Big Data on AWS
The document discusses how the cloud is well suited to support big data applications and analytics. It notes that the cloud provides elastic, on-demand infrastructure that optimizes resources and reduces costs compared to traditional IT. This allows organizations to focus on analyzing and using big data rather than managing infrastructure. The cloud also enables the collection and storage of massive datasets. Examples are given of companies using cloud-based big data for applications like risk analysis, recommendations, and targeted advertising.
Intel Developer Forum: Taming the Big Data Tsunami
using Intel® Architecture by Clive D’Souza, Solutions Architect, Intel Corporation and
Dhruv Bansal, Chief Science Officer, Infochimps
Driving Towards Cloud 2015: A Technology Vision to Meet the Demands of Cloud ...Intel IT Center
1) Cloud computing is driving a transformation in IT that will require new technologies to meet demands for flexibility, security, and energy efficiency.
2) Key technical areas to focus on include matching workloads to specialized platforms, embracing heterogeneity, automating operations, developing big data analytics capabilities, and adapting computing across data centers, local servers, and edge devices.
3) Quantifying resource usage through improved monitoring and metering will also be important for scheduling workloads efficiently and accurately billing customers based on their actual infrastructure demands.
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Sdi technologies and implementation patterns (compress)Marco Wagemakers
This document discusses spatial data infrastructure (SDI) technologies and implementation patterns. It provides examples of SDI implementations at various geographic levels from local to global. It also describes how SDI can address issues like environment, social issues, and economics. The document highlights the INSPIRE initiative as an example of an SDI and how ArcGIS can be used to support INSPIRE. It discusses how SDI is evolving with new technologies and patterns like GIS online to make spatial data and services more accessible to a wider audience.
Cetas Analytics as a Service for Predictive AnalyticsJ. David Morris
This document discusses how predictive analytics using big data can lead to successful recommendations and revenue maximization. It describes trends in data growth, the value of data analytics exceeding hardware costs, and how a unified analytics cloud platform can simplify infrastructure and optimize resources. Sample predictive analytics applications are outlined for industries like ecommerce, mobile, advertising, gaming, and IT, with the goal of revenue maximization and user engagement through recommendation engines and targeted placements. The cloudification of predictive analytics as an analytics-as-a-service approach is presented as the logical conclusion to fully leverage big data.
This document discusses how predictive analytics using big data leads to successful recommendations and revenue maximization. It outlines key trends like the growth of new data sources and analyzes how companies are using predictive analytics in applications like ecommerce, mobile, advertising, and gaming to optimize customer engagement and maximize profits. The document advocates taking predictive analytics to its logical conclusion through cloud-based analytics-as-a-service and leveraging big data to directly monetize insights from predictive modeling.
The document discusses cloud computing from an enterprise perspective. It provides an overview of NICTA, an Australian research organization, and its work on cloud computing solutions. It then summarizes a proof of concept experience conducted by NICTA for an enterprise, covering workload suitability for cloud, technical architecture, migration issues, and business/commercial considerations. Finally, it discusses challenges of software engineering for and in the cloud, such as data and architectural differences, and NICTA's current and future research in this area.
Building IT Infrastructures to Interact with Big Data - Doug Roberts, Associ...IT Network marcus evans
Doug Roberts, a speaker at the marcus evans CIO Summit 2012, discusses how CIOs can handle and interact with big data sets.
Interview with: Doug Roberts, Associate Vice President for Digital Technologies and Chief Technology Officer, Adler Planetarium and Astronomy Museum
Intel Developer Forum: Taming the Big Data Tsunami
using Intel® Architecture by Clive D’Souza, Solutions Architect, Intel Corporation and
Dhruv Bansal, Chief Science Officer, Infochimps
Driving Towards Cloud 2015: A Technology Vision to Meet the Demands of Cloud ...Intel IT Center
1) Cloud computing is driving a transformation in IT that will require new technologies to meet demands for flexibility, security, and energy efficiency.
2) Key technical areas to focus on include matching workloads to specialized platforms, embracing heterogeneity, automating operations, developing big data analytics capabilities, and adapting computing across data centers, local servers, and edge devices.
3) Quantifying resource usage through improved monitoring and metering will also be important for scheduling workloads efficiently and accurately billing customers based on their actual infrastructure demands.
Big Data World Forum (BDWF http://www.bigdatawf.com/) is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.
Sdi technologies and implementation patterns (compress)Marco Wagemakers
This document discusses spatial data infrastructure (SDI) technologies and implementation patterns. It provides examples of SDI implementations at various geographic levels from local to global. It also describes how SDI can address issues like environment, social issues, and economics. The document highlights the INSPIRE initiative as an example of an SDI and how ArcGIS can be used to support INSPIRE. It discusses how SDI is evolving with new technologies and patterns like GIS online to make spatial data and services more accessible to a wider audience.
Cetas Analytics as a Service for Predictive AnalyticsJ. David Morris
This document discusses how predictive analytics using big data can lead to successful recommendations and revenue maximization. It describes trends in data growth, the value of data analytics exceeding hardware costs, and how a unified analytics cloud platform can simplify infrastructure and optimize resources. Sample predictive analytics applications are outlined for industries like ecommerce, mobile, advertising, gaming, and IT, with the goal of revenue maximization and user engagement through recommendation engines and targeted placements. The cloudification of predictive analytics as an analytics-as-a-service approach is presented as the logical conclusion to fully leverage big data.
This document discusses how predictive analytics using big data leads to successful recommendations and revenue maximization. It outlines key trends like the growth of new data sources and analyzes how companies are using predictive analytics in applications like ecommerce, mobile, advertising, and gaming to optimize customer engagement and maximize profits. The document advocates taking predictive analytics to its logical conclusion through cloud-based analytics-as-a-service and leveraging big data to directly monetize insights from predictive modeling.
The document discusses cloud computing from an enterprise perspective. It provides an overview of NICTA, an Australian research organization, and its work on cloud computing solutions. It then summarizes a proof of concept experience conducted by NICTA for an enterprise, covering workload suitability for cloud, technical architecture, migration issues, and business/commercial considerations. Finally, it discusses challenges of software engineering for and in the cloud, such as data and architectural differences, and NICTA's current and future research in this area.
