analytical techniques

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Published By: TIBCO Software EMEA     Published Date: Sep 12, 2018
The Internet of Things (IoT) didn’t just connect everything everywhere; It laid the groundwork for the next industrial revolution. Connected devices sending data was only one achievement of the IoT—but one that helped solve the problem of data spread across countless silos that was not collected because it was too voluminous and/or too expensive to analyze. Now, with advances in cloud computing and analytics, cheaper and more scalable factory solutions are available. This, in combination with the cost and size of sensors continuously being reduced, supplies the other achievement: the possibility for every organization to digitally transform. Using a Smart Factory system, all relevant data is aggregated, analyzed, and acted upon. Sensors, devices, people, and processes are part of a connected ecosystem providing: • Reduced downtime • Minimized surplus and defects • Deep insights • End-to-end real-time visibility
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internet of things, connected ecosystem, big data, operations monitoring, process control, analytical techniques
    
TIBCO Software EMEA
Published By: IBM     Published Date: Oct 17, 2016
Why do organizations seek to design effective multi-channel customer journeys? Because customers today demand it. Download this research study from Hypatia Research Group to learn how global organizations are successfully utilizing various analytical techniques like descriptive, diagnostic, predictive, prescriptive and cognitive analysis to create a successful omni-channel customer journey.
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ibm, commerce, analytics, customer analytics, insights, research, customer journey, business technology
    
IBM
Published By: IBM     Published Date: Feb 27, 2017
Why do organizations seek to design effective multi-channel customer journeys? Because customers today demand it. Download this research study from Hypatia Research Group to learn how global organizations are successfully utilizing various analytical techniques like descriptive, diagnostic, predictive, prescriptive and cognitive analysis to create a successful omni-channel customer journey.
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hypatia research group, cognitive analysis, predictive analysis, customer journey
    
IBM
Published By: TIBCO Software EMEA     Published Date: Nov 12, 2018
The insurance industry stands on the precipice of change, with waves of innovation and disruption driving new possibilities across all departments, including pricing, underwriting, claims, and fraud. This webinar recording of a live panel debate is ideal for insurance professionals wanting to understand how best to unlock the possibilities created by advanced analytical techniques such as Artificial Intelligence (AI), Machine Learning (ML), and others. This TIBCO and Marketforce webinar on “The Fourth Industrial Revolution in Insurance” includes speakers Ian Thompson, chief claims officer at Zurich; David Williams, chief underwriting officer at AXA; and Clare Lunn, GI fraud director at LV=. The panel discusses: Moving towards the algorithmic insurer: the opportunities created by AI and ML How insurers can become more agile in the face of new innovations and disruptive technologies How the industry can turn structured and unstructured data into insights
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agile insurance, customer experience, digital initiatives, analytical techniques
    
TIBCO Software EMEA
Published By: TIBCO Software EMEA     Published Date: Oct 03, 2018
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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artificial intelligence, machine learning, dynamic pricing, predictive claims, real-time fraud, contextual customer experience, operational effectiveness
    
TIBCO Software EMEA
Published By: Workday     Published Date: Aug 20, 2018
Most enterprise software systems rely on legacy architectures that can’t keep pace with the transactional and analytical demands of modern organizations. Workday applications, by contrast, are built using modern techniques and technologies that deliver a fast, highly insightful, contextual, and actionable experience. In this video, Petros Dermetzis, Workday executive vice president of development, provides a comprehensive overview of Workday’s innovative technologies. With a little history about the evolution of enterprise architectures thrown in, Dermetzis explains how Workday, by using object technology and in-memory technology, delivers applications that help organizations make smarter decisions based on real-time data.
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evp, development, technology, workday, innovation, applications
    
Workday
Published By: IBM Software     Published Date: Feb 03, 2012
Read this paper to learn how to combine powerful analytical techniques with your existing fraud detection and prevention efforts and deploy results to the people who can use the information to eradicate fraud and recoup money.
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ibm, security, identity management, insurance fraud, data protection, risk management
    
IBM Software
Published By: IBM Software     Published Date: Oct 24, 2011
Read this paper to learn how to combine powerful analytical techniques with your existing fraud detection and prevention efforts.
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ibm, predictive analytics, collaboration, insights, integration, automation, smarter, data analysis, ibm data analysis, smarter planet new intelligence, rfid, sensors and actuators, epedigree, track and trace, insurance fraud, data management, data mining, knowledge management, data storage, knowledge management software
    
