Cloud computing offers a very important approach to achieving lasting strategic advantages by rapidly adapting to complex challenges in IT management and data analytics. This paper discusses the business impact and analytic transformation opportunities of cloud computing. Moreover, it highlights the differences among two cloud architectures—Utility Clouds and Data Clouds—with illustrative examples of how Data Clouds are shaping new advances in Intelligence Analysis.
Cloud Computing Security: Government Acquisition Considerations for the Cloud...Booz Allen Hamilton
This study provides insight into information assurance and mission assurance challenges posed by public cloud computing environments (CCE), and how accounting for those risks through acquisition security measures affect public CCE options.
Shifting Risks and IT Complexities Create Demands for New Enterprise Security...Booz Allen Hamilton
Holistic Cyber Risk Management Programs in the Financial Industry Must "Predict and Prevent" in Today's Complex Threat Environment, says new White Paper.
Strategic Information Management Through Data ClassificationBooz Allen Hamilton
This white paper presents a comprehensive approach to information management programs. It outlines how data growth directly affects the risk posture of critical corporate information assets. In addition, it defines common problems caused by gaps in information management programs as well as consequences associated with immature methodologies.
Cloud Computing IT Lexicon's Latest Hot SpotTech Mahindra
Cloud computing, a highly flexible deployment model is emerging because of enhancing interdependence of business and IT. Effective and efficient resource sharing, interconnecting between people, department and companies is possible because of this emerging technology. Cloud computing also provides a stable environment where Telcos can improve business outcomes by leveraging their experience in offering IT centric managed services. Though not without its flaws, cloud computing looks to change the way companies do business in the near future.
Cloud Computing Security: Government Acquisition Considerations for the Cloud...Booz Allen Hamilton
This study provides insight into information assurance and mission assurance challenges posed by public cloud computing environments (CCE), and how accounting for those risks through acquisition security measures affect public CCE options.
Shifting Risks and IT Complexities Create Demands for New Enterprise Security...Booz Allen Hamilton
Holistic Cyber Risk Management Programs in the Financial Industry Must "Predict and Prevent" in Today's Complex Threat Environment, says new White Paper.
Strategic Information Management Through Data ClassificationBooz Allen Hamilton
This white paper presents a comprehensive approach to information management programs. It outlines how data growth directly affects the risk posture of critical corporate information assets. In addition, it defines common problems caused by gaps in information management programs as well as consequences associated with immature methodologies.
Cloud Computing IT Lexicon's Latest Hot SpotTech Mahindra
Cloud computing, a highly flexible deployment model is emerging because of enhancing interdependence of business and IT. Effective and efficient resource sharing, interconnecting between people, department and companies is possible because of this emerging technology. Cloud computing also provides a stable environment where Telcos can improve business outcomes by leveraging their experience in offering IT centric managed services. Though not without its flaws, cloud computing looks to change the way companies do business in the near future.
Booz Allen’s data lake approach enables agencies to embed security controls within each individual piece of data to reinforce existing layers of security and dramatically reduce risk. Government agencies – including military and intelligence agencies – are using this proven security approach to secure data and fully capitalize on the promise of big data and the cloud.
When you’re planning to move to the cloud and manage a hybrid environment, security is a top concern. But cloud is not necessarily less secure than a traditional environment. In fact, it may be possible to deliver even greater security in a hybrid cloud environment because it offers new and advanced opportunities.
In this eBook, you’ll discover how hackers are using traditional tactics in new ways to attack the cloud. You’ll also find out how the cloud can help you increase security with innovative approaches designed to detect threats long before they threaten your enterprise.
Is your infrastructure holding you back?Gabe Akisanmi
This ebook will help you connect the dots between
today’s biggest business opportunities and the specific
technology required to seize them. You’ll get the facts
you need to identify where current components may
be falling short—and how the right investments in infrastructure
can lead to better business outcomes while
strengthening your role as a strategic consultant within
your organization.
Cloud Analytics Ability to Design, Build, Secure, and Maintain Analytics Solu...YogeshIJTSRD
Cloud Analytics is another area in the IT field where different services like Software, Infrastructure, storage etc. are offered as services online. Users of cloud services are under constant fear of data loss, security threats, and availability issues. However, the major challenge in these methods is obtaining real time and unbiased datasets. Many datasets are internal and cannot be shared due to privacy issues or may lack certain statistical characteristics. As a result of this, researchers prefer to generate datasets for training and testing purposes in simulated or closed experimental environments which may lack comprehensiveness. Advances in sensor technology, the Internet of things IoT , social networking, wireless communications, and huge collection of data from years have all contributed to a new field of study Big Data is discussed in this paper. Through this analysis and investigation, we provide recommendations for the research public on future directions on providing data based decisions for cloud supported Big Data computing and analytic solutions. This paper concentrates upon the recent trends in Big Data storage and analysing, in the clouds, and also points out the security limitations. Rajan Ramvilas Saroj "Cloud Analytics: Ability to Design, Build, Secure, and Maintain Analytics Solutions on the Cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43728.pdf Paper URL: https://www.ijtsrd.com/other-scientific-research-area/other/43728/cloud-analytics-ability-to-design-build-secure-and-maintain-analytics-solutions-on-the-cloud/rajan-ramvilas-saroj
Secure Digital Transformation- Cybersecurity Skills for a Safe Journey to Dev...Troy Marshall
CyCon 3.0 presentation- February 15, 2020
Successful digital transformations don’t begin with technology, they begin with people. As organizations adopt DevOps and cloud and realize the increased release velocity, ensuring the security of software and systems at the same velocity is a necessity but doing so isn’t easy. In this talk you will learn about common security challenges in DevOps and cloud and the skills cybersecurity professionals need to solve these challenges.
