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Published By: TIBCO Software     Published Date: Jul 22, 2019
What if you could use just one platform to detect all types of major financial crimes? One platform to handle the analytical tasks of fraud detection, including: Data processing and aggregation Data visualization Statistical/mathematical/machine learning modeling Batch/real-time scoring One platform that could successfully reduce complex and time-consuming fraud investigations by combining extremely different domains of knowledge including Business, Economics, Finance, and Law. A platform that can cover payments, credit card transactions, and know your customer (KYC) processes, as well as similar use cases like anti-money laundering (AML), trade surveillance, and crimes such as insurance claims fraud. Learn more about TIBCO's comprehensive software capabilities behind tackling all these types of fraud in this in depth whitepaper.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
FINANCIAL SERVICES’ HISTORY OF DISRUPTION Financial Services is an industry driven by disruption. Transformative business models such as low-cost brokerages, innovative investment products like ETFs, and the huge regulatory mandates like Gramm-Leach-Bliley are but a few examples. Here are some others: • New fintech firms such as a recent nine billion dollar investment in Ant Financial Services Group and myriad other venture capital-led fintech startups targeting well established segments across the financial services industry • Robo-advisor services powered by artificial intelligence and machine learning intermediating financial advisors and portfolio managers alike • Ever changing regulatory and risk management mandates, such as GDPR, Basel III, and Open Banking, transforming customer engagement and capital allocation Read this whitepaper to learn how you can overcome these and other disruptions.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
TIBCO® Connected Intelligence for Smart Factory Insights 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.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
Today, you can improve product quality and gain better control of the entire manufacturing chain with data virtualization, machine learning, and advanced data analytics. With all relevant data aggregated, analyzed, and acted on, sensors, devices, people, and processes become part of a connected Smart Factory ecosystem providing: •? Increased uptime, reduced downtime •? Minimized surplus and defects •? Better yields •? Reduced cost due to better quality •? Fewer deviations and less non-conformance
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
Over the past decade there has been a major transformation in the manufacturing industry. Data has enabled a paradigm shift, with real-time IoT sensor data and machine learning algorithms delivering new insights for process and product optimization. Smart Manufacturing, also known as Industry 4.0, has laid the groundwork for the next industrial revolution. Using a smart factory system, all relevant data is aggregated, analyzed, and acted upon. We call this Manufacturing Intelligence, which gives decision-makers a competitive edge to: Digitize the business Optimize costs Accelerate innovation Survive digital disruption Watch this webinar to understand use cases and their underlying technology that helped our customers become smart manufacturers.
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
The Insurance industry continues to undergo significant transformation, with new technologies, business models, and competitors entering the market at an increasing rate. To be successful in attracting and retaining the most valuable customers, insurance companies must innovate and increase the speed at which they respond to customer demands. Traditionally, the insurance software market was dominated by a handful of specialist vendors with products that were initially expensive, difficult to deploy, costly to maintain, and did not provide the speed needed for today’s market. Now there has been a shift away from these “black box” applications to platforms that allow insurers to make their algorithmic IP available to business users, allowing much faster response to business demands. The algorithmic platform approach also comes at a fraction of the cost of black box solutions, while delivering advanced analytical techniques like Machine Learning and Artificial Intelligence (AI).
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TIBCO Software
Published By: TIBCO Software     Published Date: Jul 22, 2019
On-demand Webinar The current trend in manufacturing is towards tailor-made products in smaller lots with shorter delivery times. This change may lead to frequent production modifications resulting in increased machine downtime, higher production cost, product waste—and the need to rework faulty products. Watch this webinar to learn how TIBCO’s Smart Manufacturing solutions can help you overcome these challenges. You will also see a demonstration of TIBCO technology in action around improving yield and optimizing processes while also saving costs. What You Will Learn: Applying advanced analytics & machine learning / AI techniques to optimize complex manufacturing processes How multi-variate statistical process control can help to detect deviations from a baseline How to monitor in real time the OEE and produce a 360 view of your factory The webinar also highlights customer case studies from our clients who have already successfully implemented process optimization models. Spe
