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data model

Results 176 - 200 of 383Sort Results By: Published Date | Title | Company Name
Published By: NetApp     Published Date: Nov 14, 2017
As companies’ transition to become digital enterprises, they must increasingly manage cost and performance across a hybrid IT environment. On-demand consumption strategies can be used to optimize your data storage costs, whether you are running applications in a private data center, across a hybrid cloud, or in the public cloud. Read this eBook and learn how on-demand consumption models can help you align IT spending with your business needs, both on-premises and in the cloud.
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NetApp
Published By: MobileIron     Published Date: Nov 14, 2017
Traditional identity-based security models cannot secure your business data from the latest mobile-cloud threats, including unsecured devices, unmanaged apps, and unsanctioned cloud services. To keep business data secure in the mobile-cloud world, you need a new security model that checks the state and health of devices, apps, and cloud services before letting them get to your data.
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MobileIron
Published By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
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population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
    
IBM Watson Health
Published By: IBM     Published Date: Nov 08, 2017
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
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data warehouse, analytics, ibm, deployment models
    
IBM
Published By: MarkLogic     Published Date: Nov 07, 2017
Business demands a single view of data, and IT strains to cobble together data from multiple data stores to present that view. Multi-model databases, however, can help you integrate data from multiple sources and formats in a simplified way. This eBook explains how organizations use multi-model databases to reduce complexity, save money, lessen risk, and shorten time to value, and includes practical examples. Read this eBook to discover how to: Get unified views across disparate data models and formats within a single database Learn how multi-model databases leverage the inherent structure of data being stored Load as is and harmonize unstructured and semi-structured data Provide agility in data access and delivery through APIs, interfaces, and indexes Learn how to scale a multi-model database, and provide ACID capabilities and security Examine how a multi-model database would fit into your existing architecture
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MarkLogic
Published By: MarkLogic     Published Date: Nov 07, 2017
NoSQL means a release from the constraints imposed on database management systems by the relational database model. This quick, concise eBook provides an overview of NoSQL technology, when you should consider using a NoSQL database over a relational one (and when to use both). In addition, this book introduces Enterprise NoSQL and shows how it differs from other NoSQL systems. You’ll also learn the NoSQL lingo, which customers are already using it and why, and tips to find the right NoSQL database for you.
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MarkLogic
Published By: MarkLogic     Published Date: Nov 07, 2017
This eBook explains how databases that incorporate semantic technology make it possible to solve big data challenges that traditional databases aren’t equipped to solve. Semantics is a way to model data that focuses on relationships, adding contextual meaning around the data so it can be better understood, searched, and shared. Read this eBook, discover the 5 steps to getting smart about semantics, and learn how by using semantics, leading organizations are integrating disparate heterogeneous data faster and easier and building smarter applications with richer analytic capabilities.
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MarkLogic
Published By: IBM     Published Date: Nov 03, 2017
Massive shifts within the digital business landscape are sparking immense opportunities and reshaping every sector. In some cases, complete upheaval is happening at lightning-fast speed. In other instances, digital undercurrents are stirring beneath the surface as organizations scramble to monetize vast volumes and variety of data in an effort to sharpen their competitive edge and not be blindsided by unforeseen events that completely upend existing business models. While long-standing industry leadership might be no match for the next cool app, agility, speed and the ability to harness more data than was ever imagined is fueling powerful possibilities for reinvention among companies of every size. Data is following rapidly from mobile devices and social networks, as well as from every connected product, machine and infrastructure. This data holds the potential for deep insights that can replace guesswork and approximations as to locations, behaviors, patterns and preferences. As the w
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digital business, data, data-driven enterprise, innovation, ibm
    
IBM
Published By: Schneider Electric     Published Date: Oct 31, 2017
In considering the four principal options of data center modernization, keep in mind that each option need not be treated as a separate and distinct approach. Data center stakeholders may want to combine options in order to better accommodate a particular migration timeline. Or cautious executives may want to simply dabble with the outsourcing option by piloting only a few select applications while still maintaining a core corporate data center. The key critical success factor is the recognition that data center modernization is not a one-time fi x, but rather a critical piece of an ongoing strategy to better service customers.
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modernization, data center, investment, cost effectiveness, business sense, outsourced model, resources
    
Schneider Electric
Published By: Dell and VMWare     Published Date: Oct 26, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented.
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Dell and VMWare
Published By: Dell and VMWare     Published Date: Oct 26, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented.
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Dell and VMWare
Published By: Dell and VMWare     Published Date: Oct 26, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented.
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Dell and VMWare
Published By: Dell and Nutanix     Published Date: Oct 26, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented.
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Dell and Nutanix
Published By: Dell and Nutanix     Published Date: Oct 26, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented.
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Dell and Nutanix
Published By: Dell and Nutanix     Published Date: Oct 26, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented.
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Dell and Nutanix
Published By: Dell and Nutanix     Published Date: Oct 26, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented.
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Dell and Nutanix
Published By: DellEMC and Intel®     Published Date: Oct 25, 2017
A related recent development in the data center is converged infrastructure (CI). Instead of the traditional silo deployment approach to storage, compute, and network resources, all infrastructure elements are delivered and managed in a single environment, providing virtualized access to business services in an efficient manner. This is particularly suitable for cloud-based delivery models. However, since CI achieves lower costs through optimization of data center resources, it can be effective for all IT organizations, regardless of the way in which the services are managed or presented. Intel Inside®. Intel otwiera nowe mo?liwo?ci. Ultrabook, Celeron, Celeron Inside, Core Inside, Intel, Intel Logo, Intel Atom, Intel Atom Inside, Intel Core, Intel Inside, Intel Inside Logo, Intel vPro, Itanium, Itanium Inside, Pentium, Pentium Inside, vPro Inside, Xeon, Xeon Phi, and Xeon Inside are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.
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ultrabook, celeron, celeron inside, core inside, intel, intel logo, intel atom, intel atom inside
    