Enabling Big Data with Data-Level Security:The Cloud Analytics Reference Arch...Booz Allen Hamilton
; Booz Allen’s data lake approach enables agencies to embed security controls within each individual piece of data to reinforce existing layers of security and dramatically reduce risk. Government agencies – including military and intelligence agencies – are using this proven security approach to secure data and fully capitalize on the promise of big data and the cloud.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
In this eBook, we will uncover the specifics of how a
hybrid cloud solution can transform IT management so
that you can become the leader your business needs.
We will compare traditional and hybrid requirements with
respect to three critical areas: how you’ll govern the
system, the management tools you’ll need, and what
your management opportunities will be.
Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Cloud computing is a hot topic all over the world nowadays, through which customers can access information and computer power via a web browser. As the adoption and deployment of cloud computing increase, it is critical to evaluate the performance of cloud environments. Currently, modeling and simulation technology has become a useful and powerful tool in cloud computing research community to deal with these issues. Cloud simulators are required for cloud system testing to decrease the complexity and separate quality concerns. Cloud computing means saving and accessing the data over the internet instead of local storage. In this paper, we have provided a short review on the types, models and architecture of the cloud environment.
BIG DATA SECURITY AND PRIVACY ISSUES IN THE CLOUD IJNSA Journal
Many organizations demand efficient solutions to store and analyze huge amount of information. Cloud computing as an enabler provides scalable resources and significant economic benefits in the form of reduced operational costs. This paradigm raises a broad range of security and privacy issues that must be taken into consideration. Multi-tenancy, loss of control, and trust are key challenges in cloud computing environments. This paper reviews the existing technologies and a wide array of both earlier and state-ofthe-art projects on cloud security and privacy. We categorize the existing research according to the cloud reference architecture orchestration, resource control, physical resource, and cloud service management layers, in addition to reviewing the recent developments for enhancing the Apache Hadoop security as one of the most deployed big data infrastructures. We also outline the frontier research on privacy-preserving data-intensive applications in cloud computing such as privacy threat modeling and privacy enhancing solutions.
Big data security and privacy issues in theIJNSA Journal
Many organizations demand efficient solutions to store and analyze huge amount of information. Cloud computing as an enabler provides scalable resources and significant economic benefits in the form of reduced operational costs. This paradigm raises a broad range of security and privacy issues that must be taken into consideration. Multi-tenancy, loss of control, and trust are key challenges in cloud computing environments. This paper reviews the existing technologies and a wide array of both earlier and state-ofthe-art projects on cloud security and privacy. We categorize the existing research according to the cloud reference architecture orchestration, resource control, physical resource, and cloud service management layers, in addition to reviewing the recent developments for enhancing the Apache Hadoop security as one of the most deployed big data infrastructures. We also outline the frontier research on privacy-preserving data-intensive applications in cloud computing such as privacy threat modeling and privacy enhancing solutions.
Booz Allen’s data lake approach enables agencies to embed security controls within each individual piece of data to reinforce existing layers of security and dramatically reduce risk. Government agencies – including military and intelligence agencies – are using this proven security approach to secure data and fully capitalize on the promise of big data and the cloud.
When you’re planning to move to the cloud and manage a hybrid environment, security is a top concern. But cloud is not necessarily less secure than a traditional environment. In fact, it may be possible to deliver even greater security in a hybrid cloud environment because it offers new and advanced opportunities.
In this eBook, you’ll discover how hackers are using traditional tactics in new ways to attack the cloud. You’ll also find out how the cloud can help you increase security with innovative approaches designed to detect threats long before they threaten your enterprise.
Is your infrastructure holding you back?Gabe Akisanmi
This ebook will help you connect the dots between
today’s biggest business opportunities and the specific
technology required to seize them. You’ll get the facts
you need to identify where current components may
be falling short—and how the right investments in infrastructure
can lead to better business outcomes while
strengthening your role as a strategic consultant within
your organization.
Cloud Analytics Ability to Design, Build, Secure, and Maintain Analytics Solu...YogeshIJTSRD
Cloud Analytics is another area in the IT field where different services like Software, Infrastructure, storage etc. are offered as services online. Users of cloud services are under constant fear of data loss, security threats, and availability issues. However, the major challenge in these methods is obtaining real time and unbiased datasets. Many datasets are internal and cannot be shared due to privacy issues or may lack certain statistical characteristics. As a result of this, researchers prefer to generate datasets for training and testing purposes in simulated or closed experimental environments which may lack comprehensiveness. Advances in sensor technology, the Internet of things IoT , social networking, wireless communications, and huge collection of data from years have all contributed to a new field of study Big Data is discussed in this paper. Through this analysis and investigation, we provide recommendations for the research public on future directions on providing data based decisions for cloud supported Big Data computing and analytic solutions. This paper concentrates upon the recent trends in Big Data storage and analysing, in the clouds, and also points out the security limitations. Rajan Ramvilas Saroj "Cloud Analytics: Ability to Design, Build, Secure, and Maintain Analytics Solutions on the Cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43728.pdf Paper URL: https://www.ijtsrd.com/other-scientific-research-area/other/43728/cloud-analytics-ability-to-design-build-secure-and-maintain-analytics-solutions-on-the-cloud/rajan-ramvilas-saroj
Secure Digital Transformation- Cybersecurity Skills for a Safe Journey to Dev...Troy Marshall
CyCon 3.0 presentation- February 15, 2020
Successful digital transformations don’t begin with technology, they begin with people. As organizations adopt DevOps and cloud and realize the increased release velocity, ensuring the security of software and systems at the same velocity is a necessity but doing so isn’t easy. In this talk you will learn about common security challenges in DevOps and cloud and the skills cybersecurity professionals need to solve these challenges.