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TIBCO Software
Published By: Ruckus Wireless     Published Date: Jul 16, 2018
Students and teachers at Belleville Township High School District now rely on Ruckus Networks to stay connected to laptops, tablets, and smartphones. With Ruckus Cloud Wi-Fi, the IT team at Belleville Township High School District is able to access and manage WLANs with a click of a button. Read this case study to learn why they chose Ruckus Cloud Wi-Fi, allowing Belleville to take classroom learning to the next level.
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Ruckus Wireless
Published By: Group M_IBM Q119     Published Date: Dec 18, 2018
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
IBM Cloud Private for Data is an integrated data science, data engineering and app building platform built on top of IBM Cloud Private (ICP). The latter is intended to a) provide all the benefits of cloud computing but inside your firewall and b) provide a stepping-stone, should you want one, to broader (public) cloud deployments. Further, ICP has a micro-services architecture, which has additional benefits, which we will discuss. Going beyond this, ICP for Data itself is intended to provide an environment that will make it easier to implement datadriven processes and operations and, more particularly, to support both the development of AI and machine learning capabilities, and their deployment. This last point is important because there can easily be a disconnect Executive summary between data scientists (who often work for business departments) and the people (usually IT) who need to operationalise the work of those data scientists
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 03, 2019
In our 29-criteria evaluation of machine learning data catalogs (MLDCs) providers, we identified the 12 most significant ones — Alation, Cambridge Semantics, Cloudera, Collibra, Hortonworks, IBM, Infogix, Informatica, Oracle, Reltio, Unifi Software, and Waterline Data — and researched, analyzed, and scored them. This report shows how each provider measures up and helps enterprise architecture (EA) professionals make the right choice.
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Group M_IBM Q2'19
Published By: Mist Systems     Published Date: Jun 19, 2019
Today’s digital classrooms need amazing wireless networks that are predictable, reliable and measurable. By choosing the Mist Learning WLAN, Guilford College graduated to a modern cloud platform that uses AI to automate daily Wi-Fi operations, simplify troubleshooting, and most importantly ensure every student has a great mobile experience.
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Mist Systems
Published By: IBM     Published Date: Jun 25, 2018
Recognizing the shift to a subscription business model required real-time customer support, Autodesk turned to IBM technology to enhance its customer experience. Using Watson Assistant, Autodesk developed a virtual agent to interact with customers, applying natural language processing (NLP) and deep learning techniques to recognize and extract the intent, context and meaning behind inquiries. Quickly resolving easy customer concerns, Watson Assistant is supporting 100,000 conversations per month, with response times 99% faster than before and leading to a 10-point increase in customer satisfaction levels for Autodesk. Find out how Watson Assistant can accelerate your customer support experience. Click here to find out more about how embedding IBM technologies can accelerate your solutions’ time to market.
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IBM
Published By: Selligent Marketing Cloud     Published Date: Mar 07, 2018
Both are fueled by a drive for progress, for pushing boundaries and advancing the status quo. In these fields, new trends are like a currency. Keeping ahead of the next big trend means being aware of the next big seller and allocating all the right resources – fashion design, manufacturing, and marketing – for maximum impact. Miss the hype and the next fashion season is bound to hurt the bottom line. New trends are also important to marketers because owning a new trend is a way to differentiate in today’s fast-moving digital landscape. It’s a way to stand out from the pack by investing strategically in the right approaches and technologies at the right time, then reaping the benefits organically by leading where others follow. Naturally, making these decisions requires a bit of trial and error. Nobody has a magic crystal ball that guarantees success. But as a rule of thumb, the companies winning in digital marketing are the ones willing to adopt new technologies while keeping an sharp.
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2018, marketing trends, omnichannel, multichannel, automation, loyalty, crm, marketing
    
