machine learning

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Ovum "On the Radar: ClearStory Data" Report

Published By: ClearStory     Published Date: Oct 07, 2014
Organizations are more data hungry than ever. Thanks to advances in machine learning and semantic processing, they can now gain new insights from that data. ClearStory Data helps business users gain new insights into their markets and the environments in which they operate.
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data hungry, semantic processing, insight, market enviornment, data management, data center
    
ClearStory

IoT está habilitando una nueva era de valor para los accionistas en las empresas de energía y recurs

Published By: SAP SME     Published Date: Nov 02, 2017
La tecnología actual de IoT puede impulsar aún ás la innovación en las empresas de ENR. La disponibilidad de tecnología rentable basada en la nube, las analíticas y el machine learning ahora les permite a las empresas de ENR hacer mucho más con internet de las cosas (IoT).
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SAP SME

Outsmarting Malware: Why Machine Learning Bests Traditional AV

Published By: Juniper Networks     Published Date: Aug 07, 2017
Warum maschinelles Lernen entscheidend zur Cybersicherheit beiträgt
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Juniper Networks

Outsmarting Malware: Why Machine Learning Bests Traditional AV

Published By: Juniper Networks     Published Date: Aug 08, 2017
Pourquoi l’apprentissage automatique est essentiel pour la cybersécurité
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Juniper Networks

Machine Learning: The New Proving Ground for Competitive Advantage

Published By: Google     Published Date: Aug 09, 2017
The business world’s focus on machine learning (ML) may seem like an overnight development, but the buzz around this technology has been steadily growing since the early days of big data.
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machine learning, big data, analytics, data analytics
    
Google

Five Tech Trends That Can Transform How Financial Institutions Detect and Prevent Financial Crime

Published By: Fiserv     Published Date: Nov 09, 2017
Financial institutions seeking to attract new customers and revenue channels are expanding into digital services, real-time payments and global transactions. However, with every new service, criminals are developing innovative ways to infiltrate financial systems, and older technologies that mitigate fraud no longer work as effectively. So how can financial institutions respond to this growing threat? Fortunately, more advanced technologies hold great potential for real-time financial crime mitigation. Learn about five current and emerging technologies that could impact money laundering and fraud mitigation, including artificial intelligence/machine learning, blockchain, biometrics, predictive analytics (hybrid model) and APIs. Read the latest Fiserv white paper: Five Tech Trends That Can Transform How Financial Institutions Detect and Prevent Financial Crime.
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kyc, know your customer, beneficial ownership, financial crime, financial crimes, compliance, enhanced due diligence, suspicious activity report, currency transaction report, aml directive, anti-money laundering laws
    
Fiserv

2018 Outlook: Customer Experience and Security Strike a Balance

Published By: Fiserv     Published Date: Jan 16, 2018
For the past decade, financial institutions have created sophisticated digital platforms for consumers to access, save, share and interact with their financial accounts. As sophisticated as these digital platforms have become, cyber criminals continue to pose an ever-present risk for everyone – from individual consumers to large corporations In his recent article, 2018 Outlook: Customer Experience and Security Strike a Balance, Andrew Davies, vice president of global market strategy for Fiserv’s Financial Crime Risk Management division, explains how and why security will become a key differentiator for financial institutions as they respond to a changing landscape, which includes: •Global payment initiatives •Open Banking standards •Artificial intelligence and machine learning •Consumer demand for real-time fraud prevention and detection
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2018 trends, aml trends, money laundering trends
    
Fiserv

A Beginner's Guide to collectd

Published By: Splunk     Published Date: Sep 10, 2018
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable. Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
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it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
    
Splunk

Predictive IT: How Leading Organizations use AI to Deliver Exceptional Customer Experiences

Published By: Splunk     Published Date: Nov 29, 2018
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences. Download the e-book to learn how: Micron Technology reduced number of IT incidents by more than 50% Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk

Analyst Report: From Reactive to Predictive: 5 Steps to Transform your IT Organization with AI

Published By: Splunk     Published Date: Dec 11, 2018
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences. Download this executive brief from CIO to learn: 5 steps to an effective predictive IT strategy Where AI can help, and where it can’t How to drive revenue and exceptional customer experiences with predictive analytics
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predictive it, predictive it tools, predictive analytics for it, big data and predictive analytics
    
Splunk

Advancing Analytics: The Path Forward for Finance Leaders

Published By: Workday APAC     Published Date: May 08, 2019
As your organization’s finance leader, the opportunity to better understand the landscape and your business has never been greater. Advances in analytics—powered by digital technologies, such as automation and machine learning—give finance teams deeper business insights. Read the story.
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Workday APAC

The Data-Driven Approach to Sales Performance Management

Published By: Beqom     Published Date: Jun 14, 2019
New Techniques That Will Drive Revenue in 2019 If you’re ready to move beyond simple calculations and realize the vast potential of data driven selling, you’re ready to explore the next generation of SPM platforms. Download the report to learn how the modern technologies like Artificial Intelligence and Machine Learning, can give your sales reps a roadmap to better performance and give sales management insights that will enable them to achieve more profitable sales.
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Beqom

GFT Stream: Use-Cases Across Capital Markets, Retail, and Insurance Business Segments

Published By: GFT USA, Inc.     Published Date: Jun 26, 2019
Stream is GFT’s architectural framework on GCP that enables real time processing and analysis of structured and unstructured data using AI and Machine Learning (ML) to extract intelligence from data.
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GFT USA, Inc.

