, changing demands for skills, rapid digitalization and globalization of business, requirements to connect and collect everything, and expansion of data privacy and sovereignty laws. Requirements for robust, scalable, simple and performant storage are on the rise. As the data center no longer remains the center of data, IT leaders expect storage to evolve from being delivered by rigid appliances in core data centers to flexible storage platforms capable of enabling hybrid cloud data flow at the edge and in the public cloud. Here, Gartner has assessed 24 of the most relevant storage and data protection technologies that IT leaders must evaluate to address the fast-evolving needs of the enterprise. For more information about how peer I&O leaders view the technologies aligned with this Hype Cycle, see “2020-2022 Emerging Technology Roadmap for Large Enterprises.” The Hype Cycle IT leaders responsible for storage and data protection must cope with the rapidly changing requirements of digital business, exponential data growth, introduction of new workloads, and the desire to leverage public cloud and enable edge capabilities.
    [Show full text]
  • Performance and Progress Report
    Performance and Progress Report NOAA Grant No: NA15NOS4000200 Project Title: Joint Hydrographic Center Report Period: 01/01/2016 – 12/31/2016 Lead Principal Investigator: Larry A. Mayer Principal Investigators Brian Calder John Hughes Clarke James Gardner David Mosher Colin Ware Thomas Weber Co-PIs Thomas Butkiewicz Jenn Dijkstra Semme Dijkstra Paul Johnson Thomas Lippmann Giuseppe Masetti Shachak Pe’eri Yuri Rzhanov Val Schmidt Briana Sullivan Larry Ward CONTENTS INTRODUCTION ........................................................................................................................................................ 3 INFRASTRUCTURE .................................................................................................................................................. 4 PERSONNEL .......................................................................................................................................................................... 4 Research Scientists and Staff .......................................................................................................................................... 9 NOAA Employees ......................................................................................................................................................... 14 Other Affiliated Faculty ................................................................................................................................................ 16 Visiting Scholars ..........................................................................................................................................................
    [Show full text]
  • Quarterly Enterprise Software Market Review 1Q 2019
    Quarterly Enterprise Software Market Review 1Q 2019 Boston San Francisco 200 Clarendon Street, Floor 45 601 Montgomery Street, Suite 2010 Boston, MA 02116 San Francisco, CA 94111 Peter M. Falvey Michael H.M. Shea Christopher J. Pingpank Michael S. Barker Managing Director Managing Director Managing Director Managing Director 617.896.2251 617.896.2255 617.896.2218 415.762.8101 [email protected] [email protected] [email protected] [email protected] Jeffrey G. Cook Brad E. McCarthy Misha Cvetkovic Principal Principal Vice President 617.896.2252 617.896.2245 415.762.8104 [email protected] [email protected] [email protected] www.shea-co.com Member FINRA & SIPC Copyright ©2019 Shea & Company Overview People ▪ Industry Expertise ▪ Process Excellence 1 2 24 15+ >70 Firm focused exclusively Offices in Boston and San Professionals focused on Years of experience Transactions completed on enterprise software Francisco the software industry amongst our senior representing billions of bankers dollars in value Mergers & Acquisitions Private Placements & Capital Raising Corporate Strategy ■ Sell-side and buy-side M&A advisory ■ Late-stage venture, growth equity and buyouts ■ Corporate development advisory ■ Divestitures ■ Recapitalizations ■ Balance sheet and capital structure review ■ Restructuring ■ IPO advisory ■ Fairness opinions has received an investment from has received an investment from Superior Outcomes has been acquired by has acquired Shea & Company has advised on important transactions representing billions of dollars in
    [Show full text]
  • End-Users Survey 2020 March 2020
