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Published By: IBM     Published Date: Jun 04, 2018
"The appearance of your reports and dashboards – the actual visual appearance of your data analysis -- is important. An ugly or confusing report may be dismissed, even though it contains valuable insights about your data. Cognos Analytics has a long track record of high quality analytic insight, and now, we added a lot of new capabilities designed to help even novice users quickly and easily produce great-looking and consumable reports you can trust. Watch this webinar to learn: • How you can more effectively communicate with data. • What constitutes an intuitive and highly navigable report • How take advantage of some of the new capabilities in Cognos Analytics to create reports that are more compelling and understandable in less time. • Some of the new and exciting capabilities coming to Cognos Analytics in 2018 (hint: more intelligent capabilities with enhancements to Natural Language Processing, data discovery and Machine Learning)."
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data analysis, data analytics, dashboards
    
IBM
Published By: IBM     Published Date: Jul 02, 2018
After several years of relentless hardware and software innovation, the mainframe is at an inflection point from being a supporting platform of transaction revenue to becoming a source of revenue growth and innovation. Organizations are evolving toward what IDC calls the “connected mainframe.” The platform is transforming from a revenue-supporting machine into a revenue-generating machine and is increasingly playing a central role in organizations’ digital transformation (DX) journey. Key steps in achieving the connected mainframe require organizations to modernize and integrate the platform with their internal and external environments. IDC finds that these modernization and integration initiatives lead to new business innovations, which in turn are driving revenue growth and improving organizational operational efficiency.
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IBM
Published By: IBM     Published Date: Jul 05, 2018
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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IBM
Published By: LogMeIn     Published Date: Feb 27, 2018
When Facebook released their bot feature, M, the virtual assistant living inside their Messenger platform, it was billed as the next generation of how people connect and interact with the internet. Since then, over 18,000 companies have created their own branded chatbots with the help of Facebook’s platform. Never ones to miss out on a trend, Microsoft, Google and Apple have all been hard at work developing their own integrated chatbot features. Brands of all shapes and sizes, from American Express to 1800-Flowers to Domino’s Pizza, all have their own chatbots, proving the versatility of the concept. As Microsoft CEO Satya Nadella said at the 2016 Build conference, “As an industry, we are on the cusp of a new frontier that pairs the power of natural human language with advanced machine intelligence.”
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LogMeIn
Published By: Oracle     Published Date: Sep 21, 2018
In a connected world content becomes the nucleus of business growth. Oracle provides scalable, secure solutions to help drive an organization’s digitalization efforts maximizing operation automation, machine learning, and cloud services.
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Oracle
Published By: Oracle     Published Date: Sep 21, 2018
Agility and speed are required in the cloud economy. Modernize data warehouses with built-in adaptive machine learning to eliminate manual labor for administrative tasks. With Oracle, businesses can now build data warehouses or data marts in minutes.
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Oracle
Published By: Oracle     Published Date: Mar 08, 2019
Did you know that organizations with advanced finance teams are more likely to have a compelling digital customer experience? The driver behind this trend? A digital, customer-first way of working with greater investment in talent, innovation, and advanced technologies such as artificial intelligence (AI) and machine learning (ML). While finance has long taken advantage of technology to help drive productivity and collaboration, the goalposts have recently moved. Today’s organizations must adopt an agile finance operating model— powered by emerging digital technologies and skillsets—to better support the demands of an economy driven by continuous innovation.
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Oracle
Published By: Oracle     Published Date: Apr 26, 2019
Hyperion Infographic: Cloud-based EPM solutions deliver greater agility and efficiency, at a lower cost—which is why hundreds of Hyperion customers are upgrading to Oracle EPM Cloud. New technologies are changing how finance operates… AI, machine learning, chatbots, process automation, and more. When you migrate to a cloud-based EPM solution, you can access these features and functionality to gain greater efficiencies and improve the quality of decision-making.
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Oracle
Published By: TIBCO Software     Published Date: Aug 13, 2018
The combination of legislation, market dynamics, and increasingly sophisticated risk management strategies requires you to be proactive in detecting risks like fraud quicker and more effectively. Dynamic detection systems need to adapt to evolving compliance regulations, scale to deal with growing transaction volumes, detect sophisticated risk specific patterns, and reduce false-positives. TIBCO's Risk Management Accelerator uses a combination of predictive analytics, streaming analytics, and business process management to deliver a powerful and cost-effective system for detecting anomalies. Download this solution brief to learn more.
