machine learning

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Published By: Cognizant     Published Date: Oct 23, 2018
A group of emerging technologies is rapidly creating numerous opportunities for life sciences companies to improve productivity, enhance patient care and ensure regulatory compliance. These technologies include robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), blockchain, the Internet of Things (IoT), 3-D printing and augmented reality/ virtual reality (AR/ VR). This whitepaper presents a preview of five pivotal technology trends remaking the life sciences industry: AI and automation, human augmentation, edge analytics/ processing, data ownership and protection, and the intermingling of products and services.
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cognizant, life sciences, patient care
    
Cognizant
Published By: TIBCO Software EMEA     Published Date: Sep 12, 2018
By processing real-time data from machine sensors using artificial intelligence and machine learning, it’s possible to predict critical events and take preventive action to avoid problems. TIBCO helps manufacturers around the world predict issues with greater accuracy, reduce downtime, increase quality, and improve yield. Read about our top data science best practices for becoming a smart manufacturer.
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inter-company connectivity, real-time tracking, automate analytic models, efficient analytics, collaboration
    
TIBCO Software EMEA
Published By: IBM APAC     Published Date: Oct 16, 2018
The latest IBM POWER9 Server is built for the most demanding, data-intensive, computing on earth with an enhanced core and chip architecture. It provides scalability and flexibility to handle changing customer needs while being cloud-ready with industry-leading reliability and performance. The POWER9 Systems server family has servers that are available for different workloads, IT environments or budget. You can choose from an array of server options that include: - POWER9 for Enterprise – scale-up - POWER9 for AIX & IBM I – scale-out - POWER9 for Linux - POWER9 for SAP HANA - POWER9 for Enterprise AI, Deep Learning & Machine Learning Find out more about these servers to meet the business needs of tomorrow.
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IBM APAC
Published By: Adobe     Published Date: Oct 24, 2018
Adobe automates the process of turning insights into action by connecting Adobe Analytics to other solutions in Adobe Experience Cloud, including Adobe Target and Adobe Audience Manager. Four features make this possible: • Anomaly detection. The technology automatically analyzes trends and determines if they are statistically significant — in milliseconds. • Analyze play button. With analytics, you can take insights and connect them to your email, DMP, and personalization platform in seconds. • Intelligent alert. A built-in alerting system sends an SMS text or email when it detects an anomaly. There are also predictive algorithms that help you forecast how often the alert is likely to trigger. You can set these to only notify you of the most important changes. • Intelligent recommendations. It’s simply impossible to manually create every alert you might need, so Adobe is building machine learning directly into analytics to analyze users’ behaviors. Like a virtual data assistant, it co
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Adobe
Published By: Entrust Datacard     Published Date: Mar 20, 2017
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
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Entrust Datacard
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: Box     Published Date: Jun 22, 2018
• Facing a myriad of challenges from digital transformation, business today are making big bets on the best collaboration tools they need on hand to meet those challenges. From employee buy-in, to machine-learning capabilities, to security, it's important to select a service with the right capabilities to further your business goals. The challenge, however, is that with so many services to choose from it can be difficult to figure out which one is the right fit for your business. • This eBook, 5 Considerations in Choosing a Collaboration Platform in the Digital Age, will walk you through the ins and outs of what to keep in mind as you choose the best collaboration platform for you.
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Box
Published By: Hewlett Packard Enterprise     Published Date: Mar 26, 2018
Business users expect immediate access to data, all the time and without interruption. But reality does not always meet expectations. IT leaders must constantly perform intricate forensic work to unravel the maze of issues that impact data delivery to applications. This performance gap between the data and the application creates a bottleneck that impacts productivity and ultimately damages a business’ ability to operate effectively. We term this the “app-data gap.”
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Jul 19, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: Top 5 causes of downtime and poor performance across the infrastructure stack How machine learning and predictive analytics can prevent issues Steps you can take to boost performance and availability"
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cloud, nimble storage, infrastructure
    
Hewlett Packard Enterprise
Published By: Oracle     Published Date: Jan 16, 2018
Download this webinar to learn about Machine Learning and how it can be applied to finance, and acquire basic fundamentals about how to begin the journey.
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Oracle
Published By: Dell EMC     Published Date: Oct 13, 2016
Flexibility is important, since many future initiatives—big data, machine learning, emerging technologies, and new business directions—will be built on this cloud structure. No matter what shape your cloud infrastructure takes, Dell EMC converged and hyper-converged platforms and innovations like Dell EMC VscaleTM Architecture, powered by Intel® Xeon® processors, deliver the pathways to scale-up and scale-out, today and tomorrow.
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emc, capex, opex, roi, hyper-converged platforms, network management, network performance
    
Dell EMC
Published By: Genesys     Published Date: Jun 06, 2017
In this ebook, learn: - Five trends will have the biggest impact on customer experience - How to use machine learning to detect patterns and trends to deliver the next great customer experiences - How to future-proof your contact center and adapt to changing customer needs
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genesys, customer experience, contact center solutions, contact center, customer needs
    
