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Results 151 - 175 of 349Sort Results By: Published Date | Title | Company Name
By: SAS     Published Date: May 24, 2018
This paper provides an introduction to deep learning, its applications and how SAS supports the creation of deep learning models. It is geared toward a data scientist and includes a step-by-step overview of how to build a deep learning model using deep learning methods developed by SAS. You’ll then be ready to experiment with these methods in SAS Visual Data Mining and Machine Learning. See page 12 for more information on how to access a free software trial. Deep learning is a type of machine learning that trains a computer to perform humanlike tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. Deep learning is used strategically in many industries.
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SAS
By: Epicor     Published Date: Aug 18, 2017
More than ever, businesses are considering a cloud solution for their enterprise resource planning (ERP) deployment over an on-premises system. Cloud technology appeals to these companies because updates and fixes occur automatically with little or no effort from internal IT staff, and because cloud-based solutions provide access to real-time data from anywhere. Employees want tools that make it easier for them to complete everyday tasks and make informed decisions that help the business grow. Aberdeen’s research report, “Top Performers Know It’s Time to Migrate to Cloud ERP: Here’s Why and How,” uncovers the reasons successful companies are choosing cloud over on-premises ERP models. Download this SmartBite for a quick look at the report’s highlights.
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erp software, enterprise resource planning software, saas, cloud erp, epicor erp
    
Epicor
By: Epicor     Published Date: Aug 15, 2018
More than ever, businesses are considering a cloud solution for their enterprise resource planning (ERP) deployment over an on-premises system. Cloud technology appeals to these companies because updates and fixes occur automatically with little or no effort from internal IT staff, and because cloud-based solutions provide access to real-time data from anywhere. Employees want tools that make it easier for them to complete everyday tasks and make informed decisions that help the business grow. Aberdeen’s research report, “Top Performers Know It’s Time to Migrate to Cloud ERP: Here’s Why and How,” uncovers the reasons successful companies are choosing cloud over on-premises ERP models. Download this report from Aberdeen Group and discover the compelling reasons more companies are choosing the cloud for their ERP platform.
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erp software, enterprise resource planning software, saas, cloud erp, epicor erp
    
Epicor
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
By: MarkLogic     Published Date: Mar 29, 2018
Executives, managers, and users will not trust data unless they understand where it came from. Enterprise metadata is the “data about data” that makes this trust possible. Unfortunately, many healthcare and life sciences organizations struggle to collect and manage metadata with their existing relational and column-family technology tools. MarkLogic’s multi-model architecture makes it easier to manage metadata, and build trust in the quality and lineage of enterprise data. Healthcare and life sciences companies are using MarkLogic’s smart metadata management capabilities to improve search and discovery, simplify regulatory compliance, deliver more accurate and reliable quality reports, and provide better customer service. This paper explains the essence and advantages of the MarkLogic approach.
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enterprise, metadata, management, organizations, technology, tools, mark logic
    
MarkLogic
By: MarkLogic     Published Date: May 07, 2018
Executives, managers, and users will not trust data unless they understand where it came from. Enterprise metadata is the “data about data” that makes this trust possible. Unfortunately, many healthcare and life sciences organizations struggle to collect and manage metadata with their existing relational and column-family technology tools. MarkLogic’s multi-model architecture makes it easier to manage metadata, and build trust in the quality and lineage of enterprise data. Healthcare and life sciences companies are using MarkLogic’s smart metadata management capabilities to improve search and discovery, simplify regulatory compliance, deliver more accurate and reliable quality reports, and provide better customer service. This paper explains the essence and advantages of the MarkLogic approach.
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agile, enterprise, metadata, management, organization
    
MarkLogic
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
By: Google Analytics 360 Suite     Published Date: Jul 27, 2017
Today’s marketing leaders need sophisticated tools to turn data into cross-channel insights that improve performance. In a new report, Gartner compares 11 digital marketing analytics solutions across five key areas: data integration, exploration, advanced models, platform integrations, and measurement. Selecting the best solution for your team requires thoughtful analysis. How will you determine the best fit? Gartner’s Magic Quadrant can help.
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Google Analytics 360 Suite
By: Juniper Networks     Published Date: Aug 08, 2017
Cloud, social, big data, and the Internet of Things (IoT) are increasingly central to business decisions as the pace of digitization accelerates. The impact of software-defined networking (SDN), virtualization, and converged and hyperconverged infrastructure within the datacenter is substantial. These technologies add complexity but offer enticing opportunities for new business models, revenue streams, operating efficiencies, and agility that organizations must pursue if they want to remain competitive and viable. This pursuit requires businesses to keep up with current and emerging technologies and applications and transform the ways in which they conduct business. At the core of "keeping up" is an organization's datacenter strategy — with an associated technology and services strategy that will either create industry laggards or accelerate innovators.
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Juniper Networks
By: Sprinklr     Published Date: Sep 28, 2017
Customer service today is broken, and the data shows it. Tried-and-true customer service models are losing your organization customers and prospects. So what is the solution? It’s called social customer service.
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social customer service, social media customer service, social media, social, customer service, customer care, customer reviews
    