Building IT Infrastructures to Interact with Big Data - Doug Roberts, Associ...IT Network marcus evans
Doug Roberts, a speaker at the marcus evans CIO Summit 2012, discusses how CIOs can handle and interact with big data sets.
Interview with: Doug Roberts, Associate Vice President for Digital Technologies and Chief Technology Officer, Adler Planetarium and Astronomy Museum
This document discusses cloud computing and its benefits. Brent Stineman, a National Cloud Solution Specialist with nearly 20 years of IT experience, will be presenting on the topics of what cloud computing is, the different types and delivery models of cloud, and why organizations should consider cloud. The cloud allows organizations to access computing resources on-demand in a pay-as-you-go manner and gain benefits such as flexibility, scalability, and reducing the need for large up-front capital expenditures on infrastructure.
Brent Stineman is a national cloud solution specialist with nearly 20 years of IT experience. He gave a presentation on cloud computing that discussed what the cloud is, the different types and delivery models of cloud computing, the benefits of using the cloud for organizations and customers, factors to consider in determining when an organization is ready to use the cloud, how to identify cloud opportunities within an organization, and took questions at the end.
Rethinking Disaster Prepardness to Leverage Resources in a Cloud and Mobile World: Presentation given at the 2012 Tennessee Higher Education Symposium (THEITS) - In many respects the disaster recovery plans of today are based upon the environments of old where commodity hardware, cloud resources and mobile devices didn’t exist. In November of 2011 the Tennessee Board of Regents office became the first public higher education organization to move its ERP system to the cloud by having it hosted at the state’s new data center. The following January, state auditors came on site to perform a routine biennial audit. The audit process included an information systems and disaster recovery component which led to a complete rethinking of disaster recovery in the new environment. This presentation chronicled the issues of moving mission critical systems to the cloud and how cloud resources from various sources coupled with mobile devices can be incorporated for cost effective disaster recovery planning.
IBM Storage Strategy in the Era of Smarter ComputingTony Pearson
This document discusses IBM's storage strategy in the era of smarter computing. It explains how IBM's storage products are designed for data, tuned to specific workloads, and managed with cloud technologies. Storage is designed for data by enabling insights from big data through features like real-time compression and deduplication. Products are tuned to tasks by matching workloads with optimized platforms. Storage is managed with cloud technologies through integrated service management and flexible sourcing options like public clouds.
2012 RightScale Conference NYC - State of the CloudRightScale
RightScale CEO Michael Crandell will share the latest market developments, successful cloud approaches, and key takeaways from our experience delivering a cloud management solution to more than 55,000 RightScale users.
Dr. Shahbaz Ali, CEO at Tarmin - Business Transformation in the Age of Big DataGlobal Business Events
This document discusses big data and its growth. It defines big data as datasets that are too large to capture, store, manage, share, analyze and visualize with typical database tools. It notes the explosion of unstructured data from sources like social media, sensors, and financial transactions. Examples of using big data include getting insights from remote patient monitoring, product sensors, location data and surveys to improve healthcare, manufacturing, services and marketing. The document also covers opportunities and threats of big data, and examples of big data use cases.
Cutting Big Data Down to Size with AMD and DellAMD
Matt Kimball, AMD Server Solutions Marketing presentation on "Cutting Big Data Down to Size with AMD and Dell" from Dell World.
Learn how “Hadoop” solutions are helping companies overcome growing pressures on IT budgets with an innovative approach to Big Data.
The document discusses how exponential data growth is straining centralized cloud infrastructure and driving up costs due to lack of economies of scale. It argues that a more distributed and decentralized approach is needed to better manage and leverage the vast amount of unused capacity at the edge. This includes distributing data across devices, networks, and data centers instead of concentrating it within massive centralized data centers. A hybrid model is proposed that keeps some functions like policy centralized while pushing processing and storage out closer to where the data is created and used.
The document discusses the increasing scale of genomic and biological data sets and the computational challenges they present. It describes several large-scale genomic projects including the Human Genome Project, sequencing additional species, and the 1000 Genomes Project. These projects have generated data sets ranging from gigabytes to terabytes to petabytes in size. The document argues that making these vast data sets and associated computational resources available through the cloud, like Amazon Web Services, allows more groups to tackle important problems that were previously unfeasible due to infrastructure limitations.
The document discusses NVIDIA's developments in artificial intelligence including its DGX SuperPOD deployment with 280 DGX A100 systems. It also summarizes the improvements in cost and power efficiency between a traditional AI data center and one utilizing 5 DGX A100 systems. Additionally, it outlines NVIDIA's educational resources and programs to support AI startups like the Inception program.
Emerging Big Data & Analytics Trends with Hadoop InnoTech
The document discusses big data opportunities with Hadoop solutions from EMC. It describes how big data is transforming business through use cases in healthcare, financial services, and utilities. EMC addresses challenges of the Hadoop platform through its Isilon scale-out NAS storage and Greenplum's unified analytics platform. The solutions provide enterprise-grade data protection, management, and scalability for Hadoop implementations.
The document discusses how NVIDIA has helped advance GPU computing and artificial intelligence over the past 25 years. It summarizes some of NVIDIA's key accomplishments, including developing the first programmable GPU in 1999, powering many of the world's fastest supercomputers and AI systems, and creating technologies like CUDA that have accelerated AI research and applications. The document also outlines how NVIDIA's Volta GPU architecture and platforms like DGX-2 are further advancing AI and high performance computing.
The document discusses the future of cloud computing and the Internet of Things (IoT). It covers several topics:
1) The evolution and current state of cloud computing including public, private, hybrid, and community cloud models.
2) Technical pillars of IoT including RFID, wireless sensor networks, machine-to-machine communication, and SCADA systems.
3) The relationship between cloud computing and IoT, and how they will converge with mobile cloud computing.
4) Emerging paradigms like MAI and XaaS for connecting IoT devices within and outside organizations via the cloud.
