decision analytics

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Published By: Interactive Intelligence     Published Date: Feb 27, 2013
In this white paper, learn about the advances in decision techniques that are at the center of contact center enterprise analytics. Learn how computers shouldn't replace people as decision makers, rather, aid us in decisions that are hard to make.
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contact center, enterprise, analytics, advances in decision technologies, decision makers, strategies in decision cycles, computers ai
    
Interactive Intelligence
Published By: Exact Software     Published Date: Jun 22, 2008
Businesses, more than ever before, are relying on fact based decision-making and analytics to compete in this environment. This has given rise to "Business Intelligence," or simply BI, a broad category of applications and technologies for accessing, combining, computing and analyzing data to help enterprise users make better business decisions.
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business intelligence, business analytics, analytical applications, make more money, exact america, exact software, exact, competitive
    
Exact Software
Published By: IBM Software     Published Date: Oct 26, 2010
Analytics are changing how organizations today operate. Being able to quickly and effortlessly interact with business information is now considered essential to making the best business decisions.
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analytics, business decision making, analytics system
    
IBM Software
Published By: SAS     Published Date: Jul 25, 2011
An analytic center of excellence demonstrates that an organization is committed to making better, fact-based decision and leveraging analytics to validate assumptions and identify root causes of business problems. This paper focuses on how to form an analytic center of excellence and the value the business will derive from it.
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coe, cost of excellence, sas, optimize, optimization, research, development, new product, services, internet, expedia inc, analytic, ecommerce, express warranty, news, article, story
    
SAS
Published By: SAS     Published Date: Aug 03, 2016
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment.
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best practices, embedding analytics, technology, data, operational analytics
    
SAS
Published By: SAS     Published Date: Mar 06, 2018
The Connected Customer is an individual who is intimately connected to the data, outcomes, decisions, and staff associated with any relationship to an organization. This intensely personal connection is not just a matter of the most recent transaction, but represents a combination of connected data, connected analytics, and collaborative decisions associated with improving the customer’s relationship with the organization over time. In this report, Blue Hill explores the key traits associated with supporting the Connected Customer through the Internet of Things, and provides guidance on why the Internet of Things will be essential across the general business landscape
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SAS
Published By: IBM     Published Date: Nov 05, 2013
In today’s mobile, connected era, customers expect perfection from their service providers. With competitors only a click (or tap) away, companies have a strong incentive to deliver flawless operations. Online retailers have “set a high bar” in the way that they engage customers throughout the entire sales process—not just during the commercial transaction, but before, during and after the transaction. Can your insurance company meet the challenge?
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smarter process approach, agility, business process management, bpm, insurance, case management, operational decision management, analytics, process automation
    
IBM
Published By: Cisco     Published Date: Sep 15, 2015
IDC finds that leveraging data analytics in business decisions is becoming a top priority for an increasing number of companies. This in turn is placing new demands on IT organizations; the need is twofold: to manage new streams of unstructured data from sources such as social media and to speed response times to deliver real-time analytics.
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sap, analytics, data, real-time
    
Cisco
Published By: IBM     Published Date: Apr 07, 2015
Now in V8.7 of IBM Operational Decision Manager, IBM ODM Advanced applies insights and analytics to operational decisions by bringing together data from different sources and looking at historical trends and patterns to determine the next best action. With IBM Operational Decision Manager Advanced, you gain scope, scale, speed, and simplicity. You can now capture events, build context, and apply it to operational decisions in real-time. This helps detect situations as they occur – presenting risks or opportunities – to enable action.
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ibm, odm, operational, decision, maker, analytics, update, v8.7, decisions, data, scope, scale, speed, context
    
IBM
Published By: FICO     Published Date: Sep 02, 2016
The unifying concept that defines FICO and its substantial technology and solutions stack is Decision Management. This term has not yet become mainstream - but it will. All business analytics activities are performed with the single aim of improving the accuracy and efficiency of business decisions. This applies to business intelligence, data visualization, data mining, business rules management, and many other forms of analysis. Unifying these activities under a single discipline means that currently fragmented analytical efforts can be combined into a single whole, with benefits that will be discussed in this review.
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FICO
Published By: IBM     Published Date: Mar 31, 2016
"The market buzz around APIs has distorted executive's thought processes about how to make money from APIs. Our guest speaker, Forrester analyst Randy Heffner, will tell the real truth about how to drive value from APIs. Who Should Read/View This webcast: business audience Attend to also learn how to: Provide business users with real-time information for more informed decision making Leverage the latest cloud, mobile, and analytics enhancements in IIB v10 Use the IIB Healthcare Pack to accelerate development and deployment of integration solutions Who Should Attend this Webcast: business audience"
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ibm, api, integration, application program interface, middleware
    
IBM
Published By: IBM     Published Date: Jul 20, 2016
A successful business case is one that enables your organisation’s business leaders to make the right decisionabout a Talent Analytics investment. In this report we highlight the key aspects you need to think about as you create your own business case for Talent Analytics, starting with getting a clear handle on why it is a worthwhile investment for your organisation, but also addressing considerations such as budget and resourcing concerns, how you can measure the success of your initiative and demonstrate ROI, and the major risks you need to bear in mind over the lifetime of the initiative.
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ibm, mwd advisors, talent analytics
    
IBM
Published By: Kronos     Published Date: Sep 20, 2018
If you’ve tried managing your retail operation’s labor performance without reliable, real-time data, you know the costly shortcomings of this approach. Tap into clear, easy-to-access workforce data — a single view of all elements of your workforce that empowers you to make effective decisions and protect your bottom line. Workforce Analytics for Retail transforms labor and sales data into meaningful business intelligence. Learn how managers can make data-driven decisions that optimize workforce utilization, control labor costs, and drive continuous improvement.
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Kronos
Published By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements. To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: TIBCO Software     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
Published By: TIBCO Software     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
Published By: TIBCO Software     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
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