data insights

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By: IBM     Published Date: Sep 02, 2014
Advanced analytics strategies yield the greatest benefits in terms of improving patient and business outcomes when applied across the entire healthcare ecosystem. But the challenge of collaborating across organizational boundaries in order to share information and insights is daunting to many stakeholders. In this worldwide survey of 555 healthcare providers, payers and life sciences organizations, you will learn the importance of implementing collaborative analytics strategies that: Manage, integrate and interpret data generated at all stages of the healthcare value chain Achieve the right balance of skills in order to translate data into actionable insights Focus on executive sponsorship and enterprise-wide adoption with metrics to measure and track success Position yourself to harness data, create and share insights, make informed decisions, and improve the performance of the entire healthcare ecosystem in which you operate.
Tags : ibm, analytics acrosss ecosystem
     IBM
By: IBM     Published Date: Sep 02, 2014
With tougher regulations and continuing market volatility, financial firms are moving to active risk management with a focus on counterparty risk. Firms are revamping their risk and trading practices from top to bottom. They are adopting new risk models and frameworks that support a holistic view of risk. Banks recognize that technology is critical for this transformation, and are adding state-of-the-art enterprise risk management solutions, high performance data and grid management software, and fast hardware. Join IBM Algorithmics and IBM Platform Computing to gain insights on this trend and on technologies for enabling active "real-time" risk management.
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     IBM
By: IBM     Published Date: Sep 02, 2014
In today’s stringent financial services regulatory environment with exponential growth of data and dynamic business requirements, Risk Analytics has become integral to businesses. IBM Algorithmics provides very sophisticated analyses for a wide range of economic scenarios that better quantify risk for multiple departments within a firm, or across the enterprise. With Algorithmics, firms have a better handle on their financial exposure and credit risks before they finalize real-time transactions. But this requires the performance and agility of a scalable infrastructure; driving up IT risk and complexity. The IBM Application Ready Solution for Algorithmics provides an agile, reliable and high-performance infrastructure to deliver trusted risk insights for sustained growth and profitability. This integrated offering with a validated reference architecture delivers the right risk insights at the right time while lowering the total cost of ownership.
Tags : ibm, it risk, financial risk analytics
     IBM
By: IBM     Published Date: May 20, 2015
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     IBM
By: IBM     Published Date: May 20, 2015
There is a lot of hype around the potential of big data and organizations are hoping to achieve new innovations in products and services with big data and analytics driving more concrete insights about their customers and their own business operations. To meet these challenges, IBM has introduced IBM® Spectrum Scale™. The new IBM Spectrum Scale storage platform has grown from GPFS, which entered the market in 1998. Clearly, IBM has put significant development into developing this mature platform. Spectrum Scale addresses the key requirements of big data storage - extreme scalability for growth, reduced overhead of data movement, easy accessibility , geographic location independence and advanced storage functionality. Read the paper to learn more!
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     IBM
By: Splice Machine     Published Date: Feb 13, 2014
Hadoop: Moving Beyond the Big Data Hype Let’s face it. There is a lot of hype surrounding Big Data and adoop, the defacto Big Data technology platform. Companies want to mine and act on massive data sets, or Big Data, to unlock insights that can help them improve operational efficiency, delight customers, and leapfrog their competition. Hadoop has become popular to store massive data sets because it can distribute them across inexpensive commodity servers. Hadoop is fundamentally a file system (HDFS or Hadoop Distributed File System) with a specialized programming model (MapReduce) to process the data in the files. Big Data has not lived up to expectations so far, partly because of limitations of Hadoop as a technology.
Tags : sql-on-hadoop® evaluation guide, splice machine, adoop
     Splice Machine
By: Dell and Intel®     Published Date: Jun 18, 2015
The rapid evolution of big data technology in the past few years has changed forever the pursuit of scientific exploration and discovery. Along with traditional experiment and theory, computational modeling and simulation is a third paradigm for science. Its value lies in exploring areas of science in which physical experimentation is unfeasible and insights cannot be revealed analytically, such as in climate modeling, seismology and galaxy formation. More recently, big data has been called the “fourth paradigm" of science. Big data can be observed, in a real sense, by computers processing it and often by humans reviewing visualizations created from it. In the past, humans had to reduce the data, often using techniques of statistical sampling, to be able to make sense of it. Now, new big data processing techniques will help us make sense of it without traditional reduction
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     Dell and Intel®
By: IBM     Published Date: Sep 04, 2013
This white paper outline the vale of the big data that continues to accumulate within your organization. It show how by making this data more accessible to relevant stakeholders you can unlock the value and insights, while minimizing risk.