Why cloud computing:
Cloud computing can be a cheaper, faster, and greener alternative to an On-premises solution. Without any infrastructure
investments, you can get Powerful software and massive computing resources quickly—with lower Up-front costs and fewer
management headaches down the road. Cloud-based solutions when evaluating options for new IT deployments Whenever a
secure, reliable, cost-effective cloud option exists. Shifting your agency into the cloud can be a big decision, with many
Considerations. This guide is the first in a series designed to help you Get started. The most important is the right choice
software as a service as a service, infrastructure as a service, and platform as a service or hybrid cloud. While addressing
administration goals of scalable, interactive citizen Portals. The cloud can also help your agency increase collaboration across
Organizations, deliver volumes of data to citizens in useful ways, and reduce IT costs while helping your agency focus on
mission-critical tasks. Plus, the Cloud can help you maintain operational efficiency during times of crisis.
http://docplayer.net/search/?q=assem+abdel+hamed+mousa
http://www.ipoareview.org/wp-content/uploads/2016/05/Statement-by-Dr.Assem-Abdel-Hamied-Mousa-President-of-the-Association-of-Scientists-Developers-and-FacultiesASDF.pdf
This document provides an overview of Microsoft's StreamInsight Complex Event Processing (CEP) platform. It discusses CEP concepts and benefits, the StreamInsight architecture and development environment, and deployment scenarios. The presentation aims to introduce IT professionals to CEP and Microsoft's StreamInsight solution for building event-driven applications that process streaming data with low latency.
Big Data is growing rapidly in terms of volume, variety, and velocity. The cloud is well-suited to handle Big Data challenges by providing elastic and scalable infrastructure, which optimizes resources and reduces costs compared to traditional IT. In the cloud, users can collect, store, analyze and share large amounts of data without upfront investment, and scale easily as needs change. Real-world examples show how companies in industries like banking, retail, and advertising are using the cloud's Big Data services to gain insights from large datasets.
This document discusses how the cloud is well suited to address the challenges of big data. It notes that big data sets are getting larger and more complex, requiring new tools and approaches. The cloud optimizes precious IT resources by enabling elastic scaling, global accessibility, easy experimentation, and reducing costs. The cloud empowers users to balance costs and time. Several real-world examples are provided, such as banks using the cloud to perform Monte Carlo simulations and retailers using it for targeted recommendations and click stream analysis.
Big data and cloud computing are closely intertwined. The cloud is well-suited to handle big data challenges by providing massive scalability, flexible pay-as-you-go pricing, and removing the undifferentiated heavy lifting of managing infrastructure. This allows companies to focus on analyzing large and complex datasets. Examples show how companies use Amazon Web Services to collect petabytes of data from sources like sensors and social media, process it using services like EMR, and gain insights for applications in various industries.
This document discusses cloud computing and its benefits. Brent Stineman, a National Cloud Solution Specialist with nearly 20 years of IT experience, will be presenting on the topics of what cloud computing is, the different types and delivery models of cloud, and why organizations should consider cloud. The cloud allows organizations to access computing resources on-demand in a pay-as-you-go manner and gain benefits such as flexibility, scalability, and reducing the need for large up-front capital expenditures on infrastructure.
Brent Stineman is a national cloud solution specialist with nearly 20 years of IT experience. He gave a presentation on cloud computing that discussed what the cloud is, the different types and delivery models of cloud computing, the benefits of using the cloud for organizations and customers, factors to consider in determining when an organization is ready to use the cloud, how to identify cloud opportunities within an organization, and took questions at the end.
Rethinking Disaster Prepardness to Leverage Resources in a Cloud and Mobile World: Presentation given at the 2012 Tennessee Higher Education Symposium (THEITS) - In many respects the disaster recovery plans of today are based upon the environments of old where commodity hardware, cloud resources and mobile devices didn’t exist. In November of 2011 the Tennessee Board of Regents office became the first public higher education organization to move its ERP system to the cloud by having it hosted at the state’s new data center. The following January, state auditors came on site to perform a routine biennial audit. The audit process included an information systems and disaster recovery component which led to a complete rethinking of disaster recovery in the new environment. This presentation chronicled the issues of moving mission critical systems to the cloud and how cloud resources from various sources coupled with mobile devices can be incorporated for cost effective disaster recovery planning.
IBM Storage Strategy in the Era of Smarter ComputingTony Pearson
This document discusses IBM's storage strategy in the era of smarter computing. It explains how IBM's storage products are designed for data, tuned to specific workloads, and managed with cloud technologies. Storage is designed for data by enabling insights from big data through features like real-time compression and deduplication. Products are tuned to tasks by matching workloads with optimized platforms. Storage is managed with cloud technologies through integrated service management and flexible sourcing options like public clouds.
2012 RightScale Conference NYC - State of the CloudRightScale
RightScale CEO Michael Crandell will share the latest market developments, successful cloud approaches, and key takeaways from our experience delivering a cloud management solution to more than 55,000 RightScale users.
Dr. Shahbaz Ali, CEO at Tarmin - Business Transformation in the Age of Big DataGlobal Business Events
This document discusses big data and its growth. It defines big data as datasets that are too large to capture, store, manage, share, analyze and visualize with typical database tools. It notes the explosion of unstructured data from sources like social media, sensors, and financial transactions. Examples of using big data include getting insights from remote patient monitoring, product sensors, location data and surveys to improve healthcare, manufacturing, services and marketing. The document also covers opportunities and threats of big data, and examples of big data use cases.
Cutting Big Data Down to Size with AMD and DellAMD
Matt Kimball, AMD Server Solutions Marketing presentation on "Cutting Big Data Down to Size with AMD and Dell" from Dell World.
Learn how “Hadoop” solutions are helping companies overcome growing pressures on IT budgets with an innovative approach to Big Data.
The document discusses how exponential data growth is straining centralized cloud infrastructure and driving up costs due to lack of economies of scale. It argues that a more distributed and decentralized approach is needed to better manage and leverage the vast amount of unused capacity at the edge. This includes distributing data across devices, networks, and data centers instead of concentrating it within massive centralized data centers. A hybrid model is proposed that keeps some functions like policy centralized while pushing processing and storage out closer to where the data is created and used.