DellEMC and  Intel®
Published By: OneLogin     Published Date: Oct 24, 2017
From the information provided in the interviews, Forrester has constructed a Total Economic Impact (TEI) framework for those organizations considering investing in OneLogin. The objective of the framework is to identify the benefits, costs, flexibility, and risk factors that affect the investment decision. Forrester employed four fundamental elements of TEI in modeling OneLogin: benefits, costs, flexibility options, and risks. Forrester took a multistep approach to evaluate the impact that OneLogin can have on the Organization (see Figure 2). Specifically, we: › Interviewed OneLogin marketing, sales, and product management personnel, along with Forrester analysts, to better understand the value proposition for OneLogin. › Conducted an in-depth interview with the Organization’s senior application engineer and its supervisor of IT security to obtain data with respect to costs, benefits, and risks. › Constructed a financial model representative of the interviews using the TEI metho
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OneLogin
Published By: Secureworks ABM UK 2017     Published Date: Oct 23, 2017
Despite long-standing concerns captured in a myriad of surveys, security in the cloud has progressed to a more practical and achievable level. The cloud represents a shared security responsibility model whereby that responsibility is split between the Cloud Service Provider and the cloud customer. For organisations moving some or all of their applications and data to the cloud, acceptance of this model clears the way to more thoughtful consideration for how security can and should be architected — from the ground up. As a result, IT and IT Security leaders now have a much clearer trajectory to support their business operations in the cloud in a secure manner.
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cyber security, cyber security framework, data security, firewall, general data protection regulation, incident and problem management, information security, intrusion detection
    
Secureworks ABM UK 2017
Published By: Oracle     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Security has become top of mind for CIOs, and CEOs. Encryption at rest is a piece of the solution, but not a big piece. Encryption over the network is another piece, but only a small piece. These and other pieces do not fit together well; they need to unencrypt and reencrypt the data when they move through the layers, leaving clear versions that create complex operational issues to monitor and detect intrusion. Larger-scale high-value applications requiring high security often use Oracle middleware, including Java and Oracle database. Traditional security models give the data to the processors to encrypt and unencrypt, often many times. The overhead is large, and as a result encryption is used sparingly on only a few applications. The risk to enterprises is that they may have created an illusion of security, which in reality is ripe for exploitation. The modern best-practice security model is an end-to-end encryption architecture. The application deploys application-led encryption s
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Oracle
Published By: Oracle CX     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
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Oracle CX
Published By: Oracle CX     Published Date: Oct 20, 2017
Security has become top of mind for CIOs, and CEOs. Encryption at rest is a piece of the solution, but not a big piece. Encryption over the network is another piece, but only a small piece. These and other pieces do not fit together well; they need to unencrypt and reencrypt the data when they move through the layers, leaving clear versions that create complex operational issues to monitor and detect intrusion. Larger-scale high-value applications requiring high security often use Oracle middleware, including Java and Oracle database. Traditional security models give the data to the processors to encrypt and unencrypt, often many times. The overhead is large, and as a result encryption is used sparingly on only a few applications. The risk to enterprises is that they may have created an illusion of security, which in reality is ripe for exploitation. The modern best-practice security model is an end-to-end encryption architecture. The application deploys application-led encryption s
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Oracle CX
Published By: SAS     Published Date: Oct 18, 2017
Want to get even more value from your Hadoop implementation? Hadoop is an open-source software framework for running applications on large clusters of commodity hardware. As a result, it delivers fast processing and the ability to handle virtually limitless concurrent tasks and jobs, making it a remarkably low-cost complement to a traditional enterprise data infrastructure. This white paper presents the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop. These solutions span the entire analytic life cycle – from data management to data exploration, model development and deployment.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Quality 4.0 isn't really a story about technology. It's about how that technology improves culture, collaboration, competency and leadership. The last decade has seen rapid advances in connectivity, mo­bility, analytics, scalability and data, creating what some call the fourth industrial revolution, or Industry 4.0. With the help of the Industrial Internet of Things (IIoT), manufacturers have digitized operations, transforming efficiency, supply-chain performance and in­novation. This revolution has even created entirely new business models. This e-book gives manufacturers the tools to lead the Qual­ity 4.0 transformation – a transformation that raises traditional manufacturing to the next level. It teaches readers to use advanced technology, analytics and IIoT to strengthen the manufacturing process and bring it forward into a powerful digital age.
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SAS
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