Genesys
Published By: Hewlett Packard Enterprise     Published Date: Sep 25, 2017
Infographic based on the InfoSight report.
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Sep 25, 2017
Every week InfoSight analyzes more than a trillion data points from more than 9,000 customers. How does this translate into true business value? By reducing your business risk with over Six-Nines of measured availability. By providing you with an infrastructure that gets “smarter” every single day. By empowering IT staff to focus on business priorities instead of mundane maintenance.
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Hewlett Packard Enterprise
Published By: SAS     Published Date: Jan 17, 2018
Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally. Learn more about key findings, including: Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics. Return on investment for analytics stems from the governing and sharing of data throughout the organization. Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.
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SAS
Published By: Pentaho     Published Date: Nov 04, 2015
Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.
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pentaho, analytics, platforms, hadoop, big data, predictive analytics, networking
    
Pentaho
Published By: Oracle     Published Date: Oct 20, 2017
What do these market-defining trends have in common? · Analytics for all · Analytics as competitive differentiator · Internet of Things · Artificial intelligence/Machine learning/Cognitive computing · Real-time analytics/event management They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise? It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i
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Oracle
Published By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Learn how predictive analytics and machine learning can help optimize application performance and meet the needs of the business with Nimble Storage Infosight. This ESG report highlights: • 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: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
"This research by Nimble Storage, a Hewlett Packard Enterprise Company, outlines the top five causes of application delays. The report analyzes more than 12,000 anonymized cases of downtime and slow performance. Read this report and find out: -Top 5 causes of downtime and poor performance across the infrastructure stack -How machine learning and predictive analytics can prevent issues -Steps you can take to boost performance and availability
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Hewlett Packard Enterprise
Published By: Hewlett Packard Enterprise     Published Date: Aug 23, 2018
Storage is normally the first suspect when identifying the causes of the App-Data Gap, but the facts tell a different story. Flash Alone Isn’t Enough. Infrastructure complexity makes it difficult to pinpoint the real problem, resulting in: • Extended downtime and frustration • Inefficient use of IT resources and budget • Long hours spent resolving cross-vendor issues
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Hewlett Packard Enterprise
Published By: CrowdStrike     Published Date: Aug 01, 2017
While many organizations are guarding the front door with yesterday’s signature-based antivirus (AV) solutions, today’s unknown malware walks out the back door with all their data. What’s the answer? A new white paper, “The Rise of Machine Learning in Cybersecurity,” explains machine learning (ML) technology —what it is, how it works and why it offers better protection against the sophisticated attacks that bypass standard security measures. You’ll also learn about CrowdStrike’s exclusive ML technology and how, as part of the Falcon platform’s next-gen AV solution,it dramatically increases your ability to detect attacks that use unknown malware. Download this white paper to learn:?How different types of ML are applied in various industries and why it’s such an effective tool against unknown malware?Why ML technologies differ and what factors can increase the accuracy and effectiveness of ML ?How CrowdStrike’s ML-based technology works as part of the Falcon platform’s next-generation AV
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CrowdStrike
Published By: Adobe     Published Date: Aug 30, 2017
Marketing leaders will find a host of new vendors in this year's Magic Quadrant for multichannel campaign management. Vendors are focused on integrating machine learning, personalization and ad tech capabilities into big data foundations for deeper customer engagement.
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Adobe
Published By: Oracle CX     Published Date: Oct 19, 2017
In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical. These challenges have dramatically changed the way that IT systems are architected, provisioned, and run compared to the past few decades. Most companies
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Oracle CX
Published By: Dell EMC & Intel     Published Date: Mar 16, 2018
A fundamental people-process-technology transformation enables businesses to remain competitive in today’s innovation economy. Initiatives such as advanced security, fraud detection services, connected consumer Internet of Things (IoT) devices, augmented or virtual reality experience, machine and deep learning, and cognitively enabled applications drive superior business outcomes such as predictive marketing and maintenance. Superior business outcomes require businesses to consider IT a core competency. For IT, an agile, elastic, and scalable IT infrastructure forms the crucial underpinning for a superior service delivery model. The more up to date the infrastructure, the more capable it is of supporting the scale and complexity of a changing application landscape. Current-generation applications must be supplemented and eventually supplanted with next-generation (also known as cloud-native) applications — each with very different infrastructure requirements. Keeping infrastructure up
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Dell EMC & Intel
Published By: Preempt     Published Date: Nov 02, 2018
Enterprises and the threats that target them have all fundamentally evolved over the past decade. In response, the security industry has generated an enormous amount of point solutions and technologies to try and keep pace. However, for all of this innovation and change, the underlying enforcement architecture has remained largely unchanged. Today the job of real-time policy enforcement and threat prevention still primarily falls to network firewalls and endpoint security products much as it has for the past 20 years. While essential for security, these technologies make very binary allow/block decisions based on a specific and often static event or metadata within a network session or suspicious file. On the other hand, many of the innovations in security such as machine-learning, AI and behavioral detection algorithms are often inconclusive, reactive, and limited to detection only. As a result, they feed into an increasingly overwhelmed incident response process that attempts to
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Preempt
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