Enabling Big Data with Data-Level Security:The Cloud Analytics Reference Arch...Booz Allen Hamilton
; Booz Allen’s data lake approach enables agencies to embed security controls within each individual piece of data to reinforce existing layers of security and dramatically reduce risk. Government agencies – including military and intelligence agencies – are using this proven security approach to secure data and fully capitalize on the promise of big data and the cloud.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
In this eBook, we will uncover the specifics of how a
hybrid cloud solution can transform IT management so
that you can become the leader your business needs.
We will compare traditional and hybrid requirements with
respect to three critical areas: how you’ll govern the
system, the management tools you’ll need, and what
your management opportunities will be.
Cloud computing is Internet based development and use of computer technology. It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them. Cloud computing is a hot topic all over the world nowadays, through which customers can access information and computer power via a web browser. As the adoption and deployment of cloud computing increase, it is critical to evaluate the performance of cloud environments. Currently, modeling and simulation technology has become a useful and powerful tool in cloud computing research community to deal with these issues. Cloud simulators are required for cloud system testing to decrease the complexity and separate quality concerns. Cloud computing means saving and accessing the data over the internet instead of local storage. In this paper, we have provided a short review on the types, models and architecture of the cloud environment.
BIG DATA SECURITY AND PRIVACY ISSUES IN THE CLOUD IJNSA Journal
Many organizations demand efficient solutions to store and analyze huge amount of information. Cloud computing as an enabler provides scalable resources and significant economic benefits in the form of reduced operational costs. This paradigm raises a broad range of security and privacy issues that must be taken into consideration. Multi-tenancy, loss of control, and trust are key challenges in cloud computing environments. This paper reviews the existing technologies and a wide array of both earlier and state-ofthe-art projects on cloud security and privacy. We categorize the existing research according to the cloud reference architecture orchestration, resource control, physical resource, and cloud service management layers, in addition to reviewing the recent developments for enhancing the Apache Hadoop security as one of the most deployed big data infrastructures. We also outline the frontier research on privacy-preserving data-intensive applications in cloud computing such as privacy threat modeling and privacy enhancing solutions.
Big data security and privacy issues in theIJNSA Journal
Many organizations demand efficient solutions to store and analyze huge amount of information. Cloud computing as an enabler provides scalable resources and significant economic benefits in the form of reduced operational costs. This paradigm raises a broad range of security and privacy issues that must be taken into consideration. Multi-tenancy, loss of control, and trust are key challenges in cloud computing environments. This paper reviews the existing technologies and a wide array of both earlier and state-ofthe-art projects on cloud security and privacy. We categorize the existing research according to the cloud reference architecture orchestration, resource control, physical resource, and cloud service management layers, in addition to reviewing the recent developments for enhancing the Apache Hadoop security as one of the most deployed big data infrastructures. We also outline the frontier research on privacy-preserving data-intensive applications in cloud computing such as privacy threat modeling and privacy enhancing solutions.
This paper summarizes the results of our research around data center transformation, and discusses the kind of metrics and visibility you will need to successfully migrate and manage applications in a true, high-performance Infrastructure Anywhere environment.
Efficient and reliable hybrid cloud architecture for big databaseijccsa
The objective of our paper is to propose a Cloud computing framework which is feasible and necessary for
handling huge data. In our prototype system we considered national ID database structure of Bangladesh
which is prepared by election commission of Bangladesh. Using this database we propose an interactive
graphical user interface for Bangladeshi People Search (BDPS) that use a hybrid structure of cloud
computing handled by apache Hadoop where database is implemented by HiveQL. The infrastructure
divides into two parts: locally hosted cloud which is based on “Eucalyptus” and the remote cloud which is
implemented on well-known Amazon Web Service (AWS). Some common problems of Bangladesh aspect
which includes data traffic congestion, server time out and server down issue is also discussed.
iStart hitchhikers guide to cloud computingHayden McCall
Many pundits agree that
2011 is set to become the year of
The Cloud and that IT professionals
need to prepare themselves. While everyone
seems to be talking about “The Cloud” in excited
tones, do we really understand what it’s all about?
iStart helps demystify what it all means and
navigates a clear path through all the hype.
What are the implications of ‘going public’
and staying private? By Chris Bell
http://www.istart.com.au
EDF2013: Invited Talk Julie Marguerite: Big data: a new world of opportunitie...European Data Forum
Invited Talk Julie Marguerite, THALES, at the European Data Forum 2013, 9 April 2013 in Dublin, Ireland: Big data: a new world of opportunities for software services
Over the past five years, cloud computing has gone from a curiosity to
core scientific technology. The cloud's relative simplicity, instant
availability, and reasonable cost have made it attractive to
scientists, especially in domains relatively new to large scale data
analysis. This trend will continue into the foreseeable future,
challenging resource providers to adapt their services, to provide
easy federation with other providers, and to accommodate many
different scientific disciplines. For developers of cloud services,
there are also many challenges. Efficient access to, and the curation
of large data sets remain largely unsolved problems. Image
management also raises new issues, especially if these images are to
be shared and trusted. This presentation reviews the current status
of cloud computing and presents some ideas on how the upcoming
challenges might be met.
Presented at CNAF in Bologna, Italy by Charles Loomis in May 2013.
