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ibm big data big data

Results 1 - 25 of 36Sort Results By: Published Date | Title | Company Name
Published By: IBM     Published Date: Jul 26, 2017
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base. High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-centric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
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customer analytics, data matching, big data, competitive advantage, customer loyalty
    
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, business technology
    
IBM
Published By: IBM     Published Date: Apr 22, 2016
The upside of disruption: Reinventing business processes, organizations and industries in the wake of the digital revolution
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ibm, ibm big data and analytics, ibm big data, trusted data, big data, data management
    
IBM
Published By: IBM     Published Date: Jul 06, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
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ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality
    
IBM
Published By: IBM     Published Date: Jul 06, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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ibm, mdm, big data, ibm infosphere, data management, data center
    
IBM
Published By: IBM     Published Date: Jul 06, 2016
Five high-value uses for big data: IBM has conducted surveys, studied analysts’ findings, talked with more than 300 customers and prospects and implemented hundreds of big data solutions. As a result, it has identified five high-value use cases that enable organizations to gain new value from big data.
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ibm, mdm, big data, trusted data, data solutions, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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ibm, mdm, big data, ibm infosphere, mdm advantagw, knowledge management, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
Tags : 
    
IBM
Published By: IBM     Published Date: May 27, 2014
“Big data”– which admittedly means many things to many people – is no longer confined to the realm of technology. Today, it is a business imperative. In addition to providing solutions to insurance companies’ long-standing business challenges, big data inspires new ways to transform processes, organizations and many aspects of the insurance industry as we know it.
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ibm, big data, insurance, insurance technology, big data solutions, business value, financial data, risk data
    
IBM
Published By: IBM     Published Date: May 27, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media
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ibm, big data, analytics, insurance, insurance industry, big data solutions, integration, risk assessment
    
IBM
Published By: IBM     Published Date: May 02, 2014
This paper introduces you to Big SQL, answering many of the common questions that relational database management system (DBMS) users have about this IBM technology.
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ibm, big data, big sql, querying data, database management technology, apache hadoop, data administrators, infosphere
    
IBM
Published By: IBM     Published Date: May 02, 2014
Your Big Data Stampede includes an assessment to identify the high value starting points with Big Data. We work with you to unearth trouble areas and complex problems for resolution through leveraging Big Data. Read this data sheet to learn more.
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ibm, big data, big data success, big data platform, big data stampede, high value, assessments, big data solutions
    
IBM
Published By: IBM     Published Date: May 02, 2014
These traditional analytical systems are often based on a classic pattern where data from multiple operational systems is captured, cleaned, transformed and integrated before loading it into a data warehouse.
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ibm, big data platform, architecting big data, analytics, intelligent business strategies, data complexity, data types, workload growth
    
IBM
Published By: IBM     Published Date: May 28, 2014
The ability to keep pace with trends like big data, open data, sophisticated analytics, and the de-compartmentalization of data silos and processes, distinguishes leading master data management (MDM) solutions from their counterparts. IBM, one of the five vendors in this evaluation, is positioned as THE leader with the most prominent, widely implemented solution in the market.
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ibm, forrester, master data management, big data, database management technology, data administrators, infosphere, biginsights
    
IBM
Published By: IBM     Published Date: May 28, 2014
Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.
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ibm, data lifecycle management, infosphere optim, integrating big data, governing big data, integration, best practices, big data
    
IBM
Published By: IBM     Published Date: May 28, 2014
Different types of data have different data retention requirements. In establishing information governance and database archiving policies, take a holistic approach by understanding where the data exists, classifying the data, and archiving the data. IBM InfoSphere Optim™ Archive solution can help enterprises manage and support data retention policies by archiving historical data and storing that data in its original business context, all while controlling growing data volumes and improving application performance. This approach helps support long-term data retention by archiving data in a way that allows it to be accessed independently of the original application.
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ibm, data retention, information governance, archiving, historical data, integrating big data, governing big data, integration
    
IBM
Published By: IBM     Published Date: Oct 01, 2014
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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mdm, big data, master data, data solutions, data management, project management
    
IBM
Published By: IBM     Published Date: Dec 24, 2014
Organizations and intelligence agencies from a variety of industries and sectors face the same challenges when it comes to big data – the need to uncover actionable insights, with limited resources, with critical speed. But with the right intelligence solution, overwhelming data won’t be a challenge, rather, it becomes your resource to smarter, more effective decision making.
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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: 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: Jan 09, 2015
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
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big data, mdm, client analytics, real-time analysis, it management, knowledge management, data 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 management, data center
    
IBM
Published By: IBM     Published Date: Apr 18, 2016
To help enterprises create trusted insight as the volume, velocity and variety of data continue to explode, IBM offers several solutions designed to help organizations uncover previously unavailable insights and use them to support and inform decisions across the business. Combining the power of IBM® InfoSphere® Master Data Management (MDM) with the IBM big data portfolio creates a valuable connection: big data technology can supply insights to MDM, and MDM can supply master data definitions to big data.
Tags : 
ibm, mdm, big data, ibm infosphere, data management
    
IBM
Published By: IBM     Published Date: Apr 18, 2016
"Five high-value uses for big data: IBM has conducted surveys, studied analysts’ findings, talked with more than 300 customers and prospects and implemented hundreds of big data solutions. As a result, it has identified five high-value use cases that enable organizations to gain new value from big data."
Tags : 
ibm, mdm, big data, trusted data, data solutions, data management
    
IBM
Published By: IBM     Published Date: Apr 18, 2016
"Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need."
Tags : 
ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality
    
IBM
Published By: IBM     Published Date: Sep 27, 2013
Analytics: The Real-World Use of Big Data - How innovative enterprises in the midmarket extract value from uncertain data This study highlights the phases of the big data journey, the objectives and challenges of midsize organizations taking the journey, and the current state of the technology that they are using to drive results. It also offers a pragmatic course of action for midsize companies to take as they dive into this new era of computing.
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ibm, big data, big data solutions, midmarket businesses, analytics, it management, data management, business technology
    
IBM
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