Sprinklr
By: Dassault Systèmes     Published Date: May 09, 2018
Today’s thriving High-Tech sector is driven by shrinking product lifecycles, rapid innovation, distributed engineering/manufacturing—and highly demanding customer expectations. The industry needs to deliver on multiple fronts, including: • Embed customer-centric innovation throughout the lifecycle: Only with customer experience at the core can companies stay ahead. • Tame ideas into executable products: Detecting early trends and using customer feedback is vital. • Manage complexity better: Increasing visibility of all product data helps build and manage digital models to use in every business function from R&D to field service. • Create relevant connected systems: High-Tech innovators use IoT for an ongoing dialogue of customers, devices and manufacturers. • Provide agility to compete on software, hardware and service: Customers want value from every interaction. Download your targeted industry analysis to learn more.
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Dassault Systèmes
By: IBM Watson Health     Published Date: Sep 29, 2017
In the world of value-based healthcare, your data is the key to extracting the most actionable insights that provide real value to your organization. But getting to those insights can prove difficult, especially if you have to connect disparate data sources. You need transparency into key insights that can help your team make more informed decisions for the success of your organization. In this listicle, we explore five ways an analytics solution can help you transform your organization through the power of insight. From risk modeling to predictive analytics, utilizing the right mix of analytics can improve patient outcomes and ultimately move your organization closer to your ideal value-based care model
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value-based care, analytics, insights, data, business intelligence, ehr, fee-for-service, cognitive, predictive, outcomes, infrastructure
    
IBM Watson Health
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
By: Anaplan     Published Date: Apr 02, 2019
Connected organizations collaborate across business functions to dynamically steer business performance. Previous generations of planning software have fallen short of this vision, making collaboration difficult to achieve, scattering data across multiple sources, and providing inflexible planning models that require heavy IT support. This landscape motivated Anaplan to develop an innovative platform that enables Connected Planning across the entire enterprise. The FSN Innovation Showcase highlights three major innovations that support these objectives: • Anaplan’s proprietary Hyperblock® technology • The App Hub, a suite of 250+ industry-leading solutions • Developments in machine learning and artificial intelligence
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Anaplan
By: Anaplan     Published Date: Apr 09, 2019
Connected organizations collaborate across business functions to dynamically steer business performance. Previous generations of planning software have fallen short of this vision, making collaboration difficult to achieve, scattering data across multiple sources, and providing inflexible planning models that require heavy IT support. This landscape motivated Anaplan to develop an innovative platform that enables Connected Planning across the entire enterprise. The FSN Innovation Showcase highlights three major innovations that support these objectives: • Anaplan’s proprietary Hyperblock® technology • The App Hub, a suite of 250+ industry-leading solutions • Developments in machine learning and artificial intelligence
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Anaplan
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
By: BetterUp     Published Date: Dec 05, 2018
"As HR investments become more data-driven, coaching must deliver on its ROI evidence gap. At BetterUp, we’ve created a model that can effectively measure the impact of coaching on the bottom line. Download our paper to learn: - How coaching ROI has been measured in the past, and why these methods are flawed - Which inputs are factored into our ROI algorithm - How we map the ROI of coaching to tangible business results"
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BetterUp
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
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
By: F5 Networks Inc     Published Date: Aug 13, 2013
Organizations are increasingly adopting a hybrid cloud computing strategy to realize the benefits without compromising on security and control. The integration at the network, infrastructure, and process layers that is required by hybrid models can be addressed by three new cloud-focused solution types: bridges, brokers, and gateways. This paper gives you the insight you need to better understand which architectural approach will meet your requirements and expectations.
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cloud, data centers, cloud computing, bridges, brokers, gateways, network, infrastructure, hybrid models, it management, application integration, data integration
    
F5 Networks Inc
By: F5 Networks Inc     Published Date: Aug 13, 2013
Emerging data center models are based on flexibility and non-disruptive, on-demand scalability. Infrastructure must not only support these capabilities, but be able itself to provide these same benefits and capabilities. F5 ScaleN is a breakthrough in high availability and scalability, offering the robust capabilities required to enable multi-tenant solutions, elastic applications, and infrastructure for any environment.
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elastic infrastructure, data center models, flexibility, on-demand scalability, elastic applications, multi-tenant solutions
    
F5 Networks Inc
By: Oracle     Published Date: Apr 03, 2012
This white paper describes how to successfully consolidate your database onto a private cloud through several deployment models.
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orace, service models, cloud management, 11g, database services, database consolidation, database development, data integration, data protection, data quality, data replication, database security
    
Oracle
By: Adobe     Published Date: Mar 03, 2017
When it comes to audience engagement, the landscape has been completely rewritten. Media and entertainment companies need to embrace new technologies to achieve revenue goals. The Adobe guide, Play to Win in Audience Intelligence, shows you how. Read the guide to learn: • How to bring your data sources together into a unified view of the customer • How to move beyond basic demographic attributes to behavior attributes • How to use look-alike modeling to improve customer targeting and acquisition
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audience intelligence, audience engagement, unified data source, behavior attributes, look-alike modeling, data management
    
Adobe
By: CA Technologies     Published Date: Jun 03, 2015
The complexity and high level of integration inherent in SAP environments can make development especially challenging and increase the time required to bring solutions to market. Persistent development and test challenges include unavailable systems, inability to accurately model performance and complex test data requirements. By employing service virtualization to model the core business logic in SAP systems and integrations, teams can free themselves of these constraints, leading to faster build and test cycles, better quality and lower cost.
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CA Technologies
By: Dell EMC     Published Date: Jun 29, 2016
IDC believes that EMC Isilon is indeed an easy to operate, highly scalable and efficient Enterprise Data Lake Platform. IDC validated that a shared storage model based on the Data Lake can in fact provide enterprise-grade service-levels while performing better than dedicated commodity off-the-shelf storage for Hadoop workloads.
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storage, data, enterprise, best practices, platform, network attached storage, storage area networks, storage management
    
Dell EMC
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