analytic data

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Published By: QlikTech UK     Published Date: Aug 10, 2015
In today’s digital healthcare world, analytics are critical. In the healthcare industry, your goals are visionary, complex and critically important to the health of both individuals and the economy. To successfully reach higher-value services, better health and lower costs, you need a healthcare analytics solution that tells you the whole story and unlocks the value that lives within your data.
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QlikTech UK
Published By: QlikTech UK     Published Date: Nov 24, 2015
Organizations are, or will soon be, producing petabytes – thousands of terabytes or millions of gigabytes – of valuable data. But the ability to transform these massive data sets into actionable insights requires business intelligence (BI) and analytics tools that can uncover the hidden relationships among varied sources of information, provide rich visualizations of trends and don’t require end-users to be trained data scientists.
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healthcare
    
QlikTech UK
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 Q3'19     Published Date: Jun 27, 2019
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data.
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Group M_IBM Q3'19
Published By: Sierra Wireless     Published Date: Jun 19, 2019
The IoT is transforming the energy industry by eliminating tradeoffs between operation, SCADA systems, maintenance and new services for assets deployed in industrial and power facilities, buildings and across the grid. When it comes to building the best IoT system for your business application, it’s vital to keep your use case and business requirements at the forefront of your technical design strategy. In the energy industry, accessing and collecting data at the edge from disparate, heterogenous, multi-site, fixed topologies and transferring that data efficiently to the cloud to perform analytics and action business decisions is still the greatest challenge. Mission-critical data collected from the edge is integral to energy facility operations and cannot be excluded or corrupted.
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Sierra Wireless
Published By: Infinidat EMEA     Published Date: May 14, 2019
Big Data and analytics workloads represent a new frontier for organizations. Data is being collected from sources that did not exist 10 years ago. Mobile phone data, machine-generated data, and website interaction data are all being collected and analyzed. In addition, as IT budgets are already under pressure, Big Data footprints are getting larger and posing a huge storage challenge. This paper provides information on the issues that Big Data applications pose for storage systems and how choosing the correct storage infrastructure can streamline and consolidate Big Data and analytics applications without breaking the bank.
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Infinidat EMEA
Published By: Commvault ABM Oct     Published Date: Jul 17, 2019
Enterprises are cobbling together all the pieces that make up a digital business - improved analytics, scalable architecture, automation, and more engaging customer experiences, just to name a few. At the same time, they're facing the ever-present threats of cyber attacks and data breaches.
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Commvault ABM Oct
Published By: Flexential     Published Date: Jul 17, 2019
In a data environment that’s become increasingly centralized by public cloud services, the “edge” is emerging as a critical solution for reducing latency for network-based services. Consumption habits of services and the need for analytics are shifting beyond core population centers, becoming local and even hyper-local within a region or city. As the online population continues to grow and new services emerge, the ability to handle data traffic securely – close to the customer or application – will become a common pattern for the new service evolution.
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Flexential
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: 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: 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
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
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