The document discusses the increasing scale of genomic and biological data sets and the computational challenges they present. It describes several large-scale genomic projects including the Human Genome Project, sequencing additional species, and the 1000 Genomes Project. These projects have generated data sets ranging from gigabytes to terabytes to petabytes in size. The document argues that making these vast data sets and associated computational resources available through the cloud, like Amazon Web Services, allows more groups to tackle important problems that were previously unfeasible due to infrastructure limitations.
The document discusses NVIDIA's developments in artificial intelligence including its DGX SuperPOD deployment with 280 DGX A100 systems. It also summarizes the improvements in cost and power efficiency between a traditional AI data center and one utilizing 5 DGX A100 systems. Additionally, it outlines NVIDIA's educational resources and programs to support AI startups like the Inception program.
Emerging Big Data & Analytics Trends with Hadoop InnoTech
The document discusses big data opportunities with Hadoop solutions from EMC. It describes how big data is transforming business through use cases in healthcare, financial services, and utilities. EMC addresses challenges of the Hadoop platform through its Isilon scale-out NAS storage and Greenplum's unified analytics platform. The solutions provide enterprise-grade data protection, management, and scalability for Hadoop implementations.
The document discusses how NVIDIA has helped advance GPU computing and artificial intelligence over the past 25 years. It summarizes some of NVIDIA's key accomplishments, including developing the first programmable GPU in 1999, powering many of the world's fastest supercomputers and AI systems, and creating technologies like CUDA that have accelerated AI research and applications. The document also outlines how NVIDIA's Volta GPU architecture and platforms like DGX-2 are further advancing AI and high performance computing.
The document discusses the future of cloud computing and the Internet of Things (IoT). It covers several topics:
1) The evolution and current state of cloud computing including public, private, hybrid, and community cloud models.
2) Technical pillars of IoT including RFID, wireless sensor networks, machine-to-machine communication, and SCADA systems.
3) The relationship between cloud computing and IoT, and how they will converge with mobile cloud computing.
4) Emerging paradigms like MAI and XaaS for connecting IoT devices within and outside organizations via the cloud.
Why cloud computing:
Cloud computing can be a cheaper, faster, and greener alternative to an On-premises solution. Without any infrastructure
investments, you can get Powerful software and massive computing resources quickly—with lower Up-front costs and fewer
management headaches down the road. Cloud-based solutions when evaluating options for new IT deployments Whenever a
secure, reliable, cost-effective cloud option exists. Shifting your agency into the cloud can be a big decision, with many
Considerations. This guide is the first in a series designed to help you Get started. The most important is the right choice
software as a service as a service, infrastructure as a service, and platform as a service or hybrid cloud. While addressing
administration goals of scalable, interactive citizen Portals. The cloud can also help your agency increase collaboration across
Organizations, deliver volumes of data to citizens in useful ways, and reduce IT costs while helping your agency focus on
mission-critical tasks. Plus, the Cloud can help you maintain operational efficiency during times of crisis.
http://docplayer.net/search/?q=assem+abdel+hamed+mousa
http://www.ipoareview.org/wp-content/uploads/2016/05/Statement-by-Dr.Assem-Abdel-Hamied-Mousa-President-of-the-Association-of-Scientists-Developers-and-FacultiesASDF.pdf
This document provides an overview of Microsoft's StreamInsight Complex Event Processing (CEP) platform. It discusses CEP concepts and benefits, the StreamInsight architecture and development environment, and deployment scenarios. The presentation aims to introduce IT professionals to CEP and Microsoft's StreamInsight solution for building event-driven applications that process streaming data with low latency.
Big Data is growing rapidly in terms of volume, variety, and velocity. The cloud is well-suited to handle Big Data challenges by providing elastic and scalable infrastructure, which optimizes resources and reduces costs compared to traditional IT. In the cloud, users can collect, store, analyze and share large amounts of data without upfront investment, and scale easily as needs change. Real-world examples show how companies in industries like banking, retail, and advertising are using the cloud's Big Data services to gain insights from large datasets.
This document discusses how the cloud is well suited to address the challenges of big data. It notes that big data sets are getting larger and more complex, requiring new tools and approaches. The cloud optimizes precious IT resources by enabling elastic scaling, global accessibility, easy experimentation, and reducing costs. The cloud empowers users to balance costs and time. Several real-world examples are provided, such as banks using the cloud to perform Monte Carlo simulations and retailers using it for targeted recommendations and click stream analysis.
Big data and cloud computing are closely intertwined. The cloud is well-suited to handle big data challenges by providing massive scalability, flexible pay-as-you-go pricing, and removing the undifferentiated heavy lifting of managing infrastructure. This allows companies to focus on analyzing large and complex datasets. Examples show how companies use Amazon Web Services to collect petabytes of data from sources like sensors and social media, process it using services like EMR, and gain insights for applications in various industries.
The document discusses how cloud computing has changed the game by allowing for innovation, scale, cost savings, and global reach. It outlines four key areas of change enabled by cloud computing: innovation through rapid experimentation, global scale through multiple regions and edge locations, cost optimization by paying for only what is used, and the ability to go global easily. Examples are given of companies innovating faster and scaling globally using AWS cloud services like EC2, S3, DynamoDB, and others.
Big Data Analytics on AWS - Carlos Conde - AWS Summit ParisAmazon Web Services
This document discusses using AWS for big data analytics. It notes that as data volumes grow, collecting, storing, analyzing and sharing data is essential. AWS provides services like S3, DynamoDB and EMR on Hadoop to help with collecting, storing, analyzing and sharing large volumes of data cost effectively. It also discusses using tools like Pig and parallelizing workloads to analyze data more efficiently.
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.
The Move to the Cloud for Regulated Industriesdirkbeth
The document discusses the move to cloud computing for regulated industries like pharmaceutical, biotech, and medical device companies. It notes that while 95% of people claim they don't use the cloud, they actually do for online banking, shopping, social media, and storing photos and music. The cloud provides benefits like high reliability, unlimited storage, easy sharing, and supporting enterprise software. However, regulated industries have additional requirements for cloud applications around authentication, encryption, compliance, auditing, and platform qualifications. Examples of potential cloud uses in pharma include drug discovery, clinical data collection, gene sequencing, and collaboration with partners. The future includes benefits like global accessibility, availability, and collaborative environments.
