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Published By: Dassault Systèmes     Published Date: Nov 12, 2019
The Life Sciences industry has changed significantly over the past 10 years. With a view to developing new, more effective treatments, industry leaders are exploring new therapeutic areas and approaches like biologics and precision medicine. To address this shift, pharmaceutical and medical devices manufacturers look to connect systems, people and data - characterized by more predictive and adoptive facilities that leverage machine learning, 3D modeling, Industrial Internet of Things (IIOT), digital twin, and augmented reality. This eBook explains the main challenges of manufacturing and explores 5 manufacturing experiences that disrupt the future of manufacturing in the Life Sciences industry.
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iiot, medical device, life sciences, machine learning, 3d modeling, digital twin
    
Dassault Systèmes
Published By: Dassault Systèmes     Published Date: Nov 12, 2019
The Life Sciences industry has changed significantly over the past 10 years. With a view to developing new, more effective treatments, industry leaders are exploring new therapeutic areas and approaches like biologics and precision medicine. To address this shift, pharmaceutical and medical devices manufacturers look to connect systems, people and data - characterized by more predictive and adoptive facilities that leverage machine learning, 3D modeling, Industrial Internet of Things (IIOT), digital twin, and augmented reality. This eBook explains the main challenges of manufacturing and explores 5 manufacturing experiences that disrupt the future of manufacturing in the Life Sciences industry.
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Dassault Systèmes
Published By: Dassault Systèmes     Published Date: Nov 11, 2019
Die meisten Unternehmen nutzen eine einfache Form der Analyse: deskriptive Analytik. Diese betrachtet lediglich die Vergangenheit. Um wirklich wettbewerbsfähig zu bleiben, müssen Sie jedoch weitergehen. Gehen Sie den nächsten Schritt mit einer Supply-Chain, die intuitiv anhand der Realität Ihres Unternehmens lernt und so ein Maß an Präzision und Erkenntnis bietet das früher für unmöglch gehalten wurde. In unserem Leitfaden zur selbstlernenden Supply-Chain, erfahren Sie wie Sie mit Hilfe von Advanced Analytics: • Daten kontinuierlich erfassen, analysieren und aktualisieren können, um größtmögliche Genauigkeit zu erreichen • Intelligente und souveräne Entscheidungen für jeden Schritt in Ihrer Supply-Chain treffen können • Entscheidungen dreimal so effektiv umsetzen können
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advanced analytics, deskriptive analytik, predictive analytics, big data, selbstlernende supply-chain, optimierung, planung, wettbewerbsvorteil
    
Dassault Systèmes
Published By: SAS     Published Date: Nov 08, 2019
As organizations continue to adopt predictive analytics, many are struggling to make it stick. Challenges include skills, executive and organizational support, and data infrastructure issues. Many organizations have not considered how to practically put analytics to work, given the organizational, technology, process, and deployment issues they face. Addressing these issues involves a combination of traditional and new technologies and practices. Some practical considerations highlighted in this report include: Model Development, Infrastructure and Operational Process.
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SAS
Published By: KPMG     Published Date: Nov 06, 2019
Successful supply chain organisations of the future will adopt a technology-enabled, data-powered, insight-driven approach, and invest in recruiting top talent. If yesterday’s supply chains were rigid and reactive, tomorrow’s supply chains will be nimble and predictive. Begin now to jump start your supply chain transformation journey. Read the following article to explore these key insights: • Putting the customer first • Utilising platforms correctly • Winning the war for talent • Investing in future-ready capabilities • Leveraging cross-functional data • Exploiting micro supply chains.
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KPMG
Published By: Intapp     Published Date: Nov 01, 2019
Chief Marketing Officers who modernize business development strategies can accelerate revenue and market share growth with both new and existing clients. This requires unifying data across the entire client lifecycle, making that data transparent, and developing insights that drive better decision making across the board. How much of an impact can this modern approach make? According to a recent study conducted by ALM Legal Intelligence and Calibrate Legal, the investment pays off with Am Law 200 firms seeing an average return of $47 million on $1 million of marketing and business development spending. Download this point of view to learn what it takes to transform today’s law firm marketing from reactive to predictive. Topics include: Winning business with data-driven insights CMOs as change agents The data divide Smart collaboration in action: Key-client planning The pivot: From reactive to predictive
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Intapp
Published By: HERE Technologies     Published Date: Sep 23, 2019
It’s time to move your supply chain into the realm of super-intelligent. This special report is for anyone looking to enhance their supply chain operations by utilizing the latest in technological advances such as artificial intelligence (AI), machine learning and the Internet of Things (IoT). With smart use of these tools, businesses can anticipate problems and develop solutions before they occur. Forward-thinking leaders are using this disruption to optimize their supply chains and push the quality of their findings to a whole new level. In it, you’ll learn: • The markers of a truly cognitive supply chain • The crucial role of location intelligence in supply chain optimization • The impact increased visibility has on every area of your supply chain, including asset, inventory, fleet and energy management
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HERE Technologies
Published By: Pure Storage     Published Date: Sep 13, 2019
Discover how to revolutionize processing performance, data intelligence, customer experiences, and GRC. The future of financial services will belong to those who can capture and capitalize on data. And it all begins with employing modern data strategies in four critical areas. Description You’ll learn how to: Leverage AI, machine learning and predictive analytics. Get scalable, high-speed access to vast amounts of data. Respond faster, become more competitive, and attract new customers.
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Pure Storage
Published By: MicroStrategy     Published Date: Aug 21, 2019
To survive and thrive in an era of accelerating digital disruption, organizations require accessible data, actionable insights, continuous innovation, and disruptive business models. It’s no longer enough to prioritize and implement analytics – leaders are being challenged to stop doing analytics just for analytics’ sake and focus on defined business outcomes. In addition, these leaders are being challenged to bring predictive capabilities and even prescriptive recommended actions into production at scale. As AI and accelerated growth and transformation become top of mind, many enterprises are realizing that their current segmented analytics approach isn’t built to last, and that real transformation will require proper endto- end data management, data security, and a data processing platform company-wide. The year 2019 will be a turning point for many organizations that realize being data-driven doesn’t guarantee future success.
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MicroStrategy
Published By: TIBCO Software     Published Date: Aug 20, 2019
The oil field is being dynamically transformed through the connective power of the Internet, the advancements in remote connected sensors, and the possibilities of machine learning and artificial intelligence (AI). As the quest for hydrocarbons and alternative energy sources extends into deeper and harsher environments, operators, service companies, and asset owners are leveraging technology advancements to ensure their employees are safer, their fields are more productive, and their capital assets are operating at peak efficiency.
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machine learning, predictive analytics, hydrocarbons, oil&gas, cybersecurity, asset efficiency, safety
    