Similar to Massive Data Analytics and the Cloud (20)
You Can Hack That: How to Use Hackathons to Solve Your Toughest ChallengesBooz Allen Hamilton
“Hackathon” has become a trendy word in today’s business vernacular, and for good reason. The word “hackathon” comes from both “hack” and “marathon.” If you think of a “hack” as a creative solution and “marathon” as a continuous, often competitive event, you’re at the heart of what a hackathon is about. Hackathons enable creative problem solving through an innovative and often competitive structure that engages stakeholders to come up with unconventional solutions to pressing challenges. Hackathons can be used to develop new processes, products, ways of thinking, or ways of engaging stakeholders and partners, with benefits ranging from solving tough problems to broader cultural and organizational improvements.
This playbook was designed to make hackathons accessible to everyone. That means not only can all kinds of organizations benefit from hackathons, but that all kinds of employees inside those groups—executives, project managers, designers, or engineers—should participate and can benefit, too. Use this playbook as a reference and allow the best practices we outline to guide you in designing a hackathon structure that works for you and enables your organization to achieve its desired outcomes. Give yourself anywhere from six weeks to a few months to plan your hackathon, depending on the components, approach, number of participants, and desired outcomes.
Contact Director Brian MacCarthy at MacCarthy_Brian2@bah.com for more information about Booz Allen’s hackathon offering.
Booz Allen's U.S. Commercial Leader and Executive Vice President, Bill Phelps, recently released his list of 10 Cyber Priorities for Boards of Directors. As we peer into how business, technology, regulatory, and cyber threat realities are evolving in the coming year, here is a reference guide for board members to use in validating their company's cybersecurity approach.
We looked at the data. Here’s a breakdown of some key statistics about the nation’s incoming presidents’ addresses, how long they spoke, how well, and more.
Our Military Spouse Forum built a roadmap to help you navigate your career between deployments, moves, and the unpredictable. Interested in how Booz Allen can help you navigate your career? Check out our opportunities at www.boozallen.com/careers
In August 2016, Booz Allen partnered with Market Connections to conduct a survey of National Security Leaders and the General Public to understand their perspectives on the current threats. Fifteen years after the September 11 attacks, we wanted to know what keeps them up at night today, and what they will be worried about in 15 years. This infographic provides the high-level results of our survey and we will be releasing a more detailed report later in the month of September – so stay tuned. #NationalSecurity2031
Booz Allen convened some of the smartest minds to explore making healthcare more accessible. This report shares the latest healthcare payment trends and what policy experts discovered when planning for different health reform scenarios.
An interactive workshop that guides you through the many relationships that exist in an agile team, with a business value emphasis. Team members gain empathy, discover expectations of others and the importance of these agile team relationships.
An immersive environment allows students to be completely “immersed” in a self-contained simulated or artificial environment while experiencing it as real. With immersive learning, you can show realistic visual and training environments to teach complex tasks and concepts.
Nuclear Promise: Reducing Cost While Improving PerformanceBooz Allen Hamilton
To remain competitive, nuclear operators must take aim at all addressable costs, ensuring maintenance is optimized, taking proactive steps to minimize unplanned outages and, where possible, reducing administrative and other overhead costs. There are multiple opportunities to reduce capital and operational spending, while improving safety and reliability.
General Motors and Lyft; Target and Walmart; Netflix and Amazon - we call these “frenemies”. A strange trend is emerging as unlikely partner companies join forces, and they’re transforming industries around the world. Understanding what's driving the frenemies trend, knowing what options best fit your needs, and making yourself an effective partner are all critical to success.
Threats to industrial control systems are on the rise. This briefing explores potential threats and vulnerabilities as well as what organizations can do to guard against them.
Booz Allen Hamilton and Market Connections: C4ISR Survey ReportBooz Allen Hamilton
Booz Allen Hamilton partnered with government market research firm Market Connections, Inc. to conduct the survey of military decision-makers. The research examined the main features of Integrated C4ISR through Enterprise Integration: engineering, operations and acquisition. Two-thirds of respondents (65 percent) agree agile incremental delivery of modular systems with integrated capabilities can enable rapid insertion of new technologies.
Modern C4ISR Integrates, Innovates and Secures Military NetworksBooz Allen Hamilton
A majority of the military believe Integrated C4ISR through Enterprise Integration would provide utility to their organization. Check out other key findings from our study in this infographic http://bit.ly/1OZOjG2
Agile and Open C4ISR Systems - Helping the Military Integrate, Innovate and S...Booz Allen Hamilton
Integrated C4ISR is a force multiplier that significantly improves situational awareness and decision making to give warfighters a decisive battlefield advantage. This advantage stems from Booz Allen Hamilton’s Enterprise Integration approach http://bit.ly/25nDBRg: bringing together three disciplines and their communities—engineering, operations, and acquisition.
Booz Allen Hamilton created the Field Guide to Data Science to help organizations and missions understand how to make use of data as a resource. The Second Edition of the Field Guide, updated with new features and content, delivers our latest insights in a fast-changing field. http://bit.ly/1O78U42
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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Massive Data Analytics and the Cloud
1. Massive Data Analytics and the Cloud
A Revolution in Intelligence Analysis
by
Michael Farber
farber_michael@bah.com
Mike Cameron
cameron_mike@bah.com
Christopher Ellis
ellis_christopher@bah.com
Josh Sullivan, Ph.D.
sullivan_joshua@bah.com
2.