IBM Software
Published By: IBM     Published Date: Aug 07, 2012
Insurers lose millions each year through fraudulent claims. Learn how leading insurance companies are using data mining techniques to target claims with the greatest likelihood of adjustment, improving audit accuracy and saving time and resources. Read this paper to learn how to combine powerful analytical techniques with your existing fraud detection and prevention efforts; build models based on previously audited claims and use them to identify potentially fraudulent future claims; ensure adjusters focus on claims most likely to be fraudulent; and deploy results to the people who can use the information to eradicate fraud and recoup money.
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data, mining, detect, insurance, fraud, insurers, fraudulent, claims, insurance, data, mining, techniques, audit, analytical, techniques, fraud, detection, it management, data management, data center
    
IBM
Published By: SAP     Published Date: Mar 24, 2011
In spite of the growth of virtual business activities performed via the World Wide Web, every business transaction or operation is performed at a physical place. And as handheld GPS devices drive a growing awareness of the concept of "location," people are increasingly looking for operational efficiencies, revenue growth, or more effective management as a result of geographic data services and location-based intelligence. In this white paper, David Loshin, president of Knowledge Integrity, Inc., introduces geographic data services (such as geocoding and proximity matching) and discusses how they are employed in both operational and analytical business applications. The paper also reviews analytical techniques applied across many types of organizations and examines a number of industry-specific usage scenarios.
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location-based bi, business value, geographic enhancement
    
SAP
Published By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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SAS
Published By: SPSS Inc.     Published Date: Mar 15, 2010
This paper focuses on six myths that surround direct marketing best practices and discusses how you can use specific analytical techniques and tools to beat these myths, increase response rates and boost ROI.
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spss, direct marketing software, campaign optimization, response rate, roi, segmentation, cluster analysis, customer persona, rfm, testing, prospect profiling, purchase score, postal code analysis, up-sell, cross sell
    
SPSS Inc.
Published By: IBM     Published Date: May 20, 2015
Join our IBM Big Data analytics experts at this webinar for a discussion of how the right analytical techniques can broaden the possibilities of your analytics infrastructure.
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big data, analytics, forecasting, data management
    
IBM
Published By: SAS     Published Date: Oct 18, 2017
Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications such as driverless cars. This paper, based on presentations by SAS Data Scientist Wayne Thompson, introduces key machine learning concepts and describes SAS solutions that enable data scientists and other analytical professionals to perform machine learning at scale. It tells how a SAS customer is using digital images and machine learning techniques to reduce defects in the semiconductor manufacturing process.
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SAS
Published By: IBM Software     Published Date: May 12, 2011
Learn the six myths that surround direct marketing best practices and how your organization can use specific analytical techniques and tools to bust these myths and maximize your bottom line - so you won't just survive, you'll thrive.
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ibm cognos, predictive analytics volume, direct marketing, best practices, analytical techniques
    
IBM Software
Published By: IBM Software     Published Date: May 12, 2011
Learn the six myths that surround direct marketing best practices and how your organization can use specific analytical techniques and tools to bust these myths and maximize your bottom line - so you won't just survive, you'll thrive.
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ibm cognos, predictive analytics volume, direct marketing, best practices, analytical techniques
    
IBM Software
Published By: IBM Software     Published Date: Jun 08, 2011
Learn the six myths that surround direct marketing best practices and how your organization can use specific analytical techniques and tools to bust these myths and maximize your bottom line - so you won't just survive, you'll thrive.
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ibm cognos, predictive analytics volume, direct marketing, best practices, analytical techniques
    
IBM Software
Published By: SAP     Published Date: Jul 17, 2012
In spite of the growth of virtual business activities performed via the World Wide Web, every business transaction or operation is performed at a physical place. And as handheld GPS devices drive a growing awareness of the concept of "location," people are increasingly looking for operational efficiencies, revenue growth, or more effective management as a result of geographic data services and location-based intelligence. In this white paper, David Loshin, president of Knowledge Integrity, Inc., introduces geographic data services (such as geocoding and proximity matching) and discusses how they are employed in both operational and analytical business applications. The paper also reviews analytical techniques applied across many types of organizations and examines a number of industry-specific usage scenarios.
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business, sap, white paper, technology, location, intelligence, business value, data services, business technology
    
SAP
Published By: TIBCO Software APAC     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software APAC
Published By: TIBCO Software APAC     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software APAC
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