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data model

Results 151 - 175 of 380Sort Results By: Published Date | Title | Company Name
Published By: SAS     Published Date: Mar 06, 2018
The 2016 ACFE Report to the Nations on Occupational Fraud and Abuse analyzed 2,410 occupational fraud cases that caused a total loss of more than $6.3 billion.8 Victim organizations that lacked anti-fraud controls suffered double the amount of median losses. SAS’ unique, hybrid approach to insider threat deterrence – which combines traditional detection methods and investigative methodologies with behavioral analysis – enables complete, continuous monitoring. As a result, government agencies and companies can take pre-emptive action before damaging incidents occur. Equally important, SAS solutions are powerful yet simple to use, reducing the need to hire a cadre of high-end data modelers and analytics specialists. Automation of data integration and analytics processing makes it easy to deploy into daily operations.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
The most recent decade has seen rapid advances in connectivity, mobility, analytics, scalability, and data, spawning what has been called the fourth industrial revolution, or Industry 4.0. This fourth industrial revolution has digitalized operations and resulted in transformations in manufacturing efficiency, supply chain performance, product innovation, and in some cases enabled entirely new business models. This transformation should be top of mind for quality leaders, as quality improvement and monitoring are among the top use cases for Industry 4.0. Quality 4.0 is closely aligning quality management with Industry 4.0 to enable enterprise efficiencies, performance, innovation and business models. However, much of the market isn’t focusing on Quality 4.0, since many quality teams are still trying to solve yesterday’s problems: inefficiency caused by fragmented systems, manual metrics calculations, quality teams independently performing quality work with minimal cross-functional own
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SAS
Published By: NetApp     Published Date: Mar 05, 2018
Did you know that by 2020, 50% of analytic queries will be generated using search, natural-language processing or voice, or will be automatically generated? Read the Gartner report Technology Insight for Modern Analytics and Business Intelligence Platforms and find out how to meet the time-to-insight demands of today's competitive business environment. Learn how to: • Determine when to use existing, traditional BI technologies versus modern analytics and BI • Broaden data access beyond relational systems • Adopt new approaches to data modeling
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netapp, database performance, flash storage, data management, cost challenges
    
NetApp
Published By: NetApp     Published Date: Mar 05, 2018
By 2018, more than 70% of new DBMS deployments will leverage cloud for at least one use case. Read the Gartner report State of the Operational DBMS Market, 2017 and get the latest insights and recommendations on DBMS strategy. Discover how to: •Evaluate modern data management capabilities before adopting new DBMS products •Lead a nonrelational technology assessment to determine which DBMS best meets your business requirements • Deploy a multimodel DBMS and reduce complexity in your data center
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netapp, database performance, flash storage, data management, cost challenges
    
NetApp
Published By: NetApp     Published Date: Mar 05, 2018
Access to comprehensive, up-to-date information about your infrastructure is critical to meeting the challenges of a service-led IT organization. You need visibility into your entire IT infrastructure, including both multi-vendor and multi-cloud environments, so you can make data-driven decisions and improve IT services. Discover how you can manage, monitor, and report on IT services across your entire data infrastructure so you can drive intelligent business decisions and reduce costs.
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netapp, database performance, flash storage, data management, cost challenges
    
NetApp
Published By: FICO     Published Date: Mar 02, 2018
The role of analytics in managing, improving and ultimately transforming supply chains cannot be understated. But what about the analytics themselves? FICO’s Zahir Balaporia and renowned author Tom Davenport use the term “The Analytics Supply Chain” to reflect that the actual analytics themselves parallel supply chains, with inherent challenges and problems if things “get stuck.” Rethinking analytics in these terms can not only improve supply chain performance, but also any other business problems you seek to solve. This article targets: · Steps in the analytics supply chain and the vital role of data and analytic models · How your predictions, recommendations and insights need to rely on similar attributes to finished manufactured products; · Key questions to ask yourself in determining where you need to fix your analytics supply chain.
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supply, chain, analytics, employee, optimization, organisations, productivity
    