3. Massive Data Analytics and the Cloud
A Revolution in Intelligence Analysis
Cloud computing offers a very important approach to way organizations store, access, and process massive
achieving lasting strategic advantages by rapidly adapting amounts of disparate data via massively parallel and
to complex challenges in IT management and data distributed IT systems. These technologies include
analytics. This paper discusses the business impact and Hadoop, MapReduce, BigTable, and other emergent
analytic transformation opportunities of cloud computing. Data Cloud technologies. Historically, the amount of
Moreover, it highlights the differences among two cloud processing power that could be applied constrained
architectures—Utility Clouds and Data Clouds—with the ability to analyze intelligence. Consequently, data
illustrative examples of how Data Clouds are shaping new representation and processing were restricted by the
advances in Intelligence Analysis. amount of available processing power. Complex data
models and normalization became common, and data
Intelligence Analysis Transformation was forced into models that did not fully represent
Until the advent of the Information Age, the process
all aspects of data. Understanding the emergence of
of Intelligence Analysis was one of obtaining and
”big data,” data reflection, and massively scalable
combining sparse and often denied data to derive
processing can lead to new insights for Intelligence
intelligence. Analysis needs were well-understood,
Analysis, as demonstrated by Google®, Yahoo!®,
with consistent enemies and smooth data growth
and Amazon®, which leverage cloud computing and
patterns. With the advent of the Information Age, the
Data Clouds to power their businesses. Booz Allen’s
Internet, and rapidly evolving and multi-layered methods
experience with cloud computing ideally positions
of disseminating information, including wikis, blogs,
the firm to support current and future clients in
e-mail, virtual worlds, online games, VoIP telephone,
understanding and adopting cloud computing solutions.
digital photos, instant messages (IM), and tweets, the
raw data and reflections of data on nearly everyone
Understanding the Differences Between
and their every activity are becoming increasingly
available. This availability and constant growth of
Data Clouds and Utility Clouds
Cloud computing offers a wide range of technologies
such vast amounts of disparate data is turning the
that support the transformation of data analytics.
Intelligence Analysis problem on its head, transforming
As outlined by the National Institute of Standards
it from a process of “stitching together sparse data
and Technology (NIST), cloud computing is a model
to derive conclusions” to a process of “extracting
“for enabling available, convenient, on-demand
conclusions from aggregation and distillation of
network access to a shared pool of configurable
massive data and data reflections.”1
computing resources (e.g., networks, servers,
Cloud computing provides new capabilities for storage, applications, services) that can be rapidly
performing analysis across all data in an organization. provisioned and released with minimal management
It uses new technical approaches to store, search, effort or service provider interaction.”2 A number of
mine, and distribute massive amounts of data. Cloud cloud computing deployment models exist, such as
computing allows analysts and decision makers to ask public clouds, private clouds, community clouds, and
ad-hoc analysis questions of massive volumes of data hybrids. Moreover, two major cloud computing design
in very quick and precise ways. New cloud computing patterns are emerging: Utility Clouds and Data Clouds.
technologies are driving analytic transformation in the These distinctions are not mutually exclusive; rather,
1 Discussions with US Government Computational Sciences Group. 2 US National Institute of Standards. http://groups.google.com/group/cloudforum/web/
nist-working-definition-of-cloud-computing.
1
4. Exhibit 1 | Relationship of Utility Clouds and Data Clouds
Massively Parallel Compute
DATA CLOUD
Highly Scalable Multi-
Dimensional Databases
Distributed Highly Fault-
Tolerant Massive Storage
CLOUD
COMPUTING
UTILITY CLOUD
Software as a
Service (Saas)
Platform as a Service (Paas)
Infrastructure as a Service (Iaas)
Source: Booz Allen Hamilton
these designs can work cooperatively to provide multi-tenancy is a security model that separates and
economies of scale, resiliency, security, scalability, protects data and processing. In fact, security—
and analytics at world scale. As illustrated in Exhibit focused on ensuring data segmentation, integrity, and
1, fundamentally different mission objectives drive access control—is one of the most critical design
Utility Clouds and Data Clouds. Utility Clouds focus drivers of Utility Cloud architectures.
on offering infrastructure, platforms, and software
In contrast, the main objective of Data Clouds is the
as services that many users consume. These basic
aggregation of massive data. Data Clouds have an
building blocks of cloud computing are essential to
architectural approach of dividing processing tasks into
achieving real solutions at scale. Data Clouds can
smaller units distributed to servers across the cluster
leverage those utility building blocks to provide data
with co-location of computing and storage capabilities,
analytics, structured data storage, databases, and
allowing highly scaled computation across all of the
massively parallel computation, which allow analysts
data in the cloud. The Data Cloud design pattern
unprecedented access to mission data and shared
typifies data-intensive and processing-intensive usage
analysis algorithms.
scenarios without regard to concepts used in the Utility
Specifically, Utility Clouds focus on providing IT Cloud model, such as virtualization and multi-tenancy.
capabilities as a service; e.g., Infrastructure as a
Exhibit 2 contains a comparison of Data Clouds
Service (IaaS), Platform as a Service (PaaS), and
and Utility Clouds. The difference between these
Software as a Service (SaaS). This service model
two architectures is seen in industry. Amazon is an
scales by allowing multiple constituencies to share
excellent model for Utility Cloud computing, and Google
IT assets, called multi-tenancy. Key to enabling
is an excellent model for Data Cloud computing.
2
5. Cloud Computing Can Solve Problems Consider a social network analysis problem from
Previously Out of Reach Facebook® This problem was impossible to solve
.