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     IBM
By: IBM     Published Date: Nov 14, 2014
Every day, the world creates 2.5 quintillion bytes of data and businesses are realizing tangible results from investments in big data analytics. IBM Spectrum Scale (GPFS) offers an enterprise class alternative to Hadoop Distributed File System (HDFS) for building big data platforms and provides a range of enterprise-class data management features. Spectrum Scale can be deployed independently or with IBM’s big data platform, consisting of IBM InfoSphere® BigInsights™ and IBM Platform™ Symphony. This document describes best practices for deploying Spectrum Scale in such environments to help ensure optimal performance and reliability.
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     IBM
By: Dell and Intel®     Published Date: Aug 24, 2015
In today’s digitally driven world, the success of a business is increasingly tied to its ability to extract value from data. Exploiting the untapped value of your data is now the pathway to success. By putting data-driven decision making at the heart of the business, your organization can harness a wealth of information to gain an unparalleled competitive advantage. In a future-ready enterprise, you must make a fundamental shift from a focus on technology to a strategic business focus. Data-driven insights can guide everything from the formulation of top-level corporate strategies to connected devices that monitor and enable immediate critical decisions, to the creation of personalized customer interactions. Data is the foundation for enabling business transformation and innovation.
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     Dell and Intel®
By: Dell APAC     Published Date: May 29, 2019
Digital transformation (DX) is reaching a macroeconomic scale. DX business objectives are balanced between tactical and strategic objectives and range from improvement in operational efficiencies and customer satisfaction to increasing existing product revenue to improving profit margins to launching new digital revenue streams. Successful DX relies on utilizing data for services as well as converting data into actionable insights. This reliance on data is contributing to a new digital era. 3rd Platform (cloud, social, mobile, and Big Data) computing is the underpinning of DX worldwide. It enables collection of a vast breadth of data sets and delivers the agility and efficiency needed to accelerate DX
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     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
Digital transformation (DX) is reaching a macroeconomic scale. DX business objectives are balanced between tactical and strategic objectives and range from improvement in operational efficiencies and customer satisfaction to increasing existing product revenue to improving profit margins to launching new digital revenue streams. Successful DX relies on utilizing data for services as well as converting data into actionable insights. This reliance on data is contributing to a new digital era. 3rd Platform (cloud, social, mobile, and Big Data) computing is the underpinning of DX worldwide. It enables collection of a vast breadth of data sets and delivers the agility and efficiency needed to accelerate DX
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     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
Digital transformation (DX) is reaching a macroeconomic scale. DX business objectives are balanced between tactical and strategic objectives and range from improvement in operational efficiencies and customer satisfaction to increasing existing product revenue to improving profit margins to launching new digital revenue streams. Successful DX relies on utilizing data for services as well as converting data into actionable insights. This reliance on data is contributing to a new digital era. 3rd Platform (cloud, social, mobile, and Big Data) computing is the underpinning of DX worldwide. It enables collection of a vast breadth of data sets and delivers the agility and efficiency needed to accelerate DX
Tags : 
     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
Digital transformation (DX) is reaching a macroeconomic scale. DX business objectives are balanced between tactical and strategic objectives and range from improvement in operational efficiencies and customer satisfaction to increasing existing product revenue to improving profit margins to launching new digital revenue streams. Successful DX relies on utilizing data for services as well as converting data into actionable insights. This reliance on data is contributing to a new digital era. 3rd Platform (cloud, social, mobile, and Big Data) computing is the underpinning of DX worldwide. It enables collection of a vast breadth of data sets and delivers the agility and efficiency needed to accelerate DX
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     Dell APAC
By: HERE Technologies     Published Date: May 24, 2019
How secure is your company’s network? The rising frequency of employee network access is fast becoming one of the most prevalent and unmanaged risks to the protection of critical enterprise data. When coupled with increasingly sophisticated cyber-attacks, the possibility of a security breach of enterprise networks becomes more likely. As one of the world’s leading location platforms in 2018, HERE shares insights and solutions to preventing identity fraud. Discover the latest facts and statistics. Learn more about the use-case of location verification when logging into your company’s network. Download the infographic from HERE Technologies.