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TIBCO Software
Published By: TIBCO Software     Published Date: Feb 14, 2019
With the new TIBCO Spotfire® A(X) Experience, we are revolutionizing analytics and business intelligence. This new platform accelerates the personal and enterprise analytics experience so you can get from data to insights in the fastest possible way. With the fusion of technology enablers like machine learning, artificial intelligence, and natural language search, the Spotfire® X platform redefines what’s possible for analytics and business intelligence, simplifying for everyone how data and insights are generated, consumed, and acted on. Download this whitepaper to learn more, then check out the new Spotfire analytics. It’s unlike anything you have ever seen. Simple, yet powerful, it changes everything.
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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
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: CheckMarx     Published Date: Jun 07, 2019
Artificial Intelligence (AI) software is everywhere being leveraged by many industries such as healthcare, fintech, and e-commerce. But how does AI impact the security space? Join Maty Siman, Checkmarx Founder and CTO, to get both a white hat and black hat perspective to AI and security.
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CheckMarx
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: Group M_IBM Q3'19     Published Date: Aug 21, 2019
Artificial intelligence (AI), including machine learning and deep learning, is set to become one of the most transformational technologies in the history of the world, affecting most aspects of our lives whether we’re conscious of it or not. The application of these technologies will likely reshape how people work, study, travel, govern, consume and pursue leisure activities.
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Group M_IBM Q3'19
Published By: Group M_IBM Q4'19     Published Date: Sep 27, 2019
Data quality tools are vital for digital business transformation, especially now that many have emerging features like automation, machine learning, business-centric workflows and cloud deployment models. This Magic Quadrant assesses 15 vendors to help you make the best choice for your organization.
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Group M_IBM Q4'19
Published By: Infinidat EMEA     Published Date: Oct 10, 2019
Le Big Data et les charges analytiques constituent une nouvelle frontière pour les entreprises. Les données collectées émanent de sources inexistantes il y a 10 ans. Les données des smartphones, celles générées par des machines et par les interactions avec les sites web sont collectées et analysées. De plus, dans un contexte où les budgets IT sont déjà sous pression, les empreintes Big Data s’étendent et posent d’énormes problèmes de stockage. Ce livre blanc délivre des informations sur les problématiques liées aux applications Big Data pour les systèmes de stockage et explique en quoi le choix de la bonne infrastructure de stockage peut rationaliser et consolider les applications d’analyse du Big Data sans faire sauter la banque.
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Infinidat EMEA
Published By: ConnectWise     Published Date: Aug 22, 2019
Profits are the name of the game for a lot of technology solution providers, but keeping them coming in the door isn’t always simple. Building a solid foundation starts with a strong, efficient sales team. This eBook helps outline the five keys to creating and maintaining a well-oiled sales machine that allows you to bring in more business and encourage recurring revenue from your existing clients.
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ConnectWise
Published By: SDL     Published Date: Sep 20, 2019
Component Content Management: A New Paradigm in Intelligent Content Services While technology has changed the world, the way that companies manage information has inherently stayed the same. The advent of near-ubiquitous connectivity among applications and machines has resulted in a data deluge that will fundamentally alter the landscape of content management. From mobile devices to intelligent machines, the volume and sophistication of data have surpassed the ability of humans to manage it with outdated methods of collection, processing, storage, and analysis. The opportunity afforded by the advent of artificial intelligence (AI) has stimulated the market to search for a better way to capture, classify, and analyze this data in its journey to digital transformation (DX). The paradigm of document-based information management has proven to be a challenge in finding, reusing, protecting, and extracting value from data in real time. Legacy systems may struggle with fragmented information
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SDL
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: Microsoft     Published Date: Feb 15, 2017
Read this e-Book to find out how Azure Virtual Machines can deliver more productivity and help companies control their own budget decisions, infrastructure and in turn, their own destinies.
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cloud, iaas, infrastructure as a service, smb's, infrastructure, productivity, azure, digital transformation
    
Microsoft
Published By: Commvault ABM Oct     Published Date: Jul 17, 2019
Your goal is high availability for the applications, databases, virtual machines (VMs), servers, and data that run your business. When access is lost or interrupted, recovery speed is critical, and must be measured in minutes and seconds, not hours of days. And if your backup and recovery strategy includes point solutions with limited coverage, legacy approaches that don't support today's modern technologies, or manual proc cesses that are time-consuming and complex, you may not be ready when disaster strikes.
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Commvault ABM Oct
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