More than just a new design pattern, cloud computing before the advent of cloud computing:3
comprises a range of technologies that enable new With 400 to 500 million users and billions of page
forms of analysis that were previously computationally views every day, Facebook accumulates massive
impossible or too difficult to attempt. These business amounts of data. One of the challenges it has faced
and mission problems are intractable to solve in the since its early days is developing a scalable way of
context of traditional IT design and delivery models and storing and processing all these bytes since historical
have often ended in failed or underwhelming results. data is a major driver of business innovation and the
Cloud computing allows research into these problems, user experience on Facebook. This task can only be
opening new business opportunities and new outreach accomplished by empowering Facebook’s engineers and
to clients with large amounts of data. analysts with easy to use tools to mine and manipulate
Much of the current cloud computing discussion large data sets. At some point, there isn’t a bigger
focuses on utility computing, economies of scale, server to buy, and the relational database stops scaling.
and migration of current capabilities to the cloud. To drive the business forward, Facebook needed a way
Refocusing the conversation to new business to query and correlate roughly 15 terabytes of new
opportunities that empower decision makers and social network data each day, in different languages, at
analysts to ask previously un-askable questions is the different times, often from mixed media (e.g., web, IM,
emerging power of the cloud. SMS) streaming in from hundreds of different sources.
What does the cloud allow us to do that we could Moreover, Facebook needed a massively parallel
not do before? Compute-intensive problems, such as processing framework and a way to safely and securely
large-scale image processing, sensor data correlation, store large volumes of data. Several computationally
social network analysis, encryption/decryption, data impossible problems were lingering at Facebook.
mining, simulations, and pattern recognition, are strong One of the most interesting of these problems was
examples of problems that can be solved in the cloud the Facebook Lexicon, a data analysis program that
computing domain. would first allow a user to select a word and would
Exhibit 2 | Comparison of Data and Utility Clouds
Data Clouds Utility Clouds
• Computing architecture for large-scale data processing • Computing services for outsourced IT operations
and analytics
• Concurrent, independent, multi-tenant user population
• Designed to operate at trillions of operations/day,
• Service offerings such as SaaS, PaaS, and IaaS
petabytes of storage
• Characterized by data segmentation, hosted
• Designed for performance, scale, and data processing
applications, low cost of ownership, and elasticity
• Characterized by run-time data models and simplified
development models
Source: Booz Allen Hamilton
3 arma, Joydeep Sen. “Hadoop.” Facebook, June 5, 2008. http://www.facebook.com/
S
notes.php?id=9445547199#!/note.php?note_id=16121578919.
3
6. then scan all available data at Facebook (which grows Distributed Highly Fault-Tolerant Massive Storage
by 15 terabytes per day), calculate the frequency of The foundation of Data Cloud computing is the ability
the word’s occurrence, and graphically display the to reliably store and process petabytes of data using
information over time. This task was not possible in a non-specialized hardware and networking. In practice,
traditional IT solution because of the large number of this form of storage has required a new way of
users, size of data, and time to process. But the Data thinking about data storage. The Google File System
Cloud allows Facebook to leverage more than 8,500 (GFS) and Hadoop Distributed File System (HDFS)
Central Processing Unit (CPU) cores and petabytes of are two examples of proven approaches to creating
disk space to create rich data analytics on a wide range distributed highly fault-tolerant massive storage
of business characteristics. The Data Cloud allows systems. Several attributes of highly fault-tolerant
analysts and technical leaders at Facebook to rapidly massive storage systems are key innovations in the
write analytics in the software language of their choice. Data Cloud design pattern:4
Subsequently, these analytics run over massive amounts
• Is reliable, allowing distributed storage and
of data, condensing down to small, personalized analysis
replication of bytes across networks and hardware
results. These results can then be stored in a traditional
assumed to fail at anytime
relational database, allowing existing reporting and
financial tools to remain unchanged but to still benefit • Allows for massive, world-scale storage that
from the computational power of the cloud. Facebook separates metadata from data
is now investigating a data warehousing layer that rides
• Supports a write-once, sporadic append, read-many
in the cloud and is capable of making decisions and
usage structure
courses of action based on millions of inputs.
• Stores very large files, often each greater than 1
The same capabilities inherent in the Facebook Data
terabyte in size
Cloud are available to other organizations in their own
Data Cloud. Cloud computing is a transformative force • Allows compute cycles to be easily moved to the data
addressing size, speed, and scale, with a low cost of store, instead of moving data to a processer farm.
entry and very high potential benefits. The first step
These attributes are especially important for
toward exploring the power of cloud computing is to
Intelligence Analysis. First, a large-scale distributed
understand the taxonomy differences between Data
storage system, which leverages readily available
Clouds and Utility Clouds.
commercial hardware, offers a method of replication
across many physical sites for data redundancy.
Data Cloud Design Features Vast amounts of data can be reliably stored across
The Data Cloud model offers a transformational
a distributed system without costly storage-network
effect to Intelligence Analysis. Unlike current data
arrays, reducing the risk of storing mission-critical data
warehousing models, the Data Cloud design begins
in one central location. Second, because massive scale
by assuming an organization needs to rapidly store
is achieved horizontally (by adding hardware) the ability
and process massive amounts of chaotic data that is
to gauge and predict data growth rates across the
spread across the enterprise, distressed by differing
enterprise becomes dramatically easier by provisioning
time sequences, and burdened with noise.
hardware at the leading edge of a Data Cloud vice in
Several key attributes of the Data Cloud design pattern independent storage silos for different projects.
are specifically remarkable for Intelligence Analysis and
are discussed in the following sections.
4 hemawat, Sanjay; Gobioff, Howard; and Leung, Shun-Tak. “The Google File System.”
G
Appeared in 19th ACM Symposium on Operating Systems Principles, Lake George, NY,
October 2003. http://labs.google.com/papers/gfs.html.