    End-Users Survey 2020 March 2020 Published March 16th, 2020 Document #CR-2020-011-44 Introduction We ran an end-users survey in January 2020 to learn about storage related IT projects needs, collect users perceptions and understand their technologies adoptions. By end-users we mean companies that pick, deploy and used IT products to support their business activity and mission. We considered 2 populations – US and Europe – with respectively 1123 US companies and 560 European ones. For Europe, we limit our study to UK, Germany and France. Each of these countries represents approximately one third of the total European users. Users belong to the enterprise and SMB segments with 50% from each segment. Companies span several verticals in term of industries and use-cases. The study addresses technology adoption, projects priorities and products/features needs for a total of 20 questions. Each graphic is sorted by descending order for US. “We wished to understand end-users perspective beyond what we heard from vendors, so we asked a series of 20 questions to end-users across all verticals and industries and results are more than interesting with some surprises.” Philippe Nicolas Founder and Lead Analyst Coldago Research Copyright © 2020 Coldago Research End-Users Survey 2020 - March 2020 2 Questions about technologies and products #1: What are the technologies you will consider for new projects in 2020? What are the technologies you will consider for new projects in 2020? AFA Cloud Storage AF NAS Cloud Object Storage NVMe Array* Object Storage
    [Show full text]
  • The Arcati Mainframe Yearbook 2018
    ArcatiArcati MainframeMainframe YearbookYearbook 20072018 Mainframe strategy The Arcati Mainframe Yearbook 2018 The independent annual guide for users of IBM mainframe systems SPONSORED BY: PUBLISHED BY: Arcati Limited 19 Ashbourne Way Thatcham Berks RG19 3SJ UK Phone: +44 (0) 7717 858284 Fax: +44 (0) 1635 881717 Web: http://www.arcati.com/ E-mail: [email protected] © Arcati Limited, 2018 1 Arcati Mainframe Yearbook 2018 Mainframe strategy Contents Welcome to the Arcati Mainframe Yearbook 2018 ............................................................ 3 Staying secure and compliant ........................................................................................... 5 How to Ditch Waterfall for DevOps on the Mainframe ................................................... 10 Health Solutions Provider Accelerates Integration, Sparks IT Collaboration Using Server-Side JavaScript ............................................................. 16 z/OS Code Scanning Is Essential to System z® Security ............................................. 21 DevOps for the mainframe................................................................................................ 27 ‘Reports of my death have been greatly exaggerated’ .................................................. 33 The 2018 Mainframe User Survey .................................................................................... 36 An analysis of the profile, plans, and priorities of mainframe users Vendor Directory ..............................................................................................................
    [Show full text]
  • Welcome to the Age of Composable Infrastructure Kaminario Unveils Software-Defined, Composable Storage Solutions for the Modern Datacenter
    September 2018 Welcome to the Age of Composable Infrastructure Kaminario unveils software-defined, composable storage solutions for the modern datacenter. In this issue Kaminario is Changing the Way IT Deploys Enterprise-Class Solid State Storage Capability 2 Figure 1. Magic Quadrant for Solid-State Arrays1 3 Research from Gartner: Critical Capabilities for Solid-State Arrays 5 Kaminario is Changing the Way IT Deploys Enterprise-Class Solid State Storage Capability Software Defined meets Solid State Storage Kaminario has been in the business of delivering all- flash enterprise-class storage since 2011. Relying on a unique software-defined architecture, the Kaminario K2 has been rated among the most capable solid-state storage platforms by Gartner since 2014. Key to its differentiation, the ability to scale out for performance and scale up in capacity has made the Kaminario K2 one of the leading platforms for building cloud- scale application infrastructure. With the majority of Kaminario’s business coming from SaaS, Consumer Internet, or Cloud Service Providers, the company has seen, first hand, the evolving requirements for cloud- scale storage infrastructure. No Compromises on Technical Capability Kaminario’s software-defined architecture delivers true enterprise-class capability in a highly flexible, extremely cost-efficient storage solution leveraging 100% industry-standard hardware. Ranked a Leader in Gartner’s Magic Quadrant for the past two years, Kaminario’s unique technology solution competes favorably with traditional storage array solutions. The Kaminario K2 was ranked the highest for analytics and high performance computing and within the top three for all use cases in 2018 Gartner Critical Capabilities Report. 3 Figure 1.