FICO
Published By: Oracle     Published Date: Mar 01, 2018
Per avere successo nella realtà competitiva di oggi, le aziende devono svincolarsi dai limiti imposti dall’infrastruttura IT legacy. L’acquisto di hardware e la manutenzione di enormi data center per l’esecuzione dei sistemi informatici appartengono al passato: la gestione e la manutenzione dell’infrastruttura sono semplicemente troppo costose. Un recente sondaggio di Gartner ha rivelato che oltre l’80% dei CIO ritiene che l’Infrastructure-as-a-Service (IaaS) sia un’opzione perseguibile e il 10% degli stessi già la considera la scelta predefinita per l’infrastruttura. L’utilizzo di un’infrastruttura con un modello di servizio elastico e con pagamento in base al consumo non solo riduce i costi e le preoccupazioni, ma consente inoltre alle organizzazioni IT di dedicarsi all’innovazione per favorire la crescita aziendale.
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ampio, accesso, risorse, misurabile, pubblico, privato, ibrido
    
Oracle
Published By: Oracle     Published Date: Feb 28, 2018
Per avere successo nella realtà competitiva di oggi, le aziende devono svincolarsi dai limiti imposti dall’infrastruttura IT legacy. L’acquisto di hardware e la manutenzione di enormi data center per l’esecuzione dei sistemi informatici appartengono al passato: la gestione e la manutenzione dell’infrastruttura sono semplicemente troppo costose. Un recente sondaggio di Gartner ha rivelato che oltre l’80% dei CIO ritiene che l’Infrastructure-as-a-Service (IaaS) sia un’opzione perseguibile e il 10% degli stessi già la considera la scelta predefinita per l’infrastruttura. L’utilizzo di un’infrastruttura con un modello di servizio elastico e con pagamento in base al consumo non solo riduce i costi e le preoccupazioni, ma consente inoltre alle organizzazioni IT di dedicarsi all’innovazione per favorire la crescita aziendale.
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ampio, accesso, risorse, misurabile, pubblico, privato, ibrido
    
Oracle
Published By: MobileIron     Published Date: Feb 26, 2018
Enterprises are increasingly expected to support Macs as corporateapproved devices. In order to be in compliance, it is imperative that all devices accessing sensitive corporate and customer data be fully secured and managed. MobileIron delivers a new model for authentication and identity to Macs and enables enterprises to unify Apple mobile and desktop operations using a common security and management platform. MobileIron’s layered security can be extended to not only corporate-owned Macs, but to employee-owned devices as well. And, IT organizations can bring Macs under management across the organization with unparalleled speed and at scale thanks to seamless integration with Apple’s Device Enrollment Program (DEP) and Volume Purchase Program (VPP).
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MobileIron
Published By: Cisco and NVIDIA Corporation     Published Date: Feb 26, 2018
These are interesting and challenging times to be in business. Digital forces, such as the cloud, big data, mobility, and mobile apps are disrupting tried-and-true business models, as well as entire industries. These transformational advances are producing complexity, while workers are demanding simplicity. They require centralized infrastructures to keep information safe, even as agility and flexibility rule the day. Read this eBook to learn more about powerful forces of digital business transformation!
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Cisco and NVIDIA Corporation
Published By: Oracle     Published Date: Feb 16, 2018
To succeed in today’s competitive reality, businesses need to free themselves from the limitations of legacy IT infrastructure. The days of purchasing hardware and maintaining massive data centers to run IT must come to an end. Managing and maintaining your infrastructure is simply too expensive. A recent Gartner survey found that more than 80 percent of CIOs consider Infrastructure as a Service (IaaS) to be a viable option and 10 percent of CIOs already consider it to be their default choice for infrastructure. Utilizing an infrastructure with an elastic, pay-as-you-go service model not only reduces costs and worries, but also frees IT organizations to innovate in ways that will enhance business growth.
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iaas, business, legacy, infrastructure, oracle, organisations
    