4
7. Highly Scalable Multi-Dimensional Databases inserted into the database with little or no modification.
The distributed highly fault-tolerant massive storage The database is designed to hold many unique forms
system lacks the ability to fully represent structured of data, allowing a query-time schema to be generated
data, providing only the raw data storage required when data is retrieved, instead of an a priori schema
in the Data Cloud. Moving beyond raw data storage defined when the database is first installed. This is
to representing structured data requires a highly extremely valuable because as new data arrives in a
scalable database system. Traditional relational format not seen before, instead of lengthy modifications
database systems are the ubiquitous design solution to the database schema or complicated parsing to
for structured data storage in conventional enterprise force the data into a relational model, the data can
applications. Many relational database systems simply be stored in the native format. By leveraging a
support multi-terabyte tables, relationships, and multi-dimensional database system that treats all data
complex Structured Query Language (SQL) engines, as bytes, scales to massive sizes, and allows users to
which provide reliable, well-understood data schemas. ask questions of the bytes at query-time, organizations
It is very important to understand that relational have a new choice. Multi-dimensional databases are
database systems are the best solution for many types in stark contrast to today’s highly normalized relational
of problems, especially when data is highly structured data model, which includes schemas, relationships,
and volume is less than 10 terabytes. However, a new and pre-determined storage formats stored on one or
class of problem is emerging when dealing with big several clustered database servers.
data of volumes greater than 10 terabytes. Although
Moreover, the power of multi-dimensional databases
relational database models are capable of running in a
allows computations to be “pre” computed. For
Data Cloud, many current relational database systems
instance, several large Internet content providers mine
fail in the Data Cloud in two important ways. First,
millions of data points every hour to pre-compute the
many relational database systems cannot scale to
best advertisements to show users the next time they
support petabytes or greater amounts of data storage,
visit one of the provider’s sites. Instead of pulling a
or the database requires highly specialized components
random advertisement or performing a search when
to accomplish ever-diminishing increases in scale.
the page is requested, these providers pre-compute
Second, and critically important to Intelligence Analysis,
the best advertisements to show everyone, at
is the impedance mismatch that occurs as complex
anytime, on any of their sites based on historical data,
data is normalized into a relational table format.
advertisement click rates, probability of clicking, and
When data is collected, often the first step is to revenue models. Similarly, a large US auto insurance
transform the data, normalize the data, and insert a firm leverages multi-dimensional databases to
row into a relational database. Next, users query data pre-compute the insurance quote for every car in the
based on keywords or pre-loaded search queries and United States each night. If a caller asks for a quote,
wait for the results to return. Once returned, users sift the firm can instantly tell the caller a price because
through results. it was already computed overnight based on many
input sources.5 The highly scalable nature of such
Multi-dimensional databases offer a fundamentally
databases allows for massive computational power.
different model. The distributed and highly scalable
design of multi-dimensional databases means data is There are some major analytic implications here. First,
stored and searched as billions of rows with billions a computing framework such as a Data Cloud that,
of columns across hundreds of servers. Even more by design, can scale to handle petabytes of mission
interesting, these forms of databases do not require data and perform intensive computation across
schemas or predefined definitions of their structure. all the data, all the time means new insights and
When new data arrives in an unfamiliar format, it can be discoveries are now possible by looking at big data in
5 aker, Stephen. “The Two Flavors of Google.” Businessweek.com, December 13, 2007.
B
http://www.businessweek.com/magazine/content/07_52/b4064000281756.htm.
5
8. many different ways. Consider the corollaries between 1,000 nodes, bringing extensive analytic processing
Intelligence Analysis and the massive correlation/ capabilities to users in the enterprise.
prediction engines at eHarmony® and Netflix® which
,
Working in tandem with the distributed file system
leverage regression algorithms across massive data
and the multi-dimensional database, the MapReduce
sets to compute personality, character traits, hidden
framework leverages a master node to divide large
relationships, and group tendencies. These data-driven
jobs into smaller tasks for worker nodes to process.
analytic systems leverage the attributes of Data Clouds
The framework, capable of running on thousands of
but target specialized behavioral analysis to advance
machines, attempts to maintain a high level of affinity
their particular business. Hulu® a popular online
,
between data and processing, which means the
television website, uses the Data Cloud to process
framework intelligently moves the processing close
many permutations of log files about the shows people
to the data to minimize bandwidth needs. Moving the
are watching.5
compute job to the data is easier than moving large
amounts of data to a central bank of processors.
Massively Parallel Compute (Analytic Algorithms)
Moreover, the framework manages extrapolative errors,
Parallel computing is a well-adopted technology
noticing when a worker in the cloud is taking a long
seen in processor cores and software thread-based
time on one of these tasks or has failed altogether and
parallelism. However, massively parallel processing—
automatically tasks another node with completing the
leveraging thousands of networked commodity servers
same task. All these details and abstractions are built
constrained only by bandwidth—is now the emerging
into the framework. Developers are able to focus on the
context for the Data Cloud.
analytic value of the jobs they create and no longer worry
If distributed file systems, such as GFS and HDFS, about the specialized complexities of massively parallel
and column-oriented databases are employed to computing. An intelligence analyst is able to write 10
store massive volumes of data, there is then a need to 20 lines of computer code, and the MapReduce
to analyze and process this data in an intelligent framework will convert it into a massively parallel
fashion. In the past, writing parallel code required search—working against petabytes of data across
highly trained developers, complex job coordination, thousands of machines—without requiring the analyst
and locking services to ensure nodes did not overwrite to know or understand any of these technical details.
each other. Often, each parallel system would develop
Tasks such as sorting, data mining, image
unique solutions for each of these problems. These
manipulation, social network analysis, inverted index
and other complexities inhibited the broad adoption of
construction, and machine learning are prime jobs
massively parallel processing, meaning that building
for MapReduce. In another scenario, assume that
and supporting the required hardware and software
terabytes of aerial imagery have been collected
was reserved for dedicated systems.