Esri applications running on Amazon Web Services provide organizations with several key benefits:
1) They allow organizations to deploy GIS applications and environments quickly without large upfront costs or complex IT infrastructure.
2) Running on AWS lowers operating costs by paying only for resources used and easily scaling up or down to match demand.
3) AWS enables organizations to process geospatial data and run GIS jobs faster by leveraging AWS's unlimited computing power.
The enterprise software stack is undergoing once in a generation refresh largely driven by virtualization, data explosion, infrastructure commoditization, socialization, unlimited connectivity, and online services. With ever growing security parameter and attack vectors, enterprises are looking for ways to secure information access without compromising the business agility unleashed by the abovementioned forces. This presentation focuses on the emerging opportunities in the enterprise space that entrepreneurs can leverage to build the technology giants of tomorrow.
This document discusses big data and how new data models are disrupting traditional approaches. It notes that while the new models are initially difficult to understand and threaten existing investments, they are capable of processing large volumes of data quickly. The document examines concepts like Hadoop, NoSQL, and how relational and non-relational approaches can work together in a hybrid environment. It concludes that trends point to more unified support of different data types and expanded capabilities in systems like real-time analytics and embedded search.
Big Data, Big Content, and Aligning Your Storage StrategyHitachi Vantara
Fred Oh's presentation for SNW Spring, Monday 4/2/12, 1:00–1:45PM
Unstructured data growth is in an explosive state, and has no signs of slowing down. Costs continue to rise along with new regulations mandating longer data retention. Moreover, disparate silos, multivendor storage assets and less than optimal use of existing assets have all contributed to ‘accidental architectures.’ And while they can be key drivers for organizations to explore incremental, innovative solutions to their data challenges, they may provide only short-term gain. Join us for this session as we outline the business benefits of a truly unified, integrated platform to manage all block, file and object data that allows enterprises can make the most out of their storage resources. We explore the benefits of an integrated approach to multiprotocol file sharing, intelligent file tiering, federated search and active archiving; how to simplify and reduce the need for backup without the risk of losing availability; and the economic benefits of an integrated architecture approach that leads to lowering TCSO by 35% or more.
Les "systèmes intelligents" constituent la nouvelle génération de systèmes embarqués, qui, en s'appuyant sur les caractéristiques de robustesse et de déterminisme de leurs aînés, se connectent au cloud afin d'enrichir l'expérience utilisateur, qu'il s'agisse d'entreprises (collectant des données ou surveillant des systèmes par exemple), de particuliers (à la maison ou dans un contexte médical, ou bien dans la voiture) ou bien d'autres machines (dans le cas de systèmes automatisés à grande échelle). Le cloud et particulièrement Windows Azure fourni les vecteurs de communication et les moyens de stocker massivement des données et de les traiter, déchargeant ainsi les installations locales et donc rendant le déploiement de ses systèmes plus simple. Cette session, riche en exemples concrets, présentera la stratégie qui est celle de Microsoft autour du futur des systèmes embarqués, et leur connexion au cloud, ainsi que les technologies et les partenariats mis en oeuvre pour accélérer ces déploiements de systèmes intelligents. avec un exemple qui parlera à tous: le futur de la voiture, avec Windows Embedded Automotive!
Big data analytics solutions are available on AWS. AWS provides services like Amazon S3 for storage, DynamoDB for NoSQL databases, EMR for Hadoop clusters, and GPU instances for parallel processing. The right tools should be chosen for each use case - relational databases for interactive reporting, Hadoop for large-scale analytics on structured and unstructured data. AWS services allow collecting, storing, analyzing and sharing big data cost effectively.
The document summarizes a presentation given by Ed Franklin of RiverMeadow Software on cloud computing trends, business drivers, and career opportunities. Some key points include:
- Cloud computing delivers computing resources as a utility over the internet.
- It allows for pay-as-you-go access to shared hardware, software, and data.
- Major trends driving cloud adoption include the growth of internet usage, demands for efficiency and sustainability, and business models requiring flexible computing resources.
- Jobs in areas like cloud services, big data analytics, and mobile applications are expected to grow significantly in the coming years.
ODCA Forecast 2012 Keynote: Curt Aubley, President, Open Data Center Alliance; VP/CTO NexGen Cyber Innovation & Technology; Lockheed Martin Information Systems & Global Services
Big data is enabling personalized experiences through multi-screen delivery and analytics of structured and unstructured data. Media companies are trying to extract value from big data to personalize content and ads. AT&T is using its TV, mobile, and other subscriber data anonymously across devices to improve ad targeting. Companies like Yahoo are using big data analytics to optimize online ad placement across billions of impressions and ads.
BDT101 Big Data with Amazon Elastic MapReduce - AWS re: Invent 2012Amazon Web Services
Big data technologies let you work with any velocity, volume, or variety of data in a highly productive environment. This session seeks to answer questions such as "what is big data," "how can I use unstructured data," and "how can I integrate data collections from different sources" using Hadoop with Amazon Elastic MapReduce. Join general manager of EMR, Peter Sirota, on a journey through real-world use cases of data-driven discovery.
The document discusses how the cloud can serve as a platform for better health through collaboration on data, clinical research, and data protection. Some key points:
1) The cloud allows for data collaboration through storage and transfer services, identity and access management, and encryption features.
2) It enables clinical research through services that power applications for patient-specific education, clinical knowledge systems, and personalized medicine.
3) The cloud provides data protection and disaster recovery using continuous online backup, multiple regions and availability zones, and dedicated instances for compliant workloads.
4) It can extend existing corporate datacenters and applications through services like Direct Connect.
The presentation is a introduction to Big Data and analytics, how to go about enabling big data and analytics in our company, what are the main differences between big data analytics vs. traditional analytics and how to get started.
This material was used at the SAS Big Data Analytics event held in Helsinki on 19th of April 2011.
