big data

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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: Jan 27, 2017
A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamlessly integrate with diverse technologies, from data marts to Apache Hadoop systems. And it must automatically discover, protect and monitor sensitive information as part of big data applications.
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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.
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IBM
Published By: IBM     Published Date: Mar 29, 2017
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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cloud, analytics, data, organization, ibm
    
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: Apr 18, 2017
The data integration tool market was worth approximately $2.8 billion in constant currency at the end of 2015, an increase of 10.5% from the end of 2014. The discipline of data integration comprises the practices, architectural techniques and tools that ingest, transform, combine and provision data across the spectrum of information types in the enterprise and beyond — to meet the data consumption requirements of all applications and business processes. The biggest changes in the market from 2015 are the increased demand for data virtualization, the growing use of data integration tools to combine "data lakes" with existing integration solutions, and the overall expectation that data integration will become cloud- and on-premises-agnostic.
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data integration, data security, data optimization, data virtualization, database security, data analytics, data innovation
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An effective big data integration solution delivers simplicity, speed, scalability, functionality and governance to produce consumable data. To cut through this misinformation and develop an adoption plan for your Hadoop big data project, you must follow a best practices approach that takes into account emerging technologies, scalability requirements, and current resources and skill levels.
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data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
    
IBM
Published By: IBM     Published Date: May 09, 2017
How companies are managing growth, gaining insights and cutting costs in the era of big data
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
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 06, 2017
In order to exploit the diversity of data available and modernize their data architecture, many organizations explore a Hadoop-based data environment for its flexibility and scalability in managing big data. Download this white paper for an investigation into the impact of Hadoop on the data, people, and performance of today's companies.
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hadoop, flexibility, scalability, data architecture
    
IBM
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 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. This e-book presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
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database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18
Published By: IBM APAC     Published Date: Aug 25, 2017
Machine learning automates the development of analytic models that can learn and make predictions on data. It has been one of the fastest growing disciplines within the world of statistics and data science, but the barrier to entry has been high, not only in cost, but also in the need for specialized talent.
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machine learning, apache spark, additional resources, big data, ibm
    
IBM APAC
Published By: IBM APAC     Published Date: Aug 25, 2017
Transitioning from traditional IT to cloud IT is not an all-at-once, big bang effort. Rather, the cloud adoption process should be an agile, incremental process. And the first part of that process is understanding the different cloud models. Contrary to popular belief, cloud isn’t necessarily only public cloud, multi-tenant, and hosted in a vendor’s data center. It can also be private cloud, single-tenant, and/or hosted in a corporate data center. Often the best solution is a hybrid combination of these options. This paper will show you the advantages of hybrid cloud applications and explore the considerations you should make to find an optimal solution for your organization.
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cost reduction, cost optimization, business agility, innovation, business models
    
IBM APAC
Published By: CA Technologies     Published Date: Jan 08, 2014
Today’s trends, including cloud, mobile, social media, and big data, are causing huge changes in the way that identities need to be managed. As a result, the previous notion of a network perimeter is disappearing. With the advent of cloud and mobility, identity has become the new perimeter. This trend will have profound impacts on the business and IT organizations. This paper describes an identity-centric approach to security that can help you grow your business while protecting your key assets from improper use.
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ca technologies, identity, identity management, user provisioning, identity centric security, security, cloud
    
CA Technologies
Published By: CA Technologies     Published Date: Jan 15, 2014
Today’s trends, including cloud, mobile, social media, and big data, are causing huge changes in the way that identities need to be managed. As a result, the previous notion of a network perimeter is disappearing. With the advent of cloud and mobility, identity has become the new perimeter. This trend will have profound impacts on the business and IT organizations. This paper describes an identity-centric approach to security that can help you grow your business while protecting your key assets from improper use.
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ca technologies, identity, identity management, user provisioning, identity centric security, security, cloud, network provisioning
    
CA Technologies
Published By: CA Technologies     Published Date: Jan 15, 2014
Today’s trends, including cloud, mobile, social media, and big data, are causing huge changes in the way that identities need to be managed. As a result, the previous notion of a network perimeter is disappearing. With the advent of cloud and mobility, identity has become the new perimeter. This trend will have profound impacts on the business and IT organizations. This paper describes an identity-centric approach to security that can help you grow your business while protecting your key assets from improper use.
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ca technologies, identity, identity management, user provisioning, identity centric security, security, cloud, network provisioning
    
CA Technologies
Published By: Avaya     Published Date: Dec 18, 2013
Your contact center is a hotbed of activity, constantly processing calls and emails, chats and social media posts, problems and solutions. As a result, it generates the kind of “big data” that other departments wish they had. But collecting that data is just the beginning. The next step is turning it into a plan of action.
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avaya, big data, contact center, social media, software development, it management, data center
    
Avaya
Published By: EMC Corporation     Published Date: May 27, 2014
ESG Whitepaper: New security risks and old security challenges often overwhelm legacy security controls and analytical tools. This ESG white paper discusses why today's approach to security management—that depends on up-to-the-minute situational awareness and real-time security intelligence—means organizations are entering the era of big data security analytics.
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emc, security operations, security analytics, intelligence-driven security, threat detection, security monitoring, critical incident response, security
    
EMC Corporation
Published By: Pentaho     Published Date: Aug 22, 2016
This white paper provides a concise overview of big data integration technologies, and reviews key things to consider when creating an integrated big data environment that blends new technologies with existing BI systems to meet your business goals.
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big data, data integration, bi systems, hadoop
    
Pentaho
Published By: Pentaho     Published Date: Aug 22, 2016
This white paper covers six guidelines product leaders should explore during their embedded analytics evaluation.
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big data, data integration, bi systems, hadoop
    
Pentaho
Published By: Pentaho     Published Date: Aug 29, 2016
This white paper covers the many options available for modernizing a data warehouse.
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Pentaho
Published By: Forrester     Published Date: May 10, 2012
In the never-ending race to stay ahead of the competition, companies are developing advanced capabilities to store, process, and analyze vast amounts of data from social networks, sensors, IT systems, and other sources to improve business intelligence and decisioning capabilities.This report will help security and risk professionals understand how to control and properly protect sensitive information in this era of big data.
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data-centric security, information protection, information management, data protection, security, risk and compliance, data warehousing
    
Forrester
Published By: Teradata     Published Date: Jun 12, 2013
Nationwide Mutual Insurance Company operates in a very competitive industry, so it must constantly prepare to meet new challenges as well as build on past successes, maximizing ever asset including its information. In fact, Nationwide's vision - the recognition of its information as a strategic asset - has proved to be a key factor in the company's success. Download this paper to learn more.
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big data, big data analytics, customer relationships, customer knowledge store
    
Teradata
Published By: Teradata     Published Date: Jun 12, 2013
The ever-changing environment has offered fraudsters some tactical advantages to probe for holes in the defenses of financial services companies. Conventional approaches to fraud detection and remediation remain effective to a point, but conventional tools cannot effectively and economically process what is known as big data.
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enterprise risk intelligence, fraud detection, big data, fraud prevention
    
Teradata
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