Oracle
Published By: Oracle     Published Date: Feb 15, 2018
To succeed in today’s competitive reality, businesses need to free themselves from the limitations of legacy IT infrastructure. The days of purchasing hardware and maintaining massive data centers to run IT must come to an end. Managing and maintaining your infrastructure is simply too expensive. A recent Gartner survey found that more than 80 percent of CIOs consider Infrastructure as a Service (IaaS) to be a viable option and 10 percent of CIOs already consider it to be their default choice for infrastructure. Utilizing an infrastructure with an elastic, pay-as-you-go service model not only reduces costs and worries, but also frees IT organizations to innovate in ways that will enhance business growth.
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iaas, business, legacy, infrastructure, oracle, organisations
    
Oracle
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
MongoDB is an open-source, document database designed with both scalability and developer agility in mind. MongoDB bridges the gap between key-value stores, which are fast and scalable, and relational databases, which have rich functionality. Instead of storing data in rows and columns as one would with a relational database, MongoDB stores JSON documents with dynamic schemas. Customers should consider three primary factors when evaluating databases: technological fit, cost, and topline implications. MongoDB's flexible and scalable data model, robust feature set, and high-performance, high-availability architecture make it suitable for a wide range of database use cases. Given that in many cases relational databases may also be a technological fit, it is helpful to consider the relative costs of each solution when evaluating which database to adopt.
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total, cost, ownership, comparison, mongodb, oracle
    
AstuteIT_ABM_EMEA
Published By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
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, hybrid data warehouse, development model
    
Group M_IBM Q1'18
Published By: Pure Storage     Published Date: Jan 12, 2018
Interest in machine learning has exploded over the past decade. You see machine learning in computer science programs, industry conferences, and the Wall Street Journal almost daily. For all the talk about machine learning, many conflate what it can do with what they wish it could do. Fundamentally, machine learning is using algorithms to extract information from raw data and represent it in some type of model. We use this model to infer things about other data we have not yet modeled. Neural networks are one type of model for machine learning; they have been around
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learning machines, automated intelligence, scalars, vectors, mathematics, classification, pure storage
    
Pure Storage
Published By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: Mintigo     Published Date: Nov 20, 2017
Lead scoring models were put in place to prioritize leads for follow-up, nurture and marketing investment. However, with guesswork and data coming from disparate sources, traditional lead scoring has a host of limitations. In today’s competitive landscape, organizations needs to embrace more advanced and reliable scoring models to succeed. Read this ebook to learn 4 reasons why traditional lead scoring is not adequate, and why scoring with AI is necessary.
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Mintigo
Published By: ADP     Published Date: Nov 16, 2017
Many businesses invest in analytics technology thinking it’s a silver bullet. But data doesn’t always tell the whole story. You get percentages but not insights. Trends but not necessarily relationships or patterns. Truly impactful workforce analytics has to do more. You have to turn data into insight, and then put it into action. This workbook is designed to help you progress through the workforce analytics maturity model. The first step in the process is to identify where you stand today.
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ADP
Published By: MobileIron     Published Date: Nov 16, 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. Download the one pager now to learn more.
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MobileIron
Published By: McAfee EMEA     Published Date: Nov 15, 2017
Private cloud is one of the critical deployment architectures IT teams are adopting as they transition to a service-centric delivery model. More than 75% of organizations? already use private clouds to lower costs, increase agility and exert greater control over security, data protection and compliance. The transition to private cloud represents a paradigm shift in how IT is provisioned and data centers are deployed. Virtualization is expanding beyond servers into storage and networking, while software-defined models allow new levels of agility through advanced automation and orchestration. https://www.eventbrite.com/e/mpower-emea-cybersecurity-summit-2017-tickets-36893006977?aff=kp4
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cloud, security, guide, privacy, architectures, organizations, compliance, protection
    
McAfee EMEA
Published By: McAfee EMEA     Published Date: Nov 15, 2017
Machine learning offers the depth, creative problem-solving capabilities, and automation to help security organizations gain significant ground against attackers. It’s a powerful tool for processing massive amounts of data for the purpose of malware classification and analysis, especially for unknown threats. Through supervised learning, human researchers can continually develop new training models that expand the understanding and competency of machine learning systems.
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analytics, security, problem solving, creative, data, researching, malware
    
McAfee EMEA
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
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