data analytics

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Published By: Genesys     Published Date: Jun 19, 2019
Successfully managing a contact center requires a collaborative, multidisciplinary approach to handle a broad range of operational and tactical tasks. Planning, day-to-day operations and quality management must be seamlessly orchestrated, along with human resources functions like recruitment, learning and development, and employee scheduling. Read this executive brief to learn how to transition to an AI strategy that can take your team – and business results – to the next level. See how you can: Create an AI strategy with a single data model that includes routing, interaction analytics, forecasting/scheduling and predictive engagement Harness the power of your data to align customers with the best resource Drive employee effectiveness by ensuring you hire the right people and manage their performance to drive their success over the long term
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Genesys
Published By: Simba by Magnitude     Published Date: Jul 12, 2019
Today’s C-level executives expect data and analytics to provide them with speed and agility to deliver competitive advantage and to disrupt new markets. But, in today’s complex data environment exists a near paradox between these expectations, that companies will be able to rapidly deliver value using data and analytics--and the complexities of the data landscape, making it more difficult to find, govern, connect to and access the data needed to deliver that value. Once thing is clear: if management expectation is to be met, simplifying connectivity is a must.In this white paper, veteran analyst Mike Ferguson, Managing Director of Intelligent Business Strategies explores how simplifying data access –connectivity –aligns expectations with data realities thus decreasing time to value.
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Simba by Magnitude
Published By: Mindfire     Published Date: May 07, 2010
In this report, results from well over 650 real-life cross-media marketing campaigns across 27 vertical markets are analyzed and compared to industry benchmarks for response rates of static direct mail campaigns, to provide a solid base of actual performance data and information.
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mindfire, response rates, personalized cross-media, marketing campaign, personalization, personalized urls, purls, performance data, conversion, marketing roi, direct mail campaign, multi channel marketing, integrated marketing campaign, lead generation, campaign management, tracking and measurement, reports and analytics, marketing dashboard, interactive marketing
    
Mindfire
Published By: Cisco     Published Date: Mar 22, 2019
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
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Cisco
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: Zaloni     Published Date: Apr 24, 2019
Why your data catalog won’t deliver significant ROI According to Gartner, organizations that provide access to a curated catalog of internal and external data assets will derive twice as much business value from their analytics investments by 2020 than those that do not. That’s a ringing endorsement of data catalogs, and a growing number of enterprises seem to agree. In fact, the global data catalog market is expected to grow from US$210.0 million in 2017 to US$620.0 million by 2022, at a Compound Annual Growth Rate (CAGR) of 24.2%. Why such large and intensifying demand for data catalogs? The primary driver is that many organizations are working to modernize their data platforms with data lakes, cloud-based data warehouses, advanced analytics and various SaaS applications in order to grow profitable digital initiatives. To support these digital initiatives and other business imperatives, organizations need more reliable, faster access to their data. However, modernizing data plat
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Zaloni
Published By: Hewlett Packard Enterprise     Published Date: Jul 25, 2019
With digital IT transformation solutions and new business models driven by the democratization of data, advanced analytics, and a citizen-centric approach, HPE helps cities like yours get smarter—and continue to evolve into great places for your citizens to live. Visit hpe.com/info/public-sector to learn how you can take the next step on your journey.
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Hewlett Packard Enterprise
Published By: Cisco EMEA     Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
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big data, analytics, virtualization, cloudera, ibm, sas, sap, splunk
    
Cisco EMEA
Published By: Cisco EMEA     Published Date: Mar 05, 2018
The competitive advantages and value of BDA are now widely acknowledged and have led to the shifting of focus at many firms from “if and when” to “where and how.” With BDA applications requiring more from IT infrastructures and lines of business demanding higher-quality insights in less time, choosing the right infrastructure platform for Big Data applications represents a core component of maximizing value. This IDC study considered the experiences of firms using Cisco UCS as an infrastructure platform for their BDA applications. The study found that Cisco UCS contributed to the strong value the firms are achieving with their business operations through scalability, performance, time to market, and cost effectiveness. As a result, these firms directly attributed business benefits to the manner in which Cisco UCS is deployed in the infrastructure.
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big data, analytics, cisco, value, business, enterprise
    
