data model

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Published By: IBM     Published Date: Apr 16, 2012
Join us on from the comfort of your desk and hear about IBM Cognos Insight, the newest addition to the IBM Cognos family. See for yourself how this extremely affordable and breakthrough solution empowers all users to independently explore data, build scenario models and share insights for better business outcomes.
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ibm, technology, powervm, vmware, virtualization, intel platform, technology platform, application integration, application performance management, analytical applications, data protection, data quality
    
IBM
Published By: IBM     Published Date: Jan 09, 2014
While some organizations are already utilizing Big Data or various large enterprise analytics techniques, many more are still working to grasp how these new usage models might help them. Theres a lot of undiscovered value in the vast amounts of data they currently have and the data that they can get from other sources. They know that they can somehow convert this data into insights that will let them ramp up efficiency and be ready for tomorrow today.
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big data, enterprise analytics, red hat, data analytics, powerlinux system, powervm virtualization, virtualization, cloud computing, infrastructure, design and facilities, power and cooling
    
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, business analytics
    
IBM
Published By: IBM     Published Date: May 27, 2014
If insurers want to succeed in today's digital world, they need to create experiences and business models that are orchestrated, symbiotic, contextual and cognitive.
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ibm, big data, insurance, digital insurer, business model, insurance industry, technology, integration, social business, it management
    
IBM
Published By: IBM     Published Date: Aug 05, 2014
Watson Explorer provides organizations with a combined, trusted 360-degree view of both structured and unstructured data. The solution indexes information from unstructured data sources (PDFs, Microsoft SharePoint, flat files, social media, blogs and so on) as well as structured sources for search and discovery. Organizations can leverage their data in place, respecting existing security models when creating this virtual access point to all information. Watson Explorer requires trusted master data to ensure that links are accurate and reliable, so the end user can confidently leverage a holistic view of a customer or product.
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ibm, data, customer, watson explorer, master data, structured, it management, data management
    
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: IBM     Published Date: Nov 14, 2014
IBM SPSS Modeler is a powerful, versatile data and text analytics workbench. Learn how you can build accurate predictive models quickly and intuitively, without programming. So you can use data to understand the current state of your organization and get a view into the future.
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ibm, webinar, business intelligence, entity analytics, modeler, automated modeling, predictive intelligence, building models, spss modeler gold, data management, change management
    
IBM
Published By: IBM     Published Date: Nov 19, 2014
Risk Management: General: Partially cloudy: the benefits of hybrid deployment models
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ibm, risk management, big data, data management, operational risk, event data, risk aware, risk solutions, hybrid deployment, deployment models, security management, business intelligence
    
IBM
Published By: IBM     Published Date: Jan 14, 2015
Cloud-delivered big data analytics presents an enormous opportunity for organizations that want to become more agile, more efficient and more competitive. To capitalize on the full potential of this opportunity, businesses need cloud-enabled big data analysis solutions that are flexible, simple, secure and open.
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big data, data management, the cloud, cloud solutions, data, data analytics, client engagement, computing model, scale on demand, data center
    
IBM
Published By: IBM     Published Date: Apr 09, 2015
As The Business Becomes Digital, Security Must Become Data-Centric S&R leaders of enterprises undergoing a digital transformation will soon realize that in order to adequately ensure customer protection and enable a digital workforce, S&R pros must abandon traditional perimeter-based security and put the focus on the data by embracing Forresters Zero Trust Model.
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data security, ibm, customer protection, digital workforce, zero trust model, security, it management, knowledge management, data management
    
IBM
Published By: IBM     Published Date: May 28, 2015
In this book, you look at how the Smarter Process approach helps you create a more customer-centric organization. You discover how four major technologies mobile, cloud computing, Big Data, and social collaboration are disrupting the way you do business and how you can work through the challenges.
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smarter process, data management, business models, blueworks live, big data, cloud computing, social collaboration, data center
    