Tags : technology, mapping, location data
     HERE Technologies
By: Cisco EMEA     Published Date: Mar 26, 2019
Most organizations have invested, and continue to invest, in people, processes, technology, and policies to meet customer privacy requirements and avoid significant fines and other penalties. In addition, data breaches continue to expose the personal information of millions of people, and organizations are concerned about the products they buy, services they use, people they employ, and with whom they partner and do business with generally. As a result, customers are asking more questions during the buying cycle about how their data is captured, used, transferred, shared, stored, and destroyed. In last year’s study (Cisco 2018 Privacy Maturity Benchmark Study), Cisco introduced data and insights regarding how these privacy concerns were negatively impacting the buying cycle and timelines. This year’s research updates those findings and explores the benefits associated with privacy investment. Cisco’s Data Privacy Benchmark Study utilizes data from Cisco’s Annual Cybersecurity Benchma
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     Cisco EMEA
By: CyberSource     Published Date: Apr 25, 2019
Download this white paper to find out how you could augment your fraud management with Decision Manager machine learning insights from more than 68 billion annually processed Visa and CyberSource transactions – matched with flexible rules-based fraud strategies. • Detect fraud more accurately with robust data and insights on ever-changing fraud patterns • Protect your bottom line by reducing fraud and chargebacks • Increase acceptance rates with the only fraud solution that uses machine learning to generate and test new rules-based strategies from your historic data …and more.
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     CyberSource
By: Workday APAC     Published Date: May 08, 2019
Whether informing talent strategy or building more effective teams, data-driven insights about your workforce can set you up for success. This eBook from Human Capital Institute explores how people analytics can empower your entire organization. Read now.
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     Workday APAC
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
By: Oracle     Published Date: Jun 04, 2019
How confident are you and your peers about the data and security practices you’re working with? We asked 5,000 executives globally, across 24 markets and have some interesting results to share. For example, up to half of IT leaders consider their data is manageable but struggle to gain meaningful insights from it. Yet, while AI and autonomous technology could help relieve this situation, they aren’t high on the priority list. Read our report to find out more about executives’ views about data in connection with security, ethics, and visualisation. Read the report
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     Oracle
By: Oracle     Published Date: Jun 04, 2019
Data is central to marketing function, yet research shows that 50% of CMOs struggle to manage data volumes, or gain insights. Read how to address data ethics and management in your organisation. Marketing’s top priority is to enforce technologies enabling real time data insights to drive instant, personalised CX. Meanwhile, only 30% of CMOs say they have data visualisation dashboards to analyse specific sets of data. Read the findings
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     Oracle
By: Oracle     Published Date: Jun 10, 2019
In our recent report, we look into the reasons why HR feel less than confident in their ability to manage the volume of data securely and ethically. From extracting the right type of insights to improving employee productivity and engagement to managing the skills pipeline. We look forwards to how HR can improve their systems by using automated technologies such as artificial intelligence and machine learning. Read the survey today to see how your organisation compares to your peers.
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     Oracle
By: DataCore     Published Date: Jun 06, 2019
Nothing in Business Continuity circles ranks higher in importance than risk reduction. Yet the risk of major disruptions to business continuity practices looms ever larger today, mostly due to the troubling dependencies on the location, topology and suppliers of data storage. Get insights on how to avoid spending time and money reinventing BC/DR plans every time your storage infrastructure changes.
Tags : business continuity, disaster recovery, data protection, software defined storage, virtualization, storage, downtime, high availability, replication, storage infrastructure
     DataCore
By: AWS     Published Date: Jun 11, 2019
Trupanion, a Seattle-based medical insurance provider for cats and dogs, needed to find data insights quickly. With only 1% of pet owners insured, the process of evaluating a claim to approve or deny payment was manual and time-consuming. Building accurate predictive models for decision-making required manpower, time, and technology that the small company simply did not have. DataRobot Cloud, built on AWS, helped Trupanion create an automated method for building data models using machine learning that reduced the time required to process claims from minutes to seconds. Join our webinar to hear how Trupanion transformed itself into an AI-driven organization, with robust data analysis and data science project prototyping that empowered the company to make better decisions and optimize business processes in less time and at a reduced cost. Join our webinar to learn: Why you don’t need to be an expert in data science to create accurate predictive models. How you can build and deploy pr
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     AWS
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
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