    [Show full text]
  • Data Storage Architectures for Machine Learning and Artificial Intelligence On-Premises and Public Cloud
    REPORT Data Storage Architectures for Machine Learning and Artificial Intelligence On-Premises and Public Cloud ENRICO SIGNORETTI TOPICS: ARTIFICIAL INTELLIGENCE DATA STORAGE MACHINE LEARNING Data Storage Architectures for Machine Learning and Artificial Intelligence On-Premises and Public Cloud TABLE OF CONTENTS 1 Summary 2 Market Framework 3 Maturity of Categories 4 Considerations for Selecting ML/AI Storage 5 Vendors to Watch 6 Near-Term Outlook 7 Key Takeaways 8 About Enrico Signoretti 9 About GigaOm 10 Copyright Data Storage Architectures for Machine Learning and Artificial Intelligence 2 1. Summary There is growing interest in machine learning (ML) and artificial intelligence (AI) in enterprise organizations. The market is quickly moving from infrastructures designed for research and development to turn-key solutions that respond quickly to new business requests. ML/AI are strategic technologies across all industries, improving business processes while enhancing the competitiveness of the entire organization. ML/AI software tools are improving and becoming more user-friendly, making it easier to to build new applications or reuse existing models for more use cases. As the ML/AI market matures, high- performance computing (HPC) vendors are now joined by traditional storage manufacturers, that are usually focused on enterprise workloads. Even though the requirements are similar to that of big data analytics workloads, the specific nature of ML/AI algorithms, and GPU-based computing, demand more attention to throughputs and $/GB, primarily because of the sheer amount of data involved in most of the projects. Depending on several factors, including the organization’s strategy, size, security needs, compliance, cost control, flexibility, etc, the infrastructure could be entirely on-premises, in the public cloud, or a combination of both (hybrid) – figure 1.
    [Show full text]
  • IDC TECHNOLOGY SPOTLIGHT Sponsored By: VAST Data
    IDC TECHNOLOGY SPOTLIGHT Sponsored by: VAST Data Legacy architectures have imposed a siloed approach to storage infrastructure because of design limitations. New storage technologies such as NVMe over Fabrics, storage-class memory, and quad-level cell flash media open up the opportunity to transcend these limitations with a new universal storage platform. Transcending the Limitations of Legacy Storage Architectures Through New Solid State Technologies August 2020 Written by: Eric Burgener, Research Vice President, Infrastructure Systems, Platforms, and Technologies Introduction AT A GLANCE A perennial challenge in the information technology (IT) industry is how to create the most efficient IT infrastructure while continuing to meet WHAT'S IMPORTANT evolving performance, availability, manageability, and cost goals. Over the New solid state storage technologies offer past decade, vendors and customers alike have been experimenting with the opportunity to design a highly scalable storage architecture that transcends the software-defined shared nothing infrastructures that promised simpler limitations of legacy approaches. deployment, expansion, and management, but what has become increasingly clear in the past several years is that these types of systems KEY TAKEAWAYS pose significant challenges when customers try to operate them at scale. » Enabling solid state storage technologies As vendors and customers look to deploy the types of IT infrastructure include NVMe over Fabrics, storage-class memory (3D XPoint), and quad-level cell they need to meet the requirements of the digital era, there has been a flash media. marked move back toward more disaggregated architectures. The » The resulting disaggregrated, shared hyperscalers — providers such as Facebook, Amazon, and Microsoft that everything storage architecture has led the original experiment with shared nothing designs in large-scale web already changed how leading-edge IT infrastructure — have been very public about their moves back toward organizations view legacy array designs.
    [Show full text]
  • Heading for Convergence
    power 2012 Issue 03 solutions 2012 Issue Your guide to maximizing IT efficiency dell.com/powersolutions 03 Heading for convergence Adopting a converged IT infrastructure and advanced virtualization opens the way to boundless opportunities— and convincing cost-efficiencies Heading for convergence Rapid transition: Modernizing data centers with converged infrastructure Fast deployment: Targeting use cases for virtualized integrated infrastructure with Dell vStart Agile infrastructure: Deploying the Dell Converged Blade Data Center architecture Change agent: Q&A with Dell Global CIO Adriana Karaboutis on how IT can be a catalyst of change DPS-201203-STD US$18.95 CAN$19.95 US$18.95 Find the cloud you didn’t know you already had. Do more with Dell cloud solutions You have cloud-ready systems already in place. Dell’s open virtualization and cloud solutions powered by Intel® create efficiencies within your existing infrastructure, giving you the tangible business benefits of the private cloud. Learn more at Dell.com/cloud. Intel and the Intel logo are trademarks of Intel Corporation in the U.S. and other countries. 50120388-cloud.indd 1 8/3/12 10:23 AM 2012 Issue 03 10 Cover story Heading for convergence By Andy Rhodes, Benjamin A. Tao, and Marc Stitt Modernizing data centers with a converged infrastructure can lead to convincing business agility gains. Widespread adoption of convergence heightens application and IT service delivery to drive emerging opportunities with exceptional cost-efficiency. 16 Targeting use cases for fast deployment of virtualized integrated infrastructure Stepped-up demand to accelerate IT service delivery and extend virtualization benefits to vital applications is driving the move to integrate compute stacks.
