predictive

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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, daten, datengenauigkeit, effizienz, produktivität, selbstlernende intelligenz
    
Dassault Systèmes
Published By: IBM     Published Date: Oct 21, 2015
Learn why your organization needs geospatial analytics, and how IBM SPSS Modeler can augment predictive modeling with elements of time and space.
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ibm, spss, modeler, predictive modeling, geospatial analytics
    
IBM
Published By: Bluekai     Published Date: Aug 10, 2012
How can you analyze ALL of your disparate first and third-party audience, campaign and performance data in one central place? How can a DMP power a 360 approach to audience data management and analysis to get more bang out of your marketing dollar?
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dmp, data management platform, crm, analytics, audience targeting, predictive audience analytics, real-time campaign analytics, campaign performance
    
Bluekai
Published By: IBM     Published Date: Jun 13, 2016
Read this eBook to explore how using predictive and prescriptive analytics applied to talent can drive better business results.
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ibm, workforce analytics, ibm smarter workforce institute, human resources, hr analytics
    
IBM
Published By: EMC Corporation     Published Date: Aug 05, 2014
It’s an exciting yet daunting time to be a security professional. Security threats are becoming more aggressive and voracious. Governments and industry bodies are getting more prescriptive around compliance. Combined with exponentially more complex IT environments, security management is increasingly challenging. Moreover, new “Big Data” technologies purport bringing advanced analytic techniques like predictive analysis and advanced statistical techniques close to the security professional.
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big data, data management, security threats, advanced analytics, security management, predictive analytics, compliance
    
EMC Corporation
Published By: IBM     Published Date: Feb 04, 2015
Driving the right interaction at the right time. This paper examines the need to uncover and understand the dynamic roles and changing needs of individuals, the importance of synchronizing interactions with these changing needs, and how predictive analytics can drive customer intimacy by facilitating 1:1 interactions.
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predictive analytics, customer interaction, crm, business analytics, marketing attributes
    
IBM
Published By: CrowdTwist     Published Date: Apr 16, 2018
In order for brands to compete and provide the level of personalization consumers have already come to expect, marketers need to work quickly to develop competencies around their abilities to collect contextual and anticipatory insight and meet customers in the moments that matter most to them. Now is the time for marketers to invest in technology that supports data capture, segmentation, predictive analytics, and machine learning. With these capabilities in place, brands should be on track to build rich first party profiles of customers across all channels and maximize customer lifetime value by creating relevant experiences at all stages of the customer lifecycle.
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customers, predictive, branding, consumers, competition, lifecycle
    
CrowdTwist
Published By: KPMG     Published Date: Dec 05, 2018
Some HR leaders are confidently harnessing the disruptive technologies that will transform the HR function. How ready are you for the digital workplace? Read this report – which includes insights from HR leaders in some of the world’s most successful organisations – to understand: the anticipated impact of artificial intelligence and disruptive technologies the growing importance of the employee experience the potential of predictive analytics the changes required in workplace culture and capabilities for successful transformation.
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KPMG
Published By: IBM     Published Date: Sep 08, 2015
Please join us for an in-depth discussion of the latest data and analytics capabilities that banks are using today to uncover new customer insight - at the individual level - to improve offers and cross sell, optimize campaigns and deliver profitable revenue. The discussion will explore how leading banks are employing predictive analysis on customer data not often analyzed - like individual transactions, interactions, behavior and social media. See how banks can move beyond traditional segmentation and enable marketing to the "Segment of One."
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banking, finance, customer engagement, analytics, insights, segmentation
    
IBM
Published By: IBM     Published Date: May 22, 2015
This presentation will demonstrate that it is possible to turn the promise of Big Data into business value by applying predictive analytics to Big Data sources such as Hadoop, Cloudera, and BigInsights.
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big data, analytics, forecasting, data management, hadoop
    
