predictive enterprise

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Published By: SAP     Published Date: Feb 13, 2009
In today's economic downturn, organizations are looking for ways to improve the way they do business to keep ahead of the competition and improve revenue. Increasingly, organizations are finding that the benefits of BI can be complemented when combined with predictive analysis.
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sap, business intelligence, economic downturn, predictive analytics, enterprise, business management, enterprise resource planning, enterprise software, spend management
    
SAP
Published By: HP Enterprise System     Published Date: Apr 03, 2014
SAP HANA is a powerful, in-memory computing platform that streamlines business suite applications, analytics, planning, predictive analysis, and sentiment analysis on a single platform, so businesses can operate in real time. The design approach for enterprise-level solutions involving SAP HANA, and the best practices surrounding them, isn’t intrinsically different from the approach to any other enterprise-level solution for technology implementations. This paper is written to address those elements of good solution design and apply them to the SAP landscape, with particular focus on the SAP HANA element.
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sap hana, as a service solution, solutions, cost effective, operational management, accelerate value, enterprise applications, data management
    
HP Enterprise System
Published By: SPSS     Published Date: Jun 30, 2009
This White Paper provides strategies and tactics for enabling a more innovative, predictive enterprise that maximizes the value of every customer interaction to "get, keep and grow" customers.
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spss, predictive enterprise, retail management, customer interactions, crm, customer relationship management, customer innovation, business analytics, data management, enterprise applications, roi, return on investment, predictive analytics, decision-making, data resources, enterprise feedback management, efm, customer experience, customer-facing personnel, customer interaction service
    
SPSS
Published By: SPSS     Published Date: Jun 30, 2009
This paper describes why and how Enterprise Feedback Management (EFM) is a critical component in solving the problem of enhancing customer-driven innovation and improving the predictive capabilities of the IT organization.
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predictive enterprise, spss, enterprise feedback management, efm, customer-driven innovation, crm, customer relationship management, customer experience, consumer behavior, actionable insight, centralized system, feedback programs, push orientation, lifecycle-based approach, customer retention, churn rate, compliance, internal r&d, behavioral data, descriptive data
    
SPSS
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
This paper describes why and how Enterprise Feedback Management (EFM) is a critical component in solving the problem of enhancing customer-driven innovation and improving the predictive capabilities of the IT organization.
Tags : 
predictive enterprise, spss, enterprise feedback management, efm, customer-driven innovation, crm, customer relationship management, customer experience, consumer behavior, actionable insight, centralized system, feedback programs, push orientation, lifecycle-based approach, customer retention, churn rate, compliance, internal r&d, behavioral data, descriptive data
    
SPSS, Inc.
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
This White Paper provides strategies and tactics for enabling a more innovative, predictive enterprise that maximizes the value of every customer interaction to "get, keep and grow" customers.
Tags : 
spss, predictive enterprise, retail management, customer interactions, crm, customer relationship management, customer innovation, business analytics, data management, enterprise applications, roi, return on investment, predictive analytics, decision-making, data resources, enterprise feedback management, efm, customer experience, customer-facing personnel
    
SPSS, Inc.
Published By: Oracle     Published Date: Jan 07, 2014
Most enterprises understand the importance of listening to customer comments and conversations through social channels, and engaging and developing relationships with influencers and customer communities. But as the variety, volume, and velocity of social data continues to grow, many organizations are looking for cost-effective ways to use this data to get a better understanding and more holistic view of their customer. Social provides a unique channel to learn about your customer, and offers real-time insights like interests, actions, likes and dislikes that can provide invaluable behavioral and predictive data patterns. This social data (when aggregated with enterprise CRM data) reveals a more complete picture and understanding of customers.
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social crm social roi, social media analytics, cmo and cio collaboration, socially enabled enterprise, social business, social data, social marketing, social media management, social relationship management, marketing and technology collaboration, cmo and cio relationship, customer insight, customer experience, knowledge management
    
Oracle
Published By: IBM     Published Date: Jul 12, 2016
As most companies now realize, analytics is increasingly more of an integral part of their day-to-day business operations. In a recent survey by a global research firm, 80% of CIOs stated that transition from backward-looking, passive analysis must shift to forward-looking predictive analytics. The challenge is that many analytic solutions are aligned to a specific platform, tied to inflexible programming models and requiring vast data movement. In this webcast, Forrester and experts from IBM will highlight how technology like Apache Spark on z/OS allows businesses to extract deep customer insight without the cost, latency and security risks of data movement throughout the enterprise.
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ibm, forrester, apache spark, spark technology, z systems, security, knowledge management, enterprise applications
    
IBM
Published By: FICO     Published Date: Mar 22, 2018
Predictive analytics provide the foresight to understand cybersecurity risk exposure. Cybersecurity strategies often consist of “whack-a-mole” exercises focused on the perpetual detection and mitigation of vulnerabilities. As a result, organizations must re-think the ever-escalating costs associated with vulnerability management. After all, the daily flow of cybersecurity incidents and publicized data breaches, across all industries, calls into question the feasibility of achieving and maintaining a fully effective defense. The time is right to review the risk management and risk quantifcation methods applied in other disciplines to determine their applicability to cybersecurity. Security scoring is a hot topic, and rightfully so. When evaluating ways to integrate these scores into your cybersecurity strategy, be sure to look for an empirical approach to model development. The FICO Enterprise Security Score is the most accurate, predictive security score on the market.
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FICO
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