    [Show full text]
  • Distributed Deep Learning Infrastructure for Autonomous Driving
    Whitepaper Dell Technologies Solution: Distributed Deep Learning Infrastructure for Autonomous Driving Enabled by Dell EMC™ Isilon F800 and Dell EMC™ PowerEdge C4140 with NVIDIA V100 GPUs Abstract This document demonstrates the design and architecture of a large-scale deep learning infrastructure for the development of autonomous driving use cases. It also showcases the results on how the Dell EMC™ Isilon F800 All-Flash scale- out NAS powered by PowerScale OneFS and Dell EMC™ PowerEdge C4140 with NVIDIA® V100 GPUs can be used to accelerate and scale deep learning training workloads. Benchmark results based on detection and segmentation use cases are created by using prominent, automotive-grade and publicly available datasets. July 2020 H18298 Revisions Revisions Date Description June 2020 Initial release July 2020 Branding update Acknowledgements Author: Frances Hu ([email protected]) Support: Florian Baumann ([email protected]), Frank Han ([email protected]) Other: Jacci Cenci ([email protected]) The information in this publication is provided “as is.” Dell Inc. makes no representations or warranties of any kind with respect to the information in this publication, and specifically disclaims implied warranties of merchantability or fitness for a particular purpose. Use, copying, and distribution of any software described in this publication requires an applicable software license. Copyright © June 2020 Dell Inc. or its subsidiaries. All Rights Reserved. Dell Technologies, Dell, EMC, Dell EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries. Other trademarks may be trademarks of their respective owners. [7/9/2020] [Whitepaper] [H18298] 2 Dell Technologies Solution: Distributed Deep Learning Infrastructure for Autonomous Driving | H18298 Table of contents Table of contents Revisions............................................................................................................................................................................
    [Show full text]
  • Optimizing Data Warehouse Configurations for Peak Efficiency
    Data management Optimizing data warehouse configurations for peak efficiency By Satheesh Iyer Reference architectures and best practices enable enterprises to capitalize on their information resources. Building on Microsoft guidelines, Dell has engineered end-to-end data warehousing solutions utilizing Microsoft® SQL Server® database software. he proliferation of data from vast collections of data and historical capacity and performance within their diverse sources has a significant information quickly and efficiently, allowing data warehouse systems. And none impact on data center workers to derive meaningful insights too soon. Counterproductive increases T operations. An efficient, highly that advance business and organizational in response time are resulting from a scalable data warehousing strategy helps outcomes. For this reason, data warehouses convergence of factors such as escalating enterprises manage the volume, velocity, are rapidly becoming essential elements data volumes and their related loading and variety of data running into and across in the IT infrastructure, as organizations demands, mounting complexity of online the organization, enabling them to tap the harness data to identify trends, provide analytical processing (OLAP) queries, and immense potential of big data for a distinct business intelligence reporting, and perform a rising number of end users. competitive advantage. predictive analyses (see Figure 1). Best practices and guidelines jointly Adopting an effective data warehousing To deliver on this vision, organizations developed by Dell and Microsoft can assist strategy enables enterprises to mine need to strike the optimal balance of IT staff in designing and implementing a Preprinted from Dell Power Solutions, 2012 Issue 3. Copyright © 2012 Dell Inc. All rights reserved. Preprinted from Dell Power Solutions, 2012 Issue 3.
    [Show full text]
  • Elite 80 the Hottest Privately Held Cybersecurity and It Infrastructure Companies
    Cybersecurity & IT Infrastructure APRIL 2021 ELITE 80 THE HOTTEST PRIVATELY HELD CYBERSECURITY AND IT INFRASTRUCTURE COMPANIES Copyright: Shutterstock/Paopano Erik Suppiger [email protected] (415) 835-3918 FOR DISCLOSURE AND FOOTNOTE INFORMATION, REFER TO JMP FACTS AND DISCLOSURES SECTION. Cybersecurity & IT Infrastructure TABLE OF CONTENTS Executive Summary ....................................................................................................................................................................................... 4 Funding Trends .............................................................................................................................................................................................. 5 Index by Venture Capital Firm ..................................................................................................................................................................... 11 Aqua Security ............................................................................................................................................................................................... 15 Arctic Wolf .................................................................................................................................................................................................... 16 Armis ...........................................................................................................................................................................................................
    [Show full text]