data volume

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Published By: IBM     Published Date: Aug 08, 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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big data, analytics, insurance, customer service, solutions, business intelligence, market research, data management/analytics
    
IBM
Published By: IBM     Published Date: Aug 28, 2014
Data volumes are getting out of control, but choosing the right information lifecycle governance solution can be a huge challenge, with multiple stakeholders, numerous business processes, and extensive solution requirements. Use this requirements kit from the Compliance, Governance and Oversight Council (CGOC) to find the tools and technology you need.
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ilg, data volumes, cgoc, information economics
    
IBM
Published By: IBM     Published Date: Feb 24, 2015
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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big data, ibm, claims operations, customer service
    
IBM
Published By: IBM     Published Date: Apr 29, 2015
First generation warehouses were not designed to manage data at today's volume or variety. Coercing older technologies to satisfy new demands can be inefficient, burdensome and costly. Read how IBM PureData System for Analytics is built for simplicity and speed.
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big data, data management, hardware, business intelligence
    
IBM
Published By: IBM     Published Date: Jul 08, 2015
To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize its value, and integrate it at a more granular level than ever before—focusing on the individual transaction level, rather than on general summary data. As data volumes continue to explode, clients must take advantage of a fully scalable information integration architecture that supports any type of data integration technique such as ETL, ELT (also known as ETL Pushdown), data replication or data virtualization. Read this new whitepaper to learn about the seven essential elements needed to achieve the highest performance.
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IBM
Published By: IBM     Published Date: Jul 08, 2015
Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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IBM
Published By: IBM     Published Date: Oct 19, 2015
Read this new whitepaper to learn about the seven essential elements needed to achieve the highest performance
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ibm, performance, scalability, information, intgration, data volume, enterprise
    
IBM
Published By: IBM     Published Date: Oct 19, 2015
This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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ibm, integration, data volume, business technology, information
    
IBM
Published By: IBM     Published Date: Apr 18, 2016
Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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ibm, big data, trusted data, data management, data solutions
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
Today's data-driven organization is faced with magnified urgency around data volume, user needs and compressed decision time frames. In order to address these challenges, while maintaining an effective analytical culture, many organizations are exploring cloud-based environments coupled with powerful business intelligence (BI) and analytical technology to accelerate decisions and enhance performance.
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ibm, datamart on demand, analytics, cloud, hybrid cloud, business insight
    
IBM
Published By: IBM     Published Date: Jul 06, 2016
Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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ibm, big data, trusted data, data management, data solutions
    
IBM
Published By: IBM     Published Date: Jul 19, 2016
Data movement and management is a major pain point for organizations operating HPC environments. Whether you are deploying a single cluster, or managing a diverse research facility, you should be taking a data centric approach. As data volumes grow and the cost of compute drops, managing data consumes more of the HPC budget and computational time. The need for Data Centric HPC architectures grows dramatically as research teams pool their resources to purchase more resources and improve overall utilization. Learn more in this white paper about the key considerations when expanding from traditional compute-centric to data-centric HPC.
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ibm, analytics, hpc, big data
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. Download this white paper to learn how.
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database, big data, analytics, infrastructure
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Who's afraid of the big (data) bad wolf? Survive the big data storm by getting ahead of integration and governance functional requirements Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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ibm, big data, trusted data, data management, data solutions
    
IBM
Published By: IBM     Published Date: Oct 21, 2016
The greatest challenge of the big data revolution is making sense of all the information generated by today's vast digital economy. It's well enough for an organization to collect every slice of data it can reach, but how does it extract value from this massive volume of information?
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ibm, analytics, data science, data, big data, aps data, aps
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
A big data integration platform that is flexible and scalable is needed to keep up with today’s ever-increasing big data volume.
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IBM
Published By: IBM     Published Date: Mar 30, 2017
To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize its value, and integrate it at a more granular level than ever before—focusing on the individual transaction level, rather than on general summary data. As data volumes continue to explode, clients must take advantage of a fully scalable information integration architecture that supports any type of data integration technique such as extract, transfer and load (ETL), data replication or data virtualization.
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data integration, data security, data optimization, data virtualization, database security
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
A big data integration platform that is flexible and scalable is needed to keep up with today’s ever-increasing big data volume. Download this infographic to find out how to build a strong foundation with big data integration.
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big data, big data integration, scalable data
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
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data integration, big data, data sources, business needs, technological advancements, scaling data
    
IBM
Published By: IBM     Published Date: May 23, 2017
Flexible deployment options, licensing models help take the challenges out of change. As you move toward the cloud, you're likely planning or managing a mixed environment of on- premises and on- cloud applications. To help you succeed in this transition, you need a trans-formative, mixed-workload database that can handle a massive volume of data while delivering high performance, data availability and the flexibility to adapt respond to business changes.
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cloud applications, mobile optimization, web-based applications, data availability, ibm, db2
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. In many cases, these systems are no longer up to the task—so it’s time to make a decision. Do you use more staff to keep up with the fixes, patches, add-ons and continual tuning required to make your existing systems meet performance goals, or move to a new database solution so you can assign your staff to new, innovative projects that move your business forward?
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database, growth, big data, it infrastructure, information management
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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scalability, data warehousing, resource planning
    
IBM
Published By: IBM     Published Date: Jul 26, 2017
To compete in today’s fast-paced business climate, enterprises need accurate and frequent sales and customer reports to make real-time operational decisions about pricing, merchandising and inventory management. They also require greater agility to respond to business events as they happen, and more visibility into business activities so information and systems are optimized for peak efficiency and performance. By making use of data capture and business intelligence to integrate and apply data across the enterprise, organizations can capitalize on emerging opportunities and build a competitive advantage. The IBM® data replication portfolio is designed to address these issues through a highly flexible one-stop shop for high-volume, robust, secure information replication across heterogeneous data stores. The portfolio leverages real-time data replication to support high availability, database migration, application consolidation, dynamic warehousing, master data management (MDM), service
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ibm, infosphere, data replication, security, data storage
    
IBM
Published By: IBM     Published Date: Oct 17, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
Tags : 
    
IBM
Published By: IBM     Published Date: Nov 08, 2017
Flexible deployment options, licensing models help take the challenges out of change. As you move toward the cloud, you're likely planning or managing a mixed environment of on- premises and on- cloud applications. To help you succeed in this transition, you need a trans-formative, mixed-workload database that can handle a massive volume of data while delivering high performance, data availability and the flexibility to adapt respond to business changes.
Tags : 
ibm, cloud, cloud computing, database, ibm db2
    
IBM
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