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analytics solution

Results 251 - 275 of 344Sort Results By: Published Date | Title | Company Name
Published By: IBM     Published Date: Oct 11, 2016
Ordinary analytics tools can’t keep up with today’s digital, multichannel and demanding customers. This guide highlights three major challenges associated with traditional analytics and how innovative strategies combined with IBM’s Customer Experience Analytics solution can solve them.
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ibm, customer analytics, customer experience, analytics, data insight, enterprise applications
    
IBM
Published By: IBM     Published Date: Feb 01, 2017
Ordinary analytics tools can’t keep up with today’s digital, multichannel and demanding customers. This guide highlights three major challenges associated with traditional analytics and how innovative strategies combined with IBM’s Customer Experience Analytics solution can solve them.
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ibm, commerce, customer analytics, customer insights, enterprise applications
    
IBM
Published By: IBM     Published Date: Dec 24, 2014
Watch the video above to learn about the new big data and advanced analytics solution from IBM.
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ibm, big data, insight analysis, big data analysis, intelligence solutions, advanced analytics, business decision making, it management
    
IBM
Published By: IBM     Published Date: Feb 24, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, ibm, big data outcomes, information governance, big data analytics, it management, data center
    
IBM
Published By: IBM     Published Date: Jul 14, 2015
This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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big data, data warehouse, data center, information governance, analytics, big data analytics, business management
    
IBM
Published By: IBM     Published Date: Oct 07, 2015
Whether you work in marketing, customer service, sales, finance, operations or another area of your business, IBM predictive analytics software puts a wealth of advanced capabilities at your fingertips, anywhere you need them—on premises, on cloud or as a hybrid solution.
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it management, data center
    
IBM
Published By: IBM     Published Date: Jul 12, 2016
Join us for a complimentary webinar with Mark Simmonds, IBM big data IT Architect who will talk with leading analyst Mike Ferguson of Intelligent Business Strategies about the current fraud landscape. They will discuss the business impact of fraud, how to develop a fraud-protection strategy and how IBM z Systems analytics solutions and predictive models can dramatically reduce your risk exposure and loss from fraud.
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ibm, z systems, fraud loss reduction, fraud management, fraud prevention, fraud analytics, roi, security
    
IBM
Published By: IBM     Published Date: Sep 30, 2016
Address budget shortages and skills gaps with cloud-based Security Intelligence & Analytics. Use a Software-as-a-Service solution to replace aging security technologies and deploy a market leading solution in only weeks. Read how you can focus on monitoring the environment rather than updating software, and replace up-front capital costs with a monthly operational fee.
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security, enterprise applications
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
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ibm, idc, big data, data, analytics, information governance, enterprise applications, data center
    
IBM
Published By: Group M_IBM Q418     Published Date: Oct 02, 2018
Organizations are faced with providing secure authentication, authorization, and Single Sign On (SSO) access to thousands of users accessing hundreds of disparate applications. Ensuring that each user has only the necessary and authorized permissions, managing the user’s identity throughout its life cycle, and maintaining regulatory compliance and auditing further adds to the complexity. These daunting challenges are solved by Identity and Access Management (IAM) software. Traditional IAM supports on-premises applications, but its ability to support Software-as-a-Service (SaaS)-based applications, mobile computing, and new technologies such as Big Data, analytics, and the Internet of Things (IoT) is limited. Supporting on-premises IAM is expensive, complex, and time-consuming, and frequently incurs security gaps. Identity as a Service (IDaaS) is an SaaS-based IAM solution deployed from the cloud. By providing seamless SSO integration to legacy on-premises applications and modern cloud-
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Group M_IBM Q418
Published By: Cisco     Published Date: Jul 11, 2016
Companies rely on an expanding set of applications to compete in today's rapidly evolving business environment: - They rely on a fast-growing array of applications and devices (email, collaboration tools, and smartphones/tablets) to communicate and conduct business with customers and business partners. - They are creating, collecting, and repurposing large, unstructured data sets in life sciences, geophysics, media, and manufacturing. - They are collecting, storing, and analyzing more social and sensor-generated data about environments, products, customers, and transactions. The promise of better and faster data-driven decision making based on all this information is pushing big data and analytics (BDA) technology to the top of executive agendas. To succeed, CIOs must place a laserlike investment focus on datacenter solutions that allow them to deliver scalable, reliable, and flexible infrastructure for fast-growing BDA environments. Read more to learn how!
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Cisco
Published By: IBM     Published Date: Jun 21, 2017
There are many types of databases and data analysis tools to choose from when building your application. Should you use a relational database? How about a key-value store? Maybe a document database? Is a graph database the right ft? What about polyglot persistence and the need for advanced analytics? If you feel a bit overwhelmed, don’t worry. This guide lays out the various database options and analytic solutions available to meet your app’s unique needs. You’ll see how data can move across databases and development languages, so you can work in your favorite environment without the friction and productivity loss of the past.
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data analysis, key value, document database, analytics
    