The slides are copyright of Accenture.
O documento descreve a 1a Conferência Internacional sobre o Sistema de Escrituração Digital (CISPED) realizada no Brasil em 21 de novembro de 2013. O evento reuniu especialistas para discutir o sistema eSocial, que unificará o envio de informações trabalhistas e previdenciárias pelos empregadores. O eSocial simplificará as obrigações das empresas e melhorará a qualidade dos dados fornecidos ao governo.
O documento descreve a 1a Conferência Internacional sobre o Sistema de Escrituração Digital (CISPED) realizada no Brasil em 21 de novembro de 2013. O evento reuniu especialistas para discutir o sistema eSocial, que unificará o envio de informações trabalhistas e previdenciárias pelos empregadores. O eSocial simplificará as obrigações das empresas e melhorará a qualidade dos dados fornecidos ao governo.
O documento descreve um debate sobre o Sistema Público de Escrituração Digital (SPED) Brasil que irá ocorrer em 21 de Novembro em Brasília. O debate irá discutir vários tópicos relacionados à implementação do SPED nas empresas incluindo processos de cadastro de funcionários, qualificação cadastral, folha de pagamento, rescisões de contratos e atualizações de informações.
O documento apresenta as novidades e evoluções do sistema da Nota Fiscal Eletrônica no Brasil, incluindo: (1) a ampliação do conceito de auditoria em tempo real; (2) a implementação do conceito de "nuvem fiscal" para integrar documentos fiscais e atores; (3) o lançamento da Sefaz Virtual de Contingência para permitir a emissão da NF-e em ambientes alternativos quando o sistema estadual estiver indisponível.
6 rfb peso da burocracia tributária - a busca pela simplificação - resumidaLuiz Gustavo Santos
O documento discute as iniciativas da Receita Federal para simplificar a burocracia tributária no Brasil, como a implementação do SPED que integra vários sistemas de escrituração digital, a eliminação de declarações acessórias e a facilitação do relacionamento com o contribuinte por meio da tecnologia.
O documento apresenta as novidades do projeto da Nota Fiscal Eletrônica (NF-e), incluindo: (1) a implementação de um sistema de contingência para autorização da NF-e (SVC); (2) a disponibilização de dois ambientes de contingência (Sefaz Virtual do Ambiente Nacional e Sefaz Virtual do Rio Grande do Sul); (3) a possibilidade de emissão da NF-e em contingência sem alterar a série e numeração.
O documento discute conceitos e procedimentos relacionados à contratação de serviços, obras de construção civil e retenção de INSS. Apresenta a definição de obra de construção civil e empresa construtora, explica a diferença entre obra e serviço, e detalha como calcular a base de retenção do INSS em notas fiscais de serviços. Também aborda o registro S-1310, o CNAE de construção civil, o RAT e os passos para resolver problemas complexos de forma colaborativa.
O documento descreve a implementação do eSocial, um novo sistema para a gestão de informações trabalhistas e tributárias que simplificará as relações entre empregadores, empregados e governo. O eSocial substituirá vários sistemas atuais e permitirá o envio e processamento eletrônico de dados como folha de pagamento, recolhimento de tributos e contribuições. O cronograma prevê a implantação gradual do sistema até 2015.
02 José Alberto Maia – Coordenador do Projeto eSOCIAL – MTELuiz Gustavo Santos
O documento descreve o eSocial, um novo sistema para registro eletrônico de eventos trabalhistas que visa simplificar as obrigações dos empregadores e garantir os direitos dos trabalhadores de forma unificada entre o governo e empregadores. O eSocial substituirá vários documentos atuais por um único registro digital de eventos como admissão, folha de pagamento e desligamento.
01 Jorge Campos – Diretor Executivo e Coordenador do SPED BRASILLuiz Gustavo Santos
O documento descreve um evento sobre o Sistema Público de Escrituração Digital (SPED) que ocorrerá em Brasília no dia 21 de Novembro. O SPED é uma rede online com mais de 40.000 usuários que buscam informações sobre o sistema. O evento irá discutir o desenvolvimento do projeto SPED e as melhores práticas para sua implementação.
O documento descreve a agenda de um evento realizado em 21 de novembro em Brasília sobre o sistema eSocial. A agenda inclui palestras sobre o eSocial, NF-e, fiscalização no ambiente SPED e casos práticos, com palestrantes de órgãos governamentais e do setor privado.
O documento descreve um debate sobre o Sistema Público de Escrituração Digital (SPED) Brasil que irá ocorrer em 21 de Novembro em Brasília. O debate irá discutir vários tópicos relacionados à implementação do SPED nas empresas incluindo processos de cadastro de funcionários, qualificação cadastral, folha de pagamento, rescisões de contratos e atualizações de informações.
O documento apresenta as novidades e evoluções do sistema da Nota Fiscal Eletrônica no Brasil, incluindo: (1) a ampliação do processo de auditoria em tempo real; (2) a implementação do conceito de "nuvem fiscal" para integrar documentos fiscais e atores; (3) a criação de uma Sefa Virtual de Contingência para permitir a emissão da NF-e em caso de problemas nos sistemas estaduais.
6 rfb peso da burocracia tributária - a busca pela simplificação - resumidaLuiz Gustavo Santos
O documento discute as iniciativas da Receita Federal para simplificar a burocracia tributária no Brasil, como a implementação do SPED que integra vários sistemas de escrituração digital, a eliminação de declarações acessórias e a facilitação do relacionamento com o contribuinte por meio da tecnologia.
O documento apresenta as novidades e evoluções do sistema da Nota Fiscal Eletrônica no Brasil, incluindo: (1) a ampliação do processo de auditoria em tempo real entre estados; (2) a implementação do conceito de "nuvem fiscal" para integrar documentos fiscais e atores; (3) a criação de uma Sefa Virtual de Contingência para permitir a emissão da NF-e quando os sistemas estaduais estiverem indisponíveis.
