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data model

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Published By: Zaloni     Published Date: Apr 23, 2019
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
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Zaloni
Published By: Oracle EMEA     Published Date: Apr 15, 2019
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; it’s a whole new approach to getting more value from your data. Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results. Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployed—either on premises or in the cloud—they face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets. Oracle has a better way. Download this whitepaper to f
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Oracle EMEA
Published By: Group M_IBM Q2'19     Published Date: Apr 10, 2019
A new era of business reinvention is dawning. Organizations are facing an unprecedented convergence of technological, social and regulatory forces. As artificial intelligence, automation, Internet of Things, blockchain and 5G become pervasive, their combined impact will reshape standard business architectures. The “outside-in” digital transformation of the past decade is giving way to the “inside-out” potential of data exploited with these exponential technologies. We call this next-generation business model the Cognitive Enterprise.
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Group M_IBM Q2'19
Published 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
Published By: VMware     Published Date: Apr 09, 2019
To help their business clients unleash innovation and support growth, IT teams need to evolve to a modern data center that is virtualized, software defined and automated, with a consistent operational model for infrastructure and application delivery. In this collection of case studies, we reveal how companies are building more agile, innovative businesses based on VMware solutions.
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VMware
Published By: VMware     Published Date: Apr 09, 2019
Lower your data center costs with VMware vSan. In this infographic, we’ll show you how to reduce CAPEX and OPEX with a pay-as-you-grow model that enables rapid application deployment and easy ongoing management.
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VMware
Published 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
Published By: Here Technologies     Published Date: Apr 02, 2019
In this report, VSI applies HERE’s HD map data to a lane keeping application and examines performance of lane keeping with a map-based approach compared to a camera and computer vision-based approach. VSI tested the lane keeping system with and without map data on a local road in 3 scenarios: Lane lines expanding into a turn or exit lane An intersection without lane lines A widening in the lane The results show that in all scenarios, the computer-vision-only lane keeping systems got confused and made errors in a vehicle’s trajectory when lane markings were out of the ordinary or invisible. Faced with the same road conditions, the map-based lane keeping system stayed within the desired trajectory outperforming the compute- vision-only systems. This report proves that using a lane model from an HD map can solve common issues involved in computer-vision-only lane keeping.
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over the air technologies, location data, auto, mapping
    
Here Technologies
Published By: Red Hat     Published Date: Mar 28, 2019
Technology has fundamentally changed the way we live. Access to data and information anytime, anywhere is no longer a luxury—it is a requirement, in both our personal and professional lives. For IT organizations, this means pressure has never been greater to deliver higher-quality applications more often, enabling companies to stay relevant and seize digital business opportunities. Cloud-native is an approach to building applications that takes advantage of cloud computing models and DevOps principles to make the delivery of new features and services faster and more flexible. With a cloud-native strategy, organizations can begin the culture, process, and technology changes needed to meet new demands and become an IT organization that can deliver business innovation faster.
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Red Hat
Published By: Cisco     Published Date: Mar 22, 2019
The Secure Data Center is a place in the network (PIN) where a company centralizes data and performs services for business. Data centers contain hundreds to thousands of physical and virtual servers that are segmented by applications, zones, and other methods. This guide addresses data center business flows and the security used to defend them. The Secure Data Center is one of the six places in the network within SAFE. SAFE is a holistic approach in which Secure PINs model the physical infrastructure and Secure Domains represent the operational aspects of a network.
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Cisco
Published By: Cisco     Published Date: Mar 22, 2019
Cisco ACI, the industry-leading software-defined networking solution, facilitates application agility and data center automation. With ACI Anywhere, enable scalable multicloud networks with a consistent policy model, and gain the flexibility to move applications seamlessly to any location or any cloud while maintaining security and high availability.
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Cisco
Published By: SAS     Published Date: Mar 20, 2019
In today’s crowded analytics marketplace, who can you trust? What’s needed to deliver on the promise of transforming data into real value? And what do CIOs need to cost-effectively and successfully lead their organizations through changing technologies? For an organization to experiment with (and ultimately deploy) analytics, the responsibility falls squarely on the shoulders of IT. IT must provide secure access to lots of high-quality data, a friendly environment for experimentation and discovery, and a method for rapidly deploying and governing models. SAS can support an organization's journey toward becoming a data- and analytics-driven organization. We can help unlock the value by enabling with choices that make sense. Plus, we can show organizations how to get the most out of technology investments.
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SAS
Published By: IBM APAC     Published Date: Mar 06, 2019
The Forrester Study on cost savings and business benefits enabled by Watson Studio and Watson Knowledge Catalog. Watson Studio provides a suite of tools for data scientists, application developers, and subject matter experts to collaboratively and easily work with data and use that data to build, train and deploy machine learning models at scale. The Forrester provides readers a framework to evaluate the potential financial impact of the Watson Studio and Watson Knowledge Catalog investment on their organizations.
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IBM APAC
Published By: BetterUp     Published Date: Mar 06, 2019
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. Learn how coaching ROI has been measured in the past, and why these methods are flawed. Discover which inputs are factored into our ROI algorithm and you can map the ROI of coaching to tangible business results.
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BetterUp
Published By: HERE Technologies     Published Date: Feb 26, 2019
In this report, VSI applies HERE’s HD map data to a lane keeping application and examines performance of lane keeping with a map-based approach compared to a camera and computer vision-based approach. VSI tested the lane keeping system with and without map data on a local road in 3 scenarios: 1. Lane lines expanding into a turn or exit lane 2. An intersection without lane lines 3. A widening in the lane The results show that in all scenarios, the computer-vision-only lane keeping systems got confused and made errors in a vehicle’s trajectory when lane markings were out of the ordinary or invisible. Faced with the same road conditions, the map-based lane keeping system stayed within the desired trajectory outperforming the compute- vision-only systems. This report proves that using a lane model from an HD map can solve common issues involved in computer-vision-only lane keeping.
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location data, auto, mapping
    