IBM
Published By: IBM     Published Date: May 28, 2015
Transform your organization into a mobile enterprise for optimized business and customer-centric engagements
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smarter process, data management, business models, blueworks live, big data, cloud computing, social collaboration, business process management, customer service, infrastructure
    
IBM
Published By: IBM     Published Date: Jul 01, 2015
This white paper discusses how enterprise analytics systems can assist provider organizations in building sustainable healthcare systems and achieving their vision for accountable care
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healthcare analytics, data blueprint, enterprise analytics systems, sustainable healthcare systems, mission-critical analysis, integrated data model, operational analytics
    
IBM
Published By: IBM     Published Date: Apr 01, 2016
Read the eBook to: 1) Expand what you know about Big Data; 2) Learn about the Big Data Zones Model that brings a new approach to managing data, faster to deploy, faster to insights and with less risk; 3) Gain confidence in your Big Data projects and learn about the importance of governance in a Big Data world
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ibm, ibm connect, big data, big data zones model, data management
    
IBM
Published By: IBM     Published Date: Jun 07, 2016
The database you pick for your next application matters now more than ever. It can be difficult, and oftentimes impossible, to quickly join today's data into the relational model. Learn how a NoSQL database can act as a viable alternative to or compliment an existing relational database.
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ibm, nosql database, database, analytics, networking, knowledge management, enterprise applications, database development
    
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: Jul 19, 2016
Learn how IBM Cognos Analytics incorporates many governed discovery features, with which business users can easily expose the underlying data modelling of existing reports and modify it to an individual or departmental requirements
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ibm, ibm cognos analytics, analytics, business intelligence, business analytics, business integration, business management, business metrics
    
IBM
Published By: IBM     Published Date: Sep 30, 2016
Data is the lifeblood of todays digital businesses; protecting it from theft, misuse, and abuse is the top responsibility of every S&R leader. Hacked customer data can erase millions in profits, stolen IP can destroy competitive advantage, and unnecessary privacy abuses can bring unwanted scrutiny and fines from regulators while damaging reputations. S&R pros must take a data-centric approach that ensures security travels with the data regardless of user population, location, or even hosting model; position data security and privacy capabilities as competitive differentiators; and build a new kind of customer relationship.
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ibm, security, data, privacy, forrester, forrester research, data management
    
IBM
Published By: IBM     Published Date: Jan 18, 2017
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
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ibm, analytics, aps data, open data science, data science, data engineers, enterprise applications
    
IBM
Published By: IBM     Published Date: Apr 07, 2017
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization. This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solutions.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations, market research, model management
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Today, all consumers can obtain any piece of data at any point in time. This experience represents a significant cultural shift: the beginning of the democratization of data. However, the data landscape is increasing in complexity, with diverse data types from myriad sources residing in a mix of environments: on-premises, in the cloud or both. How can you avoid data chaos?
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations, market research, model management
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
Companies in all industries can benefit from a master data management program, advises MDM expert Anne Marie Smith. Learn how to enhance yours.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations, market research, model management
    
IBM
Published By: IBM     Published Date: Nov 03, 2017
Massive shifts within the digital business landscape are sparking immense opportunities and reshaping every sector. In some cases, complete upheaval is happening at lightning-fast speed. In other instances, digital undercurrents are stirring beneath the surface as organizations scramble to monetize vast volumes and variety of data in an effort to sharpen their competitive edge and not be blindsided by unforeseen events that completely upend existing business models. While long-standing industry leadership might be no match for the next cool app, agility, speed and the ability to harness more data than was ever imagined is fueling powerful possibilities for reinvention among companies of every size. Data is following rapidly from mobile devices and social networks, as well as from every connected product, machine and infrastructure. This data holds the potential for deep insights that can replace guesswork and approximations as to locations, behaviors, patterns and preferences. As the w
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digital business, data, data-driven enterprise, innovation, ibm
    
IBM
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