big data solution

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Published By: IBM     Published Date: Jul 15, 2015
The Forrester Wave.
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big data, analytics solutions, evaluate, analytical data, strategy
    
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, data management
    
IBM
Published By: IBM     Published Date: Jul 08, 2015
While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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IBM
Published By: Sage     Published Date: Jul 08, 2015
Download this white paper to learn more about how to improve your organization's inventory management and control.
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inventory management, big data, inventory control, cost containment, customer service
    
Sage
Published By: SevOne     Published Date: Jul 07, 2015
Because inventory is usually one of the biggest numbers on their balance sheet, effective inventory control and management is a vital function to help insure the continued success of distribution and manufacturing and companies.
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erp, inventory management, big data, manufacturing, distribution, business technology
    
SevOne
Published By: IBM     Published Date: Jul 01, 2015
This paper discusses why it is important for healthcare organizations to become data driven, gives examples of organizations that are already leveraging a wide range of big data.
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clinical analytics, enhanced data foundation, data-driven healthcare organization, integrated data sources, data lifecycle management, big data, healthcare analytics solutions
    
IBM
Published By: IBM     Published Date: May 19, 2015
Predictive analytics is within easy reach for all enterprises if they choose the right big data predictive analytics solution to meet their needs.
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predictive analytics, predictive analytics solutions, big data, enterprise. advanced analytics, application development
    
IBM
Published By: Equinix     Published Date: May 18, 2015
This paper illustrates how organisations are becoming digital enterprises due to the technology implications of scale and volume.
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technology, digital economy, network, become a digital enterprise, mobile, social, cloud, big data, digital enterprise, digital infrastructure, equinox, hybrid infrastructure, equinix solutions, optimise your network, digital world challenges, networking, byod
    
Equinix
Published By: Cisco     Published Date: May 15, 2015
Whitepaper focused on how leaning on bundled solutions and proven expertise can achieve big data success.
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big data, strategy, cisco, internet
    
Cisco
Published By: IBM     Published Date: May 07, 2015
Learn IBM emerged as one of the three leaders after Forrester Research evaluated 13 big data predictive analytics solution vendors.
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analytics solution, predictive analytics, embed intelligence, forrester wave, application development
    
IBM
Published By: Teradata     Published Date: May 01, 2015
Creating value in your enterprise undoubtedly creates competitive advantage. Making sense of the data that is pouring into the data lake, accelerating the value of the data, and being able to manage that data effectively is a game-changer. Michael Lang explores how to achieve this success in “Data Preparation in the Hadoop Data Lake.” Enterprises experiencing success with data preparation acknowledge its three essential competencies: structuring, exploring, and transforming. Teradata Loom offers a new approach by enabling enterprises to get value from the data lake with an interactive method for preparing big data incrementally and iteratively. As the first complete data management solution for Hadoop, Teradata Loom enables enterprises to benefit from better and faster insights from a continuous data science workflow, improving productivity and business value. To learn more about how Teradata Loom can help improve productivity in the Hadoop Data Lake, download this report now.
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data management, productivity, hadoop, interactive, enterprise
    
Teradata
Published By: IBM     Published Date: Apr 29, 2015
In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative.
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data warehouse, big data, unstructured data, implementations
    
IBM
Published By: Basho     Published Date: Apr 13, 2015
Today’s consumers expect instant access to communications services whether they’re in the office, at home, or on the road. With data speeds increasing and international roaming costs decreasing, data usage is rapidly growing. Telecommunications Service Providers (TSPs) are under pressure to deliver more services to more people and approach 100% uptime all while lowering prices to consumers. Traditional relational databases can’t meet the requirements for massive scalability, availability, and fault tolerance that the rapid growth in data usage and rise of big data demands. Read this solution brief to learn how Riak excels at these. Riak is a distributed NoSQL database optimized for big data. Riak meets many of the challenges you may be facing with your own service operations systems.
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riak, basho, telecommunications service provider, license fees, scalability, availability, data usage, big data, service operations system, networking, it management, data management
    
Basho
Published By: IBM     Published Date: Apr 09, 2015
This ebook outlines four steps to develop a proactive approach to data security and privacy that will help you keep big data safe, and shows how IBM InfoSphere solutions can help protect data while giving your staff the right levels of access to do their jobs efficiently and accurately.
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data security, ibm, ibm infosphere, privacy strategy, big data security, it management, knowledge management, data management
    
IBM
Published By: IBM     Published Date: Apr 06, 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, analytics, unstructured content, enterprise information, ibm, it management, knowledge management, storage, data management
    
IBM
Published By: New Relic     Published Date: Mar 17, 2015
Application performance management (APM) focuses on monitoring, maintaining, and optimizing the performance and health of business applications across development, test, datacenter, and network environments. As mission-critical enterprise application environments become more complex because of the increased use of cloud, big data, and mobility, APM is becoming a top priority for IT teams that need to quickly and cost effectively track end-to-end application performance, identify and remediate the root cause of performance problems, and maintain service levels required by end users and business stakeholders. SaaS-delivered APM solutions offer rapid time to value for IT organizations that need to implement APM quickly with minimal disruption to the business.
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apm, application performance management, big data, application performance, mobility, data center, data management
    
New Relic
Published By: ClearSlide, Inc     Published Date: Feb 25, 2015
As sales transforms to customer engagement-based selling, sales teams are challenged to not only help customers address their problems, but also challenge their current wisdom, driving innovation and differentiation in the market.
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sales analytics, best practices, big data, data solutions
    
ClearSlide, Inc
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.
Tags : 
big data, ibm, big data outcomes, information governance, big data analytics, it management, data management, data center
    
IBM
Published By: IBM     Published Date: Feb 24, 2015
IBM offers a comprehensive solutions portfolio that helps insurance companies integrate big data and analytics capabilities into their telematics strategy. The portfolio incorporates dozens of new patented technologies developed by IBM Research and builds on IBM Watson Foundations.
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telematics, ibm, insurance, big data, comprehensive solutions
    
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: HP     Published Date: Feb 02, 2015
Customers across all industries are transitioning to the 3rd Platform, where IT organizations are seeking to leverage mobile, social, cloud, and big data solutions to drive business value. At the same time, the pace at which the business operates is continually accelerating.
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HP
Published By: Teradata     Published Date: Jan 30, 2015
Big Data analytics are a top priority at many companies today. Most hope to derive new insights from all available data to improve productivity, cut costs, reduce churn, enhance the customer experience, and seize new business opportunities.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, data management, business technology
    
Teradata
Published By: Teradata     Published Date: Jan 30, 2015
This report is about two of those architectures: Apache™ Hadoop® YARN and Teradata® Aster® Seamless Network Analytical Processing (SNAP) Framework™. In the report, each architecture is described; the use of each in a business problem is illustrated; and the results are compared.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, aster, snap, framework, apache, hadoop, yarn, architectures, data management, business technology
    
Teradata
Published By: Teradata     Published Date: Jan 30, 2015
It is hard for data and IT architects to understand what workloads should move, how to coordinate data movement and processing between systems, and how to integrate those systems to provide a broader and more flexible data platform. To better understand these topics, it is helpful to first understand what Hadoop and data warehouses were designed for and what uses were not originally intended as part of the design.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, framework, apache, hadoop, architecture, warehouse, optimization, security, scalability, consistency, flexibility, data management
    
Teradata
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
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