O documento discute conceitos e procedimentos relacionados à contratação de serviços, obras de construção civil e retenção de INSS sobre nota fiscal de serviço. Apresenta a definição de obra de construção civil e empresa construtora. Explica a diferença entre obra e serviço e quando há retenção de INSS. Demonstra exemplos de apuração da base de cálculo da retenção. Aborda também RAT, registro S-1310 e CNAE de obras e serviços de construção civil.
O documento descreve um evento sobre o Sistema Público de Escrituração Digital (SPED) que ocorrerá em Brasília no dia 21 de Novembro. O SPED é uma rede online com mais de 40.000 usuários que buscam informações sobre o sistema. O evento irá discutir o desenvolvimento do projeto SPED e as melhores práticas para sua implementação.
O documento descreve a agenda de um evento realizado em 21 de novembro em Brasília sobre o sistema eSocial. A agenda inclui palestras sobre o eSocial, NF-e, fiscalização no ambiente SPED e casos práticos, com palestrantes de órgãos governamentais e do setor privado.
A INFOLIVE é uma empresa de produção e transmissão de conteúdo para internet com 15 anos de experiência. Ela oferece serviços de broadcast e streaming, webTV e TV corporativa, e filmes e vídeos institucionais. A INFOLIVE tem um portfólio de projetos realizados para clientes em diversos setores.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
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Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
10. Traditional analytics required a
fixed data model,
based on pre-known questions
Big Data promotes data exploration and
experimentation which leads to innovation
12. Lower costs,
faster throughput
Collection & Computation Collaboration
Generation
storage & analytics & sharing
Increased pressure on traditional IT and too
13. Require tools designed for data
collection and computation at
any volume, velocity or format.
14. Software
• Designed for distribution
• Easy programming models
• Flexible language choice
• Platform for abstraction and ecosystem
• Good example: Hadoop
15. Infrastructure
• Designed for distribution
• Easy programming models
• Flexible language choice
• Platform for abstraction and ecosystem
• Good example: cloud computing
23. “Over the next decade, the number of files or containers that
encapsulate the information in the digital universe will grow by
75x.
While the pool of IT staff available to manage them will grow
only slightly. At 1.5x”
- 2011 IDC Digital Universe Study
25. Cloud computing
30% 70%
The Old Managing All of the
IT World Using Big Data
“Undifferentiated Heavy Lifting”
26. Cloud computing
30% 70%
The Old Managing All of the
IT World Using Big Data
“Undifferentiated Heavy Lifting”
Cloud-Based Configuring
Infrastructure Analyzing and Using Big Data
Cloud Assets
70% 30%
41. Simple Storage Service
1 Trillion
1000.000
750.000
500.000
250.000
0.000
750k+ peak transactions per second
42. Global Accessibility
Region
US-WEST (N. California) EU-WEST (Ireland)
GOV CLOUD ASIA PAC (Tokyo)
US-EAST (Virginia)
US-WEST (Oregon)
ASIA PAC
(Singapore)
SOUTH AMERICA (Sao Paulo)
45. Big Data Verticals
Social
Media/Advertisi Financial
Oil & Gas Retail Life Sciences Security Network/Gamin
ng Services
g
User
Anti-virus
Targeted Monte Carlo Demographics
Recommend
Advertising Simulations
Seismic Genome Fraud
Usage analysis
Analysis Analysis Detection
Image and
Transactions
Video Risk Analysis
Analysis Image In-game
Processing
Recognition metrics
47. Bank – Monte Carlo Simulations
“The AWS platform was a good fit for its
unlimited and flexible computational power to
23 Hours to our risk-simulation process requirements.
With AWS, we now have the power to decide
20 Minutes how fast we want to obtain simulation
results, and, more importantly, we have the
ability to run simulations not possible before
due to the large amount of infrastructure
required.” – Castillo, Director, Bankinter
According to IDC, 95% of the 1.2 zettabytes of data in the digital universe is unstructured; and 70% of of this is user-generated content. Unstructured data is also projected for explosive growth, with estimates of compound annual growth (CAGR) at 62% from 2008 - 2012.ChallengesUnconstrained growth
The more misspelled words you collect, the better is your spellcheck application
Computers typically generate data as byproduct of interacting with people or other with other device. The more interactions, typically there is more data. This data comes in a variety of formats from semi-structured logs to in unstructured binaries. This data can be extremely valuable. It can be used to understand and track application or service behavior so that we can find errors or suboptimal user experience. We can mind it for patterns and correlations to generate recommendations.For example ecommerce sites can analyze user access logs to provide product recommendations, social networking sites provide new friends recommendations, dating sites find qualified soul mates, and so fourth.
Big data is important.
Now the Philosophy around data has changed. The philosophy is collect as much data as possible before you know what questions you are going to ask and most importantly you don't know which algorithms you are going to ask because you don't know what type of questions I might need in future. The ultimate mantra of collect and measure everything. How you are going to refine those algorithms, how much data, how much processing power, you really don't know how much resources you really need. Big data is what clouds are for. Its Big data analysis and cloud computing is the perfect marriage.Free of constraintsCollect and Store without limitsCompute and Analyze without limitsVisualize without limites
These resources are even more precious because of the rarity of skills.
Our goal, and what our customers tell us they see, is that this ratio is inverted after moving to AWS. When you move your infrastructure to the cloud, this changes things drastically. Only 30% of your time should be spent architecting for the cloud and configuring your assets. This gives you 70% of your time to focus on your business. Project teams are free to add value to the business and it's customers, to innovate more quickly, and to deliver products to market quickly as well.
Our goal, and what our customers tell us they see, is that this ratio is inverted after moving to AWS. When you move your infrastructure to the cloud, this changes things drastically. Only 30% of your time should be spent architecting for the cloud and configuring your assets. This gives you 70% of your time to focus on your business. Project teams are free to add value to the business and it's customers, to innovate more quickly, and to deliver products to market quickly as well.
There are many patterns of usage that make capacity planning a complex science. From on and off usage patterns, where capacity is only needed at fixed times and not at others, fast growth where an online service becomes so successful that step changes in traditional capacity need to be added, variable peaks - where you just don't know what demand will be when and best guess applies, to predictable peaks such as during commute times as customers use mobile devices to access your service.