HERE Technologies
Published By: Nice Systems     Published Date: Feb 26, 2019
NICE has made a significant investment into AI and ML techniques that are embedded into its core workforce management solution, NICE WFM. Recent advancements include learning models that find hidden patterns in the historical data used to generate forecasts for volume and work time. NICE WFM also has an AI tool that determines, from a series of more than 40 models, which single model will produce the best results for each work type being forecasted. NICE has also included machine learning in its scheduling processes which are discussed at length in the white paper.
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Nice Systems
Published By: HP Inc.     Published Date: Feb 14, 2019
How to overcome complexity and be ready for future growth. The modern production digital print market brought a world of opportunities for micro-runs and variable data printing into the hands of Print Service Providers (PSPs). With print available in any quantity to anyone, print is being democratized, resulting in ever-greater numbers of increasingly smaller jobs. The old print model of high-volume static print is being replaced with a myriad of micro-runs and micro-jobs. Automation that allows PSP owners to master the ensuing complexity and respond faster than ever before is enabling them to refocus on market development and on delivering value.
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HP Inc.
Published By: CloudHealth by VMware     Published Date: Feb 13, 2019
Google Cloud Platform is being widely adopted for its security and performance networking capabilities, machine learning, Kubernetes support, and data analytics. Google has been developing innovative price models to attract new users and provide cost benefits for customers. Read this eBook for answers to questions such as: -What are Committed Use Discounts? -Why do you need Committed Use Discounts? -What are Sustained Use Discounts? -What is the difference between Committed and Sustained Use Discounts? Download GCP Discounts and Why You Should Care to learn how you can take advantage of discounts in Google Cloud Platform to save you money on your monthly cloud bill.
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cloud management, google cloud platform, multicloud management
    
CloudHealth by VMware
Published By: Domino Data Lab     Published Date: Feb 08, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
Published By: Domino Data Lab     Published Date: Feb 08, 2019
A data science platform is where all data science work takes place and acts as the system of record for predictive models. While a few leading model-driven businesses have made the data science platform an integral part of their enterprise architecture, most companies are still trying to understand what a data science platform is and how it fits into their architecture. Data science is unlike other technical disciplines, and models are not like software or data. Therefore, a data science platform requires a different type of technology platform. This document provides IT leaders with the top 10 questions to ask of data science platforms to ensure the platform handles the uniqueness of data science work.
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Domino Data Lab
Published By: Domino Data Lab     Published Date: Feb 08, 2019
As organizations increasingly strive to become model-driven, they recognize the necessity of a data science platform. According to a recent survey report “Key Factors on the Journey to Become Model-Driven”, 86% of model-driven companies differentiate themselves by using a data science platform. And yet the question of whether to build or buy still remains. This paper presents a framework to facilitate the decision process, and considers the four-year projection of total costs for both approaches in a sample scenario. Read this whitepaper to understand three major factors in your decision process: Total cost of ownership - Internal build costs often run into the tens of millions Opportunity costs - Distraction from your core competency Risk factors - Missed deadlines and delayed time to market
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Domino Data Lab
Published By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
"Extracting value from data is central to the digital transformation required for businesses to succeed in the decades to come. Buried in data are insights that reveals what your customers need and how they want to receive it, how sales, manufacturing, distribution, and other aspects of business operations are functioning, what risks are arising to threaten the business, and more. That insight empowers your businesses to reach new customers, develop and deliver new products, to operate more efficiently and more effectively, and even to develop new business models. "
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Jan 31, 2019
"IT needs to reach beyond the traditional data center and the public cloud to form and manage a hybrid connected system stretching from the edge to the cloud, wherever the cloud may be. We believe this is leading to a new period of disruption and development that will require organizations to rethink and modernize their infrastructure more comprehensively than they have in the past. Hybrid cloud and hybrid cloud management will be the key pillars of this next wave of digital transformation – which is on its way much sooner than many have so far predicted. They have an important role to play as part of a deliberate and proactive cloud strategy, and are essential if the full benefits of moving over to a cloud model are to be fully realized."
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Hewlett Packard Enterprise
Published By: Larsen & Toubro Infotech(LTI)     Published Date: Jan 31, 2019
LTI helped a leading global bank digitize its traditional product ecosystem for AML transaction monitoring. With the creation of a data lake and efficient learning models, the bank successfully reduced false positives and improved customer risk assessment. Download Complete Case Study.
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Larsen & Toubro Infotech(LTI)
Published By: Oracle     Published Date: Jan 28, 2019
For more than a decade, Oracle has developed and enhanced its ZFS Storage Appliance, giving its users a formidable unified and enterprise-grade storage offering. The latest release, ZS7-2, boasts upgraded hardware and software and is a timely reminder that more users might do well to evaluate this offering. It has a trifecta of advantages: (1) It’s notable performance, price-performance, and flexibility are all improved in this new release (2) There is a surprisingly inclusive set of functionalities, including excellent storage analytics that were developed even before analytics became a contemporary “must-have” (3) There’s a compelling group of “better together” elements that make ZFS Storage Appliance a particularly attractive choice for both Oracle Database environments and users that want to seamlessly integrate a cloud component into their IT infrastructure. Given the proven abilities of Oracle’s prior models, it’s also safe to assume that the new ZS7-2 will outperform other m
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Oracle
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