apache hadoop

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By: MapR Technologies     Published Date: Jan 08, 2014
Forrester Research shares seven architectural qualities for evaluating Big Data production platforms. In this webinar guest speaker Mike Gualtieri, Principal Analyst at Forrester, along with experts from MapR and Cisco, will present the following: • The 7 architectural qualities for productionizing Hadoop successfully • Architectural best practices for Big Data applications • The benefits of planning for scale • How Cisco IT is using best practices for their Big Data applications Speakers • Mike Gualtieri, Principal Analyst at Forrester Research • Jack Norris, Chief Marketing Officer at MapR Technologies • Andrew Blaisdell, Product Marketing Manager at Cisco • Sudharshan Seerapu, IT Engineer at Cisco
Tags : big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
     MapR Technologies
By: MapR Technologies     Published Date: Jan 03, 2014
As the demand for Big Data analytics mushrooms, IT decision-makers must prepare for the widespread deployment of Hadoop. This Technical Insight Paper from the Evaluator Group outlines the key requirements that must be met to make Hadoop enterprise data center ready.
Tags : big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
     MapR Technologies
By: Dell     Published Date: Aug 24, 2015
To extract value from an ever-growing onslaught of data, your organization needs next-generation data management, integration, storage and processing systems that allow you to collect, manage, store and analyze data quickly, efficiently and cost-effectively. That’s the case with Dell | Cloudera® Apache™ Hadoop® solutions for big data.
Tags : dell, data management, data integration, big data, hadoop
     Dell
By: IBM     Published Date: Oct 26, 2015
Read how IBM InfoSphere BigInsights for Hadoop enables organizations to efficiently manage and mine large volumes of diverse data for valuable insights.
Tags : ibm, ibm infosphere biginsights, data, big data, hadoop
     IBM
By: IBM     Published Date: May 02, 2014
Learn more about Forrester’s results, and how these organizations are realizing both economic and operational benefits with InfoSphere Optim solutions.
Tags : ibm, big data, big sql, querying data, database management technology, apache hadoop, data administrators, infosphere, biginsights, industry-standard sql, management systems, database metadata, application programming interfaces, api, data persistence, virtualize data, lifecycle management, big data strategy, it management, data management
     IBM
By: Group M_IBM Q1'18     Published Date: Jan 04, 2018
IBM® InfoSphere® Big Match for Hadoop helps you analyze massive volumes of structured and unstructured customer data to gain deeper customer insights. It can enable fast, efficient linking of data from multiple sources to provide complete and accurate customer information—without the risks of moving data from source to source. The solution supports platforms running Apache Hadoop such as IBM Open Platform, IBM BigInsights, Hortonworks and Cloudera.
Tags : hadoop, infosphere, data, customer insights
     Group M_IBM Q1'18
By: IBM     Published Date: Jul 05, 2018
Scalable data platforms such as Apache Hadoop offer unparalleled cost benefits and analytical opportunities. IBM helps fully leverage the scale and promise of Hadoop, enabling better results for critical projects and key analytics initiatives. The end-to- end information capabilities of IBM® Information Server let you better understand data and cleanse, monitor, transform and deliver it. IBM also helps bridge the gap between business and IT with improved collaboration. By using Information Server “flexible integration” capabilities, the information that drives business and strategic initiatives—from big data and point-of- impact analytics to master data management and data warehousing—is trusted, consistent and governed in real time. Since its inception, Information Server has been a massively parallel processing (MPP) platform able to support everything from small to very large data volumes to meet your requirements, regardless of complexity. Information Server can uniquely support th
Tags : 
     IBM
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