Each of these examples is typified by wasted IT resources. Where you planned correctly, the IT resources will be over provisioned so that services are not impacted and customers lost during high demand. In the worst cases, that capacity will not be enough, and customer dissatisfaction will result. Most businesses have a mix differing patterns at play, and much time and resource is dedicated to planning and management to ensure services are always available. And when a new online service is really successful, you often can't ship in new capacity fast enough. Some say that's a nice problem to have, but those that have lived through it will tell you otherwise!
Elasticity with AWS enables your provisioned capacity to follow demand. To scale up when needed and down when not. And as you only pay for what is used, the savings can be significant.
You control how and when your service scales, so you can closely match increasing load in small increments, scale up fast when needed, and cool off and reduce the resources being used at any time of day. Even the most variable and complex demand patterns can be matched with the right amount of capacity - all automatically handled by AWS.
Vertical scaling on commodity hardware. Perfect for Hadoop.
New model is collect as much data as possible – “Data-First Philosophy”Allows us to collect data and ask questions laterAsk many different kinds of questions
And scale is something AWS is used to dealing with. The Amazon Simple Storage Service, S3, recently passed 1 trillion objects in storage, with a peak transaction rate of 750 thousand per second. That's a lot of objects, all stored with 11 9's of durability.
And just like an electricity grid, where you would not wire every factory to the same power station, the AWS infrastructure is global, with multiple regions around the globe from which services are available. This means you have control over things like where you applications run, where you data is stored, and where best to serve your customers from.
Global reach (North Pole, Space)Native app every smartphoneSMSwebmobile-web10M+ users, 15M+ venues, ~1B check-insTerabytes of log data
Bank at least 400,000 simulations to get realistic results.23 hours to 20 minutes and dramatically reduced processing, with the ability to reduce even further when required.Bankinter uses Amazon Web Services (AWS) as an integral part of their credit-risk simulation application, developing complex algorithms to simulate diverse scenarios in order to evaluate the financial health of their clients. “This requires high computational power,” says Bankinter Director of New Technologies Pedro Castillo. “We need to execute at least 400,000 simulations to get realistic results.”
One result of such experimentation is Taste Test which is a recommendations product that helps Etsy figure out your tastes and to offer you relevant products. It works like this, you see 6 images at a time and you pick an image you like the most. You iterate through these sets of images a few times (you can also skip a set if you don’t like any images) and after a few iterations, Etsy displays the products that are most relevant to you. I encourage you to try – it’s a lot of fun.Today, Etsy uses Amazon Elastic MapReduce for web log analysis and recommendation algorithms. Because AWS easily and economically processes enormous amounts of data, it’s ideal for the type of processing that Etsy performs. Etsy copies its HTTP server logs every hour to Amazon S3, and syncs snapshots of the production database on a nightly basis. The combination of Amazon’s products and Etsy’s syncing/storage operation provides substantial benefits for Etsy. As Dr. Jason Davis, lead scientist at Etsy, explains, “the computing power available with [Amazon Elastic MapReduce] allows us to run these operations over dozens or even hundreds of machines without the need for owning the hardware.”Dr. Davis goes on to say, “Amazon Elastic MapReduce enables us to focus on developing our Hadoop-based analysis stack without worrying about the underlying infrastructure. As our cycles shift between development and research, our software and analysis requirements change and expand constantly, and [Amazon Elastic MapReduce] effectively eliminates half of our scaling issues, allowing us to focus on what is most important.”Etsy has realized improved results and performance by architecting their application for the cloud, with robustness and fault tolerance in mind, while providing a market for users to buy and sell handmade items online.
Another example of such innovation is gift ideas. A lot of us struggle to pic the right present for our friends and so Etsy has a product that makes it easier. Etsy looks at your facebook social graph and learns about your interests and those of your friends. It uses this information to give you ideas for presents. For example, if your friend is an REM fan, Etsy may suggest a t-shirt with REM print on it.These innovative data products are just a few examples of innovation that is possible if we lower the cost barriers for data experimentation.
Yelp is also doing product recommendations based on location, people reviews, or people searches. For example, “people who viewed this, viewed that” feature can help customers discover other relevant options in the area. People can discover interesting facts about places with “People viewed this after searching for that” feature. In this example, the westin hotel probably has glass elevators and is likely offers the best location to stay in san francisco at least by some definition of best.There is also “review highlights” feature. Yelp analyses written reviews and provides highlights about the places, so that their customers don’t have to read through all the reviews to get basic ideas about the place. All these differentiating features were possible because of Hadoop and flexible infrastructure for data processing.
500% increase in returns for advertising.Pedabytes of storage.There is a lot of data the retail business has about the users, it’s just never used it in advertising.For example, the retail knows that the customer has purchased a sports movie and is currently searching for video games, so it may make sense to advertise a sports video game for the customer.Efficient: Elastic infrastructure from AWS allows capacity to be provisioned as needed based on load, reducing cost and the risk of processing delays. Amazon Elastic MapReduce and Cascading lets Razorfish focus on application development without having to worry about time-consuming set-up, management, or tuning of Hadoop clusters or the compute capacity upon which they sit.Ease of integration: Amazon Elastic MapReduce with Cascading allows data processing in the cloud without any changes to the underlying algorithms.Flexible: Hadoop with Cascading is flexible enough to allow “agile” implementation and unit testing of sophisticated algorithms.Adaptable: Cascading simplifies the integration of Hadoop with external ad systems.Scalable: AWS infrastructure helps Razorfish reliably store and process huge (Petabytes) data sets.The AWS elastic infrastructure platform allows Razorfish to manage wide variability in load by provisioning and removing capacity as needed. Mark Taylor, Program Director at Razorfish, said, “With our implementation of Amazon Elastic MapReduce and Cascading, there was no upfront investment in hardware, no hardware procurement delay, and no additional operations staff was hired. We completed development and testing of our first client project in six weeks. Our process is completely automated. Total cost of the infrastructure averages around $13,000 per month. Because of the richness of the algorithm and the flexibility of the platform to support it at scale, our first client campaign experienced a 500% increase in their return on ad spend from a similar campaign a year before.”