Selligent Marketing Cloud
Published By: Selligent Marketing Cloud     Published Date: Mar 07, 2018
What does it take to be relevant today? In the era of hyper-connectivity, consumers have become entitled, demanding more control over their experiences and expecting that marketers use data and insights to create a seamless, relevant brand experience. Research shows that communications containing relevant information and offers are the best drivers of brand loyalty and conversions
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insight marketing, customer engagement, omnichannel, multichannel, automation, loyalty, crm, marketing
    
Selligent Marketing Cloud
Published By: Selligent Marketing Cloud     Published Date: Mar 07, 2018
Context can make or break the communication – and, ultimately, the relationship – between a consumer and a brand. Today’s consumers expect relevant communications that speak directly to their needs in the moment. We have the technology today to deliver such messages – but there are significant barriers to developing relevant, contextual programs of this kind. Some of the development challenges represent new versions of old challenges. Take data as an example: it has always been hard to harness data from different sources and to leverage insights in real time. But today, there are additional opportunities – if not expectations – for marketers to use contextual data to better reach and engage customers through the optimal channel(s).
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data driven marketing, contextual marketing, cmo, omnichannel, multichannel, automation, loyalty, crm
    
Selligent Marketing Cloud
Published By: Amazon Web Services     Published Date: Feb 01, 2018
At Amazon, we’ve been investing deeply in AI for more than 20 years. Machine learning (ML) algorithms drive many of our internal systems, and have formed the core of our customers' experience —from the path optimization in our fulfillment centers, and Amazon.com’s recommendations engine, to Echo powered by Alexa, and our new retail experience, Amazon Go. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every executive, developer, and data scientist.
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machine learning, algorithms, interal systems, amazon
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Feb 01, 2018
Machine learning is proving its power across virtually every industry in ways that add actionable insight and efficiency. But one can look at the rise of this transformative paradigm with a more focused lens to see AI technologies as a business tool of the highest order, one that improves processes and inspires new models. AI, in other words, has a big role to play on the balance sheet. Two leading brands in very different spaces — Capital One in financial services, John Deere in agriculture — are seeing efforts that stretch back decades come to fruition with the launch of cloud-based AI platforms. Capital One is developing digital products and experiences using machine learning to help millions of customers with their financial lives; John Deere’s Precision Agriculture solution helps farmers gain precise information about their machines and crops. In both instances, AI and a cloud platform combine to enable transformation.
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digital, technologies, optimization, amazon
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Feb 01, 2018
Moving Beyond Traditional Decision Support Future-proofing a business has never been more challenging. Customer preferences turn on a dime, and their expectations for service and support continue to rise. At the same time, the data lifeblood that flows through a typical organization is more vast, diverse, and complex than ever before. More companies today are looking to expand beyond traditional means of decision support, and are exploring how AI can help them find and manage the “unknown unknowns” in our fast-paced business environment.
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predictive, analytics, data lake, infrastructure, natural language processing, amazon
    
Amazon Web Services
Published By: HP     Published Date: Jul 03, 2014
A Viewpoint paper on learning how your enterprise can become mobile
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enterprise mobility, mobile workers, mobile devices, byod
    
HP
Published By: Datarobot     Published Date: May 14, 2018
The DataRobot automated machine learning platform captures the knowledge, experience, and best practices of the world’s leading data scientists to deliver unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users of all skill levels, from business people to analysts to data scientists, to build and deploy highly-accurate predictive models in a fraction of the time of traditional modeling methods
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Datarobot
Published By: Datarobot     Published Date: May 14, 2018
Organizations across industries look to technology, not only as a way to run their operations more smoothly, but as a way to gain competitive advantage. Artificial Intelligence (AI) and machine learning have transformed the businesses that are aggressively adopting these technologies, allowing them to systematically solve business problems faster and more effectively.
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Datarobot
Published By: Oracle     Published Date: Jun 04, 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
Published By: Lumesse     Published Date: Feb 13, 2015
This White Paper provides information on how Technological advance is powering a motivational disconnect between what Gen Y/Millenial employees can achieve when it comes to learning and development (L&D).
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gen y, l&d, millenial employees, generation y, l&d in a digital landscape, learning and development
    
Lumesse
Published By: SAS     Published Date: May 24, 2018
This paper provides an introduction to deep learning, its applications and how SAS supports the creation of deep learning models. It is geared toward a data scientist and includes a step-by-step overview of how to build a deep learning model using deep learning methods developed by SAS. You’ll then be ready to experiment with these methods in SAS Visual Data Mining and Machine Learning. See page 12 for more information on how to access a free software trial. Deep learning is a type of machine learning that trains a computer to perform humanlike tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. Deep learning is used strategically in many industries.
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SAS
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