data insights

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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
The bar for success is rising in higher education.  University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
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Hewlett Packard Enterprise
Published By: Uberflip     Published Date: Dec 20, 2018
In today’s world, marketers know that producing content isn’t enough. If they’re going to continue to make an investment in creating content, they need to do more to ensure it performs. We’ve long since known that combining content with a remarkable experience will allow it to reach its full potential, and allow marketers to see results. But as with any emerging category, content experience was not without its detractors. After all, what kind of results could you expect from an investment in the experience around that content? If you’ve ever wondered why you should care about content experience, and wanted something a little more concrete than a few anecdotes from marketers, or third-party stats, then look no further.
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Uberflip
Published By: TIBCO Software GmbH     Published Date: Jan 15, 2019
Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202
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TIBCO Software GmbH
Published By: IBM Watson Health     Published Date: Dec 10, 2018
In this case study, large health systems implement IBM Watson Health to surface improvement opportunities. Using this tool, they were able to cut costs, reduce patients’ length of stay, acquire actionable data, address number of readmissions and improve management of COPD and sepsis.
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hospitals, health systems, healthcare, analytics, data, insights, case study, performance improvement, healthcare insights, cost, length of stay, financial performance data, readmissions, quality performance, benchmarks, dashboards, patient volume, savings
    
IBM Watson Health
Published By: Artemis Health     Published Date: Feb 05, 2019
Self-insured employers are mining their health and benefits data to save costs and provide quality care for employees. Data is driving business decisions, but how do you get from millions of rows of data to a consumable graph to taking action? In this white paper, we’ll delve into data analytics best practices that help self-insured employers find actionable insights in their benefits data. • Which data sources will help you ensure you’re measuring the right thing at the right time • How to ensure data variety and choose key metrics • An example of a successful predictive analysis using benefits data
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Artemis Health
Published By: FICO EMEA     Published Date: Jan 25, 2019
Communications service providers (CSPs) have long recognized the potential of data analytics. Yet their early efforts to pull actionable intelligence from the oceans of data they have access to were largely unsuccessful. Many tried a 'big bang' approach to building a central repository without knowing what they wanted to do with the data in it. The arrival of artificial intelligence (AI) – its machine learning subset in particular – has changed their thinking and approach. For this Quick Insights report, we surveyed 64 professionals from CSPs around the world who are applying, leveraging and/ or planning to deploy advanced analytics in some capacity at various points across the customer lifecycle.
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analytics, artificial intelligence, customer lifecycle, insights, telecom credit lifecycle, customer acquisition, optimisation
    
FICO EMEA
Published By: Verisign     Published Date: May 31, 2017
Verisign has a unique view into distributed denial of service (DDos) attack trends, including attack statistics, behavioral trends and future outlook. The below data contains observations and insights about attack frequency and size derived from mitigations enacted on behalf of customers of Verisign DDoS Protection Services from January through March 2017.
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Verisign
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: 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
Published By: SAP     Published Date: May 18, 2014
Over the course of several months in 2011, IDC conducted a research study to identify the opportunities and challenges to adoption of a new technology that changes the way in which traditional business solutions are implemented and used. The results of the study are presented in this white paper.
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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
Forrester conducted in-depth surveys with 330 global BI decision-makers and found strong correlations between overall company success and adoption of innovative BI, analytics, and big data tools. In this paper, you will learn what separates the leading companies from the rest when it comes to exploiting innovative technologies in BI and analytics, and what steps you can take to either stay a leader or join their ranks.
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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, produced in collaboration with SAP, provides insight into executive perception of real-time business operations in North America. It is a companion paper to Real-time Business: Playing to win in the new global marketplace, published in May 2011, and to a series of papers on real-time business in Europe, Asia-Pacific and Latin America.
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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
Leading companies and technology providers are rethinking the fundamental model of analytics, and the contours of a new paradigm are emerging. The new generation of analytics goes beyond Big Data (information that is too large and complex to manipulate without robust software), and the traditional narrow approach of analytics which was restricted to analysing customer and financial data collected from their interactions on social media. Today companies are embracing the social revolution, using real-time technologies to unlock deep insights about customers and others and enable better-informed decisions and richer collaboration in real-time.
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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: Lenovo and Intel®     Published Date: Jan 08, 2019
If you are trying to process, understand, and benefit from "big data," you need SAP® HANA®. In-memory database Process data at extreme speeds Real-time analytics and insights If you want to make sure you have access to your data for insights, whenever and wherever you need them, then SAP HANA on Lenovo's future-defined infrastructure—powered by the Intel® Xeon® Platinum processor—delivers what you need. Get the details on everything you need to know about the value of SAP HANA, why SAP chose Lenovo for their own HANA installation, and how Lenovo can help your organization today.
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sap hana, lenovo, intel, big data, database, analytics, insights
    
Lenovo and Intel®
Published By: Hewlett Packard Enterprise     Published Date: Oct 24, 2017
Big Data is not just a big buzzword. Government agencies have been collecting large amounts of data for some time and analyzing the data collected to one degree or another. Big data is a term that describes high volume, variety and velocity of information that inundates an organization on a regular basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and better services.
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cloud optimization, cloud efficiency, cloud management, cloud assurance, cloud visibility, enterprise management, data management
    
Hewlett Packard Enterprise
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