for intelligence purposes. Even with an algorithm
MapReduce, a framework pioneered by Google, has available to detect tanks, planes, or missile silos,
overcome many of these previous barriers and allows the task of finding these weapons could take days
for data-intensive computing while abstracting the if run in a conventional manner. Processing 100
details of the Data Cloud away from the developer. terabytes of imagery on a standard computer takes
This ability allows analysts and developers to quickly 11 days. Processing the same amount of data on
create many different parallelized analytic algorithms 1,000 standard computers takes 15 minutes. By
that leverage the capabilities of the Data Cloud. incorporating MapReduce, each image or part of an
Consequently, the same MapReduce job crafted to image becomes its own task and can be examined
run on a single node can as easily run on a group of in a parallel manner. Distributing this work to many
5 aker, Stephen. “The Two Flavors of Google.” Businessweek.com, December 13, 2007.
B
http://www.businessweek.com/magazine/content/07_52/b4064000281756.htm.
6
9. computers drastically cuts the time for this job and • Batch Processing Systems—Log file analysis,
other large tasks, scales the performance linearly by nightly automated relationship matching, regression
adding commodity hardware, and ensures reliability testing, and financial analysis
through data and task replication.
• Unpredictable Content—Web portals or intelligence
dissemination systems that vary widely in usage
Programmatic Models for Scaling in the Data Cloud
based on time of day, temporal content stores for
Building applications and the architectures that
conferences, or National Special Security Events.
run in the Data Cloud requires new thinking about
scale, elasticity, and resilience. Cloud application Clearly, applications that can leverage the Data Cloud
architectures follow two key tenets: (1) only use can take advantage of the ubiquitous infrastructure
computing resources when needed (elasticity) and (2) that already exists within the cloud, elastically drawing
survive drastically changing data volumes (scalability). on resources as needed based on scale. Moreover,
Much of this work is accomplished by designing cloud the efficient application of computing resources across
applications to dynamically scale by dynamically the cloud and the rapid ability to decrease processing
processing asynchronously queued events. As a result, time through massive parallelization is a transformative
any number of jobs can be submitted to the Data force for many stages of Intelligence Analysis.
Cloud, and those jobs are persistently queued for
resilience until completed. The jobs are then removed Conclusion
from a queue and distributed across any number of Cloud computing has the potential to transform
worker nodes, drawing on resources in the cloud on how organizations use computing power to create a
demand. When the work is complete, these jobs are collaborative foundation of shared analytics, mission-
closed and the resources returned to the cloud. centric operations, and IT management. Challenges to
the implementation of cloud computing remain, but the
These features, working in concert, achieve scalability
new analytic capabilities of big data, ad-hoc analysis,
across computers and data volume, elasticity of
and massively scalable analytics—combined with the
resource utilization, and resilience for assured
security and financial advantages of switching to a cloud
operational readiness. These forms of application
computing environment—are driving research across the
architecture address the difficulties of massive data
cloud ecosystem. Cloud computing technology offers a
processing. The cloud abstracts the complexities of
very important approach to achieving lasting strategic
resource provisioning, error handling, parallelization,
advantage by rapidly adapting to complex challenges in
and scalability, allowing developers to trade
IT management and data analytics.
sophistication for scale.
The following actions leverage the power of the
Data Cloud:6
• Processing Pipelines—Document or image
processing, video transcoding, indexing data, and
data mining
6 aria, Jinesh. Cloud Architectures. Amazon, June 16, 2008. http://jineshvaria.
V
s3.amazonaws.com/public/cloudarchitectures-varia.pdf.
7
10. About Booz Allen
Booz Allen Hamilton has been at the forefront of strategy rapidly deploy talent and resources, and deliver enduring
and technology consulting for nearly a century. Today, results. By combining a consultant’s problem-solving
Booz Allen is a leading provider of management and orientation with deep technical knowledge and strong
technology consulting services to the US government execution, Booz Allen helps clients achieve success in
in defense, intelligence, and civil markets, and to major their most critical missions—as evidenced by the firm’s
corporations, institutions, and not-for-profit organizations. many client relationships that span decades. Booz Allen
In the commercial sector, the firm focuses on leveraging helps shape thinking and prepare for future developments
its existing expertise for clients in the financial services, in areas of national importance, including cybersecurity,
healthcare, and energy markets, and to international clients homeland security, healthcare, and information technology.
in the Middle East. Booz Allen offers clients deep functional
Booz Allen is headquartered in McLean, Virginia, employs
knowledge spanning strategy and organization, engineering
more than 25,000 people, and had revenue of $5.59
and operations, technology, and analytics—which it
billion for the 12 months ended March 31, 2011. Fortune
combines with specialized expertise in clients’ mission and
has named Booz Allen one of its “100 Best Companies
domain areas to help solve their toughest problems.
to Work For” for seven consecutive years. Working Mother
The firm’s management consulting heritage is the basis has ranked the firm among its “100 Best Companies for
for its unique collaborative culture and operating model, Working Mothers” annually since 1999. More information
enabling Booz Allen to anticipate needs and opportunities, is available at www.boozallen.com. (NYSE: BAH)
To learn more about the firm and to download digital versions of this article and other Booz Allen Hamilton
publications, visit www.boozallen.com.
Contact Information:
Michael Farber Mike Cameron Christopher Ellis Josh Sullivan, Ph.D.
Senior Vice President Principal Principal Principal
farber_michael@bah.com cameron_mike@bah.com ellis_christopher@bah.com sullivan_joshua@bah.com
240-314-5671 301-543-4432 301-419-5147 301-543-4611
8