IBM
Published By: IBM     Published Date: Nov 30, 2017
Analyst firm, Enterprise Strategy Group, examines how companies can leverage cloud-based data lakes and self-service analytics for timely business insights that weren’t possible until now. And learn how IBM Cloud Object Storage, as a persistent storage layer, powers analytics and business intelligence solutions on the IBM Cloud. Complete the form to download the analyst paper.
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analytics, technology, digital transformation, data lake, always-on data lake, ibm, cloud-based analytics
    
IBM
Published By: Unica Corporation     Published Date: Jan 19, 2010
Most web analytics solutions were initially architected to generate reports using only aggregate data. Next generation web analytics solutions use both aggregate and individual level data to achieve interactive marketing success. This free interactive infographic, includes live links that will guide you through a valuable framework for web analysis and gives insight into your overall website performance and visitors' behaviors. Learn how to optimize your visitors' website experiences and turn those experiences into actions.
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interactive web analytics map, next generation web analytics, website optimization, multi-channel analytics, aggregate level analytics, individual level analytics, website performance, behaviorial targeting
    
Unica Corporation
Published By: SAS     Published Date: Feb 29, 2012
In this white paper, Ian Henderson of Sword Ciboodle and Retha Keyser of SAS describe what that ideal can look like and how to achieve it.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This paper presents technologies and recommendations for not only surviving, but thriving, as a marketer in today's demanding and dynamic business climate.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This paper presents the 5 most common practices that result in losing a customer and how to avoid those pitfalls. You'll also learn how more customer-centric measures can help you deepen and grow relationships with your most valuable customers.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This white paper includes practical, candid and irreverent advice from Scott on what it really means to be real time in marketing and PR.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
In a webcast co-hosted by the AMA and SAS, presenters described three areas of focus for using social media, and the five best practices for being effective in social media. This paper provides a summary of that webcast.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This white paper provides a blueprint for action for senior marketers and decision makers across the enterprise. It provides straightforward advice on how to build a more durable and profitable customer base.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This collection is part of the ANA Magazine Thought Leadership Series sponsored by SAS. The articles explore the variety of ways to use analytics to create marketing functions that are more accountable and profitable.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Feb 29, 2012
This paper provides an intro to managers and marketing professionals applying analytics to marketing to significantly improve outcomes. It explains not only why you need to make this shift, but also how you get started and what tools you'll need.
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sas, analytics, business analytics, business intelligence, customer intelligence, data management, fraud & financial crimes, high-performance analytics
    
SAS
Published By: SAS     Published Date: Aug 28, 2018
With the widespread adoption of predictive analytics, organizations have a number of solutions at their fingertips. From machine learning capabilities to open platform architectures, the resources available to innovate with growing amounts of data are vast. In this TDWI Navigator Report for Predictive Analytics, researcher Fern Halper outlines market opportunities, challenges, forces, status and landscape to help organizations adopt technology for managing and using their data. As highlighted in this report, TDWI shares some key differentiators for SAS, including the breadth and depth of functionality when it comes to advanced analytics that supports multiple personas including executives, IT, data scientists and developers.
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SAS
Published By: SAS     Published Date: Nov 16, 2018
Medicaid fraud is prevalent, costly and difficult to prevent. With a combination of more integrated data and advanced analytics, state agencies can turn the tables on fraudsters. They can accelerate the transition from detection to prevention, as new forms of fraud are recognized faster and fewer improper payments go out the door. This IIA Discussion Summary explores the challenges and opportunities in preventing Medicaid fraud in an interview with SAS’ Ellen Joyner-Roberson, Principal Marketing Manager for Fraud and Security Intelligence, and Victor Sterling, Principal Solutions Architect.
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SAS
Published By: SAS     Published Date: Dec 20, 2018
Think of the self-service things you use in a day. Gas pumps. ATMs. Online apps for shopping. They’re convenient and easy to use. People choose what they want, when they want – without involving others in their minute-to-minute decisions. What if your organization could treat data discovery and analytics the same way? SAS has combined two of its visual solutions to do just that. SAS Visual Analytics and SAS Visual Statistics share the same web-based interface to provide self-service data exploration and easy-to-use interactive predictive analytics in a collaborative environment. This white paper takes a look at this convergence and outlines how these products can be used together so that everyone, even nontechnical users, can investigate data on their own, create analytical models and uncover new insights that drive competitive differentiation. Your analytics journey just got a lot easier.
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SAS
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