TIBCO Software
Published By: TIBCO Software     Published Date: Aug 20, 2019
“How will we use all the data from the smart grid?”
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greater efficiency, demand forecasting, advanced analytics, smart meters, predictive analytics, data security
    
TIBCO Software
Published By: TIBCO Software     Published Date: Aug 02, 2019
A perfect storm of legislation, market dynamics, and increasingly sophisticated fraud strategies requires you to be proactive in detecting fraud quicker and more effectively. TIBCO’s Fraud Management Platform allows you to meet ever-increasing requirements faster than traditional in-house development, easier than off-the-shelf systems, and with more control because you’re in charge of priorities, not a vendor. All this is achieved using a single engine that can combine traditional rules with newer predictive analytics models. In this webinar you will learn: Why a fraud management platform is necessary How to gain an understanding of the components of a fraud management platform The benefits of implementing a fraud management platform How the TIBCO platform has helped other companies Unable to attend live? We got you. Register anyway and receive the recording after the event.
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TIBCO Software
Published By: RMS     Published Date: Jul 25, 2019
The insurance industry boasts some of the most sophisticated modeling capabilities in the world. And yet the average property underwriter does not have access to the kind of predictive tools that carriers use at a portfolio level to manage risk aggregation, streamline reinsurance buying and optimize capitalization.
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RMS
Published By: AWS     Published Date: Jul 24, 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
Published By: TIBCO Software     Published Date: Jul 22, 2019
Connected Intelligence in Insurance Insurance as we know it is transforming dramatically, thanks to capabilities brought about by new technologies such as machine learning and artificial intelligence (AI). Download this IDC Analyst Infobrief to learn about how the new breed of insurers are becoming more personalized, more predictive, and more real-time than ever. What you will learn: The insurance industry's global digital trends, supported by data and analysis What capabilities will make the insurers of the future become disruptors in their industry Notable leaders based on IDC Financial Insights research and their respective use cases Essential guidance from IDC
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TIBCO Software
Published By: ETQ     Published Date: Jul 10, 2019
Product recalls cost food and beverage companies millions of dollars each year, but 56% of last year's recalls across the US, UK and Ireland were preventable. With compliance challenges becoming more complex and public scrutiny exponentially greater, one recall can cause a world of trouble. The new US Food Safety Modernization Act (FSMA) seeks to encourage a more proactive and predictive approach to food safety. Learn how automation can help you comply with this new regulation by 2020 and avoid a costly product recall.
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ETQ
Published By: Group M_IBM Q3'19     Published Date: Jun 24, 2019
Today's energy, environment, and utility companies face an unfamiliar landscape in which they must integrate alternative energies, expand situational awareness across the system, and deepen their relationships with customers-all while continuing to deliver reliable, safe, and affordable electricity, gas and water to everyone.By combining predictive analytics with IoT, cloud and mobile technologies, utilities companies can Lower costs, improve operational efficiency and increase equipment reliability.
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Group M_IBM Q3'19
Published By: Genesys     Published Date: Jun 19, 2019
Successfully managing a contact center requires a collaborative, multidisciplinary approach to handle a broad range of operational and tactical tasks. Planning, day-to-day operations and quality management must be seamlessly orchestrated, along with human resources functions like recruitment, learning and development, and employee scheduling. Read this executive brief to learn how to transition to an AI strategy that can take your team – and business results – to the next level. See how you can: Create an AI strategy with a single data model that includes routing, interaction analytics, forecasting/scheduling and predictive engagement Harness the power of your data to align customers with the best resource Drive employee effectiveness by ensuring you hire the right people and manage their performance to drive their success over the long term
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Genesys
Published By: Sierra Wireless     Published Date: Jun 19, 2019
By simplifying the ability of companies to securely extract, orchestrate and act on data from when it is generated by energy assets to when it is transmitted to the cloud, Octave simplifies the development and commercialization of Energy IoT applications. With Octave, energy companies are empowered to realize the Energy IoT’s tremendous potential, with new demand response, energy efficiency optimization, predictive maintenance and other applications that maximize the value created by energy assets and minimize their environmental impact. In doing so, these Energy IoT applications can reduce energy costs, improve customer engagement, lower greenhouse gas emissions and increase energy reliability. Start with Sierra to learn more about how our Octave D2C data orchestration solution can help you bring to market Energy IoT applications that reimagine the future of energy.