Machine Learning 101

Published By: IBM APAC     Published Date: May 14, 2019
Machine Learning For Dummies, IBM Limited Edition, gives you insights into what machine learning is all about and how it can impact the way you can weaponize data to gain unimaginable insights. Your data is only as good as what you do with it and how you manage it. In this book, you discover types of machine learning techniques, models, and algorithms that can help achieve results for your company. This information helps both business and technical leaders learn how to apply machine learning to anticipate and predict the future. You will find topics like: - What is machine learning? - Explaining the business imperative - The key machine learning algorithms - Skills for your data science team - How businesses are using machine learning - The future of machine learning
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IBM APAC

Smart Factory Applications in Discrete Manufacturing

Published By: Cisco     Published Date: Sep 27, 2018
As the world of traditional manufacturing fuses with information technology, organizations are tapping into a level of technical orchestration never attainable before. Symphonies of systems facilitate real - time interactions of people, machines, assets, systems, and things. This is the Smart Factory; the factory ecosystem of the future. It is an application of the Industrial Internet of Things (IIoT) built with sets of hardware and software that collectively enable processes to govern themselves through machine learning and cognitive computing
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Cisco

Digital transformation in manufacturing: The CIO’s approach

Published By: Infor     Published Date: Mar 03, 2017
Analysts and industry experts agree: Digital disruption in manufacturing is on the horizon. Technologies like the Internet of Things, dynamic enterprise management, global supply chain visibility, and machine learning are already changing the way manufacturers produce goods and interact with customers. Further changes will continue to intensify issues and reveal opportunities.
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cio, finance, digital, manufacturing, enterprise, enterprise applications
    
Infor

Digital transformation in manufacturing: The CFO’s approach

Published By: Infor     Published Date: Mar 03, 2017
Analysts and industry experts agree: Digital disruption in manufacturing is on the horizon. Technologies like the Internet of Things, dynamic enterprise management, global supply chain visibility, and machine learning are already changing the way manufacturers produce goods and interact with customers. Further changes will continue to intensify issues and reveal opportunities.
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cfo, finance, digital, manufacturing, enterprise, enterprise applications
    
Infor

Accelerate Deep Learning With a Modern Data Platform

Published By: Pure Storage     Published Date: Oct 09, 2018
Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data.
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Pure Storage

AI and Machine Learning with Workforce Management

Published By: Nice Systems     Published Date: Feb 26, 2019
NICE has made a significant investment into AI and ML techniques that are embedded into its core workforce management solution, NICE WFM. Recent advancements include learning models that find hidden patterns in the historical data used to generate forecasts for volume and work time. NICE WFM also has an AI tool that determines, from a series of more than 40 models, which single model will produce the best results for each work type being forecasted. NICE has also included machine learning in its scheduling processes which are discussed at length in the white paper.
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Nice Systems

Survey Report: Data Integration Reaches Inflection Point

Published By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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Group M_IBM Q2'19

CMOs Know Innovation Means Business Power

Published By: Oracle     Published Date: Mar 01, 2019
Join Oracle’s CX and Marketing Strategy Director, Wendy Hogan, and Senior Vice President Oracle Marketing, Shashi Seth, as they tell how AI, machine learning and data science can engage customers, automate tasks and build ROI. Reaching the right customers on the right channel at the right time, brings rewards for CMOs who embrace these innovations, including engaged customers and increased ROI. Be inspired by the new-generation AI, machine learning and data science and take your marketing to the next level. Watch the webinar.
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Oracle

Differentiating for Success: A Guide for Cloud Service Providers

Published By: Intel     Published Date: Apr 16, 2019
Gartner predicts that the public cloud market will surpass USD 300 billion by 2021 . With the big players (Amazon, Google, Microsoft and IBM) taking home 63 percent of the market share , how will next wave CSPs stand out from the crowd? Download Intel's latest whitepaper, Differentiating for Success: A Guide for Cloud Service Providers' to discover how to offer unique services, including: - Providing workload-specific optimizations, for example machine learning or high-performance computing - Targeting a particular geographical area - Focusing on an industry, such as financial services - Delivering emerging technology, such as virtual reality, in-memory databases, and containerization
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Intel

The Democratization of Machine Learning

Published By: IBM APAC     Published Date: Aug 25, 2017
Machine learning automates the development of analytic models that can learn and make predictions on data. It has been one of the fastest growing disciplines within the world of statistics and data science, but the barrier to entry has been high, not only in cost, but also in the need for specialized talent.
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machine learning, apache spark, additional resources, big data, ibm
    
IBM APAC

Guardians of trust: how to build trust in the analytics powering new technologies

Published By: KPMG     Published Date: Jul 10, 2018
As organisations increasingly leverage data, sophisticated analytics, robotics and AI in their operations, we ask who should be responsible for trusted analytics and what good governance looks like. Read this report to discover: • the four key anchors underpinning trust in analytics – and how to measure them • new risks emerging as the use of machine learning and AI increases • how to build governance of AI into core business processes • eight areas of essential controls for trusted data and analytics.
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KPMG

Guardians of trust: How to build trust in the analytics powering new technologies

Published By: KPMG     Published Date: Jul 11, 2018
As organisations increasingly leverage data, sophisticated analytics, robotics and AI in their operations, we ask who should be responsible for trusted analytics and what good governance look like? Read this report to discover: • the four key anchors underpinning trust in analytics – and how to measure them • new risks emerging as the use of machine learning and AI increases • how to build governance of AI into core business processes • eight areas of essential controls for trusted data and analytics. Download the report now:
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KPMG
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