Cisco EMEA
Published By: Spectrum Enterprise     Published Date: Jun 05, 2019
The success of every business is driven by the quality of its connections, whether with clients, employees, investors, suppliers, manufacturers or other key stakeholders. Increasingly, these relationships are measured through data-driven analytics, enhanced through video communication, and empowered through cloud computing and collaboration. As the volume of data grows, so do bandwidth requirements.
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Spectrum Enterprise
Published By: Hitachi Vantara     Published Date: Mar 08, 2019
Consider the key trends driving the modernization of the data infrastructure: focus on governance, mobilization and analytics. And take a look at the technologies that make up modern data infrastructure, including artificial intelligence (AI), flash storage, converged and hyperconverged platforms, and software-defined infrastructures. Read this e-book to observe the key trends driving the modernization of data infrastructure and see how organizations are adapting and flourishing in a data-driven world.
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Hitachi Vantara
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
Digital transformation (DX) is a must for midsize firms (those with 100 to 999 employees) to thrive in the digital economy. DX enables firms to increase competitive advantage through initiatives such as automating business processes, creating greater operational efficiencies, building deeper customer relationships, and creating new revenue streams based on technology-enabled products and services. DX is a journey, and it starts with firms embracing an IT-centric vision that guides a data-driven, analytics-first strategy. The outcome of DX initiatives depends on the ability of a firm to efficiently leverage people (talent), process, platforms, and governance to meet the firm’s business objectives.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem. Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: May 10, 2019
Nimble Secondary Flash array represents a new type of data storage, designed to maximize both capacity and performance. By adding high-performance flash storage to a capacity-optimized architecture, it provides a unique backup platform that lets you put your backup data to work. Nimble Secondary Flash array uses flash performance to provide both near-instant backup and recovery from any primary storage system. It is a single device for backup, disaster recovery, and even local archiving. By using flash, you can accomplish real work such as dev/test, QA, and analytics. Deep integration with Veeam’s leading backup software simplifies data lifecycle management and provides a path to cloud archiving.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: May 10, 2019
The performance of enterprise applications will have a direct impact on business activities and outcomes. The quality of the delivery of applications will depend on how smoothly the underlying data infrastructure operates. ? Optimal application performance and delivery is difficult to achieve in complex environments. ? Many IT infrastructure and operations teams are stretched to the breaking point. ? Predictive analytics and machine learning can be applied to great effect
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Hewlett Packard Enterprise
Published By: SAP     Published Date: May 18, 2014
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications
    
SAP
Published By: SAP     Published Date: May 18, 2014
Download this whitepaper to learn the results of this latest exploration of the emerging world of in-memory database technologies.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications, database development
    
SAP
Published By: SAP     Published Date: May 18, 2014
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications, database development
    
SAP
Published By: SAP     Published Date: May 18, 2014
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, database development, service oriented architecture
    
SAP
Published By: SAP     Published Date: May 18, 2014
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications
    
SAP
Published By: SAP     Published Date: May 18, 2014
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications
    
SAP
Published By: SAP     Published Date: May 18, 2014
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications
    
SAP
Published By: SAP     Published Date: May 18, 2014
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, it management, knowledge management
    
SAP
Published By: SAP     Published Date: May 18, 2014
This paper explores the results of a survey, fielded in April 2013, of 304 data managers and professionals, conducted by Unisphere Research, a division of Information Today Inc. It revealed a range of practical approaches that organizations of all types and sizes are adopting to manage and capitalize on the big data flowing through their enterprises.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications
    
SAP
Published By: SAP     Published Date: May 18, 2014
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
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sap, big data, real time data, in memory technology, data warehousing, analytics, big data analytics, data management, business insights, architecture, business intelligence, big data tools, analytical applications
    
SAP
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