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Published By: Hewlett Packard Enterprise     Published Date: Jun 17, 2019
"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond the remote monitoring systems of a prior generation. Three key features differentiate cloud-based predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically what types of value these systems can drive, IDC discusses them at some length in this white paper."
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Hewlett Packard Enterprise
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: Intel     Published Date: Apr 11, 2019
The Internet of Things (IoT) unleashes valuable business insights through data that’s gathered at every level of a retail organization. With IoT and data analytics, retailers now have the capability to gather insight into customer behavior, offer more personalized experiences, achieve better inventory accuracy, create greater supply chain efficiencies, and so much more. But with data comes great risk. A recent report by security firm Thales and 451 Research found that 43 percent of retailers have experienced a data breach in the past year, with a third reporting more than one breach.1 Intel® technology-based gateways and Asavie, a provider of next-gen enterprise mobility management and IoT connectivity solutions, offer a security connectivity solution that minimizes the effort and cost to businesses to ensure safety from cybersecurity attacks. In addition, the Intel/Asavie IoT solution provides retailers with a solid basis to build their smart, connected projects:
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Intel
Published By: HERE Technologies     Published Date: May 22, 2019
Operational readiness depends on rich location data. When managing logistics and tracking high-value assets, there is no room for error and our new data-driven world demands richer, smarter advanced mapping and navigation services. The 2018 Counterpoint Research Location Ecosystems Update compared 16 location platform vendors—including Google, TomTom and Mapbox—and it named HERE the “undisputed leader” in location based services. Counterpoint recognized HERE for its integrated analytical capability and commitment to open partnerships, allowing for custom operational requirements and a truly mobile location intelligence platform. See how HERE provides the industry leading tools and expertise to process that data—streamlining the logistics supply chain, boosting responsiveness, and guaranteeing mission success.
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mapping, defence, location data.
    
HERE Technologies
Published By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
One of the biggest changes faces organizations making purchasing and deployment decisions about analytic databases -- including relational data warehouses -- is whether to opt for a cloud solution.
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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: Group M_IBM Q2'19     Published Date: May 03, 2019
"Managing and securing endpoints with conventional mobile device management (MDM) or enterprise mobile management (EMM) solutions is time-consuming and ineffective. For this reason, global IT leaders are turning towards unified endpoint management (UEM) solutions to consolidate their management of smartphones, tablets, laptops and IoT devices into a single management console. To increase operational efficiency, maximize data security and deliver on their digital transformation goals, they’ll need a UEM platform that does more than just promise success. The answer is a smarter solution, built for today, that brings new opportunities, threats, and efficiency improvements to the forefront. With Watson™, IBM® MaaS360® UEM features cognitive insights, contextual analytics, and cloud-sourced benchmarking capabilities. It helps you make sense of daily mobile details while managing your endpoints, users, apps, document, and data from one platform."
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: May 28, 2019
However, big data and analytics solutions can have shortcomings. Proprietary and best-of-breed approaches can require valuable time and resources to build, integrate and maintain — while outsourcing data analytics can constrain reporting frequency and timeliness. In a world where operational efficiency and fast, reliable information is paramount, these limitations can put payers at a competitive disadvantage.
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Group M_IBM Q2'19
Published By: Citrix Systems     Published Date: Jun 04, 2019
Now that 72.3% of cloud users have a mix of on-prem/off-prem clouds, the networking game has changed. Traditional app delivery solutions can’t ensure reliable, secure access in a SaaS, multi-device, hybrid, and multi-cloud world. Get this solution brief to learn why a holistic strategy innately reduces complexities that otherwise would prohibit visibility and control in distributed architectures. The brief also explains: The Citrix Networking approach to delivering reliability and a high-quality experience How to ensure reliable access to apps at branch and remote locations while keeping costs low How to provide full visibility and analytics for your network, applications, users, and data
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Citrix Systems
Published By: Simba by Magnitude     Published Date: Mar 25, 2019
Software providers say that connecting applications to data sources, having adequate resources to do so, applying an effective maintenance strategy and addressing scalability are top-of-mind challenges. This eBook from the connectivity experts with 100s of person-years of data adapter experience is your how-to guide on the journey toward addressing these challenges to accelerate adoption of your application.
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Simba by Magnitude
Published By: SAP     Published Date: Jun 18, 2011
To stay ahead of the competition in a global marketplace, firms are increasingly speeding up operations, in many cases adopting real-time systems and tools to allow for instant decision-making and faster business cycles. Download here to learn how.
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real-time business analytics, faster decision making, business automation, business metrics, analytical data, sap
    
SAP
Published By: SAP     Published Date: Feb 03, 2017
The spatial analytics features of the SAP HANA platform can help you supercharge your business with location-specific data. By analyzing geospatial information, much of which is already present in your enterprise data, SAP HANA helps you pinpoint events, resolve boundaries locate customers and visualize routing. Spatial processing functionality is standard with your full-use SAP HANA licenses.
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SAP
Published By: SAP     Published Date: Mar 09, 2017
There’s strong evidence organizations are challenged by the opportunities presented by external information sources such as social media, government trend data, and sensor data from the Internet of Things (IoT). No longer content to use internal databases alone, they see big data resources augmented with external information resources as what they need in order to bring about meaningful change. According to a September 2015 global survey of 251 respondents conducted by Harvard Business Review Analytic Services, 78 percent of organizations agree or strongly agree that within two years the use of externally generated big data will be “transformational.” But there’s work to be done, since only 21 percent of respondents strongly agree that external data has already had a transformational effect on their firms.
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SAP
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: HERE Technologies     Published Date: Apr 24, 2019
Find out how Locomizer, the award-winning global leader applying pattern-detection and spatial analytics, leveraged data from HERE Places in order to define a precise audience segment and the 10 best JCDecaux digital billboard locations that would ensure a successful ad campaign. Read the case study to discover: - which audience segment was targeted - why location was an important factor - how HERE Places data played an essential role in the campaign’s effectiveness
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spatial analytics, leveraged data, digital billboard, locomizer, here
    
HERE Technologies
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: 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 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: 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
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