IBM
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
The intrepid data miner runs many risks, including being buried under mountains of data or disappearing along with the "mysterious disappearing terabyte."  This article outlines some risks, debunks some myths, and attempts to provide some protective "hard hats" for data miners in the marketing sector.
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spss, data mining, data miner, data management, business process, best practices, business intelligence, statistics, statistical modeling, algorithms, predictive analysis, data analysis, scalability, optimization, business knowledge, decision-making
    
SPSS, Inc.
Published By: SPSS     Published Date: Jun 30, 2009
The intrepid data miner runs many risks, including being buried under mountains of data or disappearing along with the "mysterious disappearing terabyte."  This article outlines some risks, debunks some myths, and attempts to provide some protective "hard hats" for data miners in the technology sector.
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spss, data mining, data miner, data management, business process, best practices, business intelligence, statistics, statistical modeling, algorithms, predictive analysis, data analysis, scalability, optimization, business knowledge, decision-making
    
SPSS
Published By: SAP     Published Date: Dec 04, 2015
Download this whitepaper to see how advanced technologies such as big data, cloud computing, mobile devices, and enterprise access to in-memory platforms, predictive analytics, and planning software can help CFOs make better and more sophisticated use of data, influence decisions, and take practical, timely action.
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finance function, finance, cfo, big data, cloud computing, mobile, in-memory platforms, predictive analytics, planning software
    
SAP
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: IBM     Published Date: Feb 10, 2014
The closer your organization gets to your customers, the more successful it will be. Learn how to take customer relationships to a new level of intimacy using a combination of business intelligence and predictive analytics software.
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ibm, king fish media, business analytics, insights, business intelligence software, analytics quotient, roi, predictive analytics, customer behavior, customer intimacy, data warehousing
    
IBM
Published By: IBM     Published Date: Apr 29, 2014
Customer Profitability Analytics enables banks to analyze customer, account, product, and transaction data and apply costing models to determine a bank-wide view of profitability. Applying predictive analytics, they can model future behavior and derive a lifetime value for each customer.
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ibm, banking, customer profitability, customer profitability analytics, transaction data, predictive analytics, customer behavior
    
IBM
Published By: IBM     Published Date: Aug 06, 2014
Customer Profitability Analytics enables banks to analyze customer, account, product, and transaction data and apply costing models to determine a bank-wide view of profitability. Applying predictive analytics, they can model future behavior and derive a lifetime value for each customer.
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ibm, banking, customer, profit, analytics, costing models
    
IBM
Published By: Artemis Health     Published Date: Feb 05, 2019
Self-insured employers are mining their health and benefits data to save costs and provide quality care for employees. Data is driving business decisions, but how do you get from millions of rows of data to a consumable graph to taking action? In this white paper, we’ll delve into data analytics best practices that help self-insured employers find actionable insights in their benefits data. • Which data sources will help you ensure you’re measuring the right thing at the right time • How to ensure data variety and choose key metrics • An example of a successful predictive analysis using benefits data
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Artemis Health
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
    
IBM
Published By: IBM     Published Date: Aug 08, 2012
With tight budgets, it isn't easy to create the operational dexterity needed to thrive in a competitive marketplace. View this demo to find out how IBM® SPSS® solutions for predictive operational analytics help manage physical and virtual assets, maintain infrastructure and capital equipment, and improve the efficiency of people and processes. By using your existing business information, IBM SPSS software can help you: predict and prevent equipment failures that can lead to disruptive, costly downtime; quickly identify and resolve product quality issues to mitigate risks and reduce warranty costs; optimize product assortment planning to increase revenue, reduce working capital requirements and improve the return on inventory investments; and act to retain your best employees by developing predictive attrition models to identify the workers at greatest risk of leaving the organization.
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ibm, technology, predictive operational analytics, spss
    
IBM
Published By: IBM     Published Date: Nov 30, 2016
Learn how to create powerful analytic apps with IBM Cloudant, dashDB and Apache Spark. This presentation will contain demos of real-life use cases e.g. machine learning predictive analytics, Graph-parallel computation and more.
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ibm, cloud, analytic apps, apps, cloudant
    
IBM
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