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Published By: Aberdeen     Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
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aberdeen, michael lock, data-driven decisions, business intelligence, public sector, analytics, federal, state, governmental, decisions, data management
    
Aberdeen
Published By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse. First, the data warehouse appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had a substantial effect on the analytical architecture.
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Group M_IBM Q2'19
Published By: Forcepoint     Published Date: May 14, 2019
IDC Infobrief: How Security Solutions Enable Cloud Success Cloud applications have transformed how organizations conduct business, increasing productivity and reducing costs. However, moving to the cloud means critical data now flows outside the organization’s traditional security boundaries. Unsurprisingly, security concerns still rank as the number one reason for not using cloud services*. This IDC InfoBrief, sponsored by Forcepoint, outlines five key security considerations and best practices for safe cloud adoption, including: Multi-cloud adoption: exposing challenges for security architectures Cloud-first and GDPR implications Cloud application visibility and control Data management and DLP in the cloud Leveraging User and Entity Behavior Analytics (UEBA) for protection Read the eBook to find out the five information security lessons learned from transitioning to the cloud. *IDC’s 2017 CloudView Survey; IDC’s 2017 CloudImpact Survey
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Forcepoint
Published By: Forcepoint     Published Date: May 14, 2019
In Philip K. Dick's 1956 "The Minority Report," murder ceased to occur due to the work of the "Pre-Crime Division," that anticipated and prevented killings before they happened. Today, we are only beginning to see the impact of predictive analytics upon cybersecurity – especially for insider threat detection and prevention. Based on user interaction with data, CISOs and their teams emerge as the IT equivalent of a Pre-Crime Division, empowered to intervene before a violation is ever committed. Watch this webcast where we examine the technologies which make predictive analytics valuable, along with ethically minded guidance to strike the balance between vigilance and privacy.
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Forcepoint
Published By: Forcepoint     Published Date: May 14, 2019
Security spending is expected to reach $120 billion by 2021, yet the amount of data loss events seems to be increasing. Legacy DLP solutions, which rely on traditional threat blocking policies, have been unable to evolve to address these threats. Organizations need to fundamentally rethink how they address cybersecurity for today’s modern threats. Watch this webcast to understand how taking a Risk-Adaptive approach enables security to fluctuate based on the threat environment. See how Dynamic Data Protection, an industry-first solution, uses human-centric behavior analytics to continuously determine the risk cyber identities pose, based on their actions.
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Forcepoint
Published By: Forcepoint     Published Date: May 14, 2019
IDC Infobrief: How Security Solutions Enable Cloud Success Cloud applications have transformed how organizations conduct business, increasing productivity and reducing costs. However, moving to the cloud means critical data now flows outside the organization’s traditional security boundaries. Unsurprisingly, security concerns still rank as the number one reason for not using cloud services*. This IDC InfoBrief, sponsored by Forcepoint, outlines five key security considerations and best practices for safe cloud adoption, including: Multi-cloud adoption: exposing challenges for security architectures Cloud-first and GDPR implications Cloud application visibility and control Data management and DLP in the cloud Leveraging User and Entity Behavior Analytics (UEBA) for protection Read the eBook to find out the five information security lessons learned from transitioning to the cloud. *IDC’s 2017 CloudView Survey; IDC’s 2017 CloudImpact Survey
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Forcepoint
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: 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: 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
    
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
    
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
    
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
    
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
    
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
    
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
    
SAP
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