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Sierra Wireless
Published By: Hewlett Packard Enterprise     Published Date: Jun 17, 2019
"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond the remote monitoring systems of a prior generation. Three key features differentiate cloud-based predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically what types of value these systems can drive, IDC discusses them at some length in this white paper."
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Hewlett Packard Enterprise
Published By: KPMG     Published Date: Jun 06, 2019
HR’s most confident leaders are using data, predictive insights and AI to transform HR into a new value driver. Discover what it takes to become an HR transformation trailblazer. Read this report to discover: • how trailblazers are exploiting uncertainty to drive new competitive advantage • which technologies HR leaders are investing in • what it means to integrate human and digital labour in a collaborative workplace • six priorities for forward-looking HR leaders.
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KPMG
Published By: Domino Data Lab     Published Date: May 23, 2019
As data science becomes a critical capability for companies, IT leaders are finding themselves responsible for enabling data science teams with infrastructure and tooling. But data science is much more like an experimental research organization than the engineering and business teams that IT organizations support today. Compounding the challenge, data science teams are growing fast, often by 100% a year. This guide will quickly help you understand what data science teams do to build their predictive models and how to best support them. Learn how to modernize IT’s approach to ensure your company’s data science teams perform their best, and maximize impact to the business. Some highlights include: Why data science should not be treated like engineering. How to go beyond simple infrastructure allocation and give data science teams capabilities to manage their workflows and model lifecycle. Why agility and special hardware to support burst computing are so important to data science break
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Domino Data Lab
Published By: TIBCO Software     Published Date: May 16, 2019
Banks globally are betting big on artificial intelligence and machine learning to give them the technological edge they need for more real-time, personalized and predictive banking services. A framework will help both differentiate early winners and provide them with sustained advantages in intelligence. Download this IDC Analyst Infobrief to learn about how the world’s best banks are becoming more personal, more predictive, and more real-time than ever. What you will learn: 8 trends that reflect bank’s readiness for connected intelligence 9 pitfalls to avoid & 9 ways to bridge the gaps The personal, real-time and predictive building blocks of AI & ML for banks Notable leaders based on IDC Financial Insights’ research and their respective use cases Essential guidance from IDC to leading banks
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data, analytics, customer, banks, intelligence, capabilities, customers, insights
    
TIBCO Software
Published By: Forcepoint     Published Date: May 14, 2019
In Philip K. Dick's 1956 "The Minority Report," murder ceased to occur due to the work of the "Pre-Crime Division," that anticipated and prevented killings before they happened. Today, we are only beginning to see the impact of predictive analytics upon cybersecurity – especially for insider threat detection and prevention. Based on user interaction with data, CISOs and their teams emerge as the IT equivalent of a Pre-Crime Division, empowered to intervene before a violation is ever committed. Watch this webcast where we examine the technologies which make predictive analytics valuable, along with ethically minded guidance to strike the balance between vigilance and privacy.
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Forcepoint
Published By: Hewlett Packard Enterprise     Published Date: May 10, 2019
Applications are the engines that drive today’s digital businesses. When the infrastructure that powers those applications is difficult to administer, or fails, businesses and their IT organizations are severely impacted. Traditionally, IT assumed much of the responsibility to ensure availability and performance. In the digital era, however, the industry needs to evolve and reset the requirements on vendors. HPE Nimble Storage has broken away from convention and transformed how storage is managed and supported with the HPE InfoSight predictive analytics platform. HPE engaged ESG to conduct a quantitative survey of the HPE Nimble Storage installed base, as well as non-HPE Nimble Storage customers, to better assess how HPE InfoSight positively impacts customer environments. To find out more download this whitepaper today.
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Hewlett Packard Enterprise
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