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Published By: MapR Technologies     Published Date: Mar 29, 2016
Add Big Data Technologies to Get More Value from Your Stack Taking advantage of big data starts with understanding how to optimize and augment your existing infrastructure. Relational databases have endured for a reason – they fit well with the types of data that organizations use to run their business. These types of data in business applications such as ERP, CRM, EPM, etc., are not fundamentally changing, which suggests that relational databases will continue to play a foundational role in enterprise architectures for the foreseeable future. One area where emerging technologies can complement relational database technologies is big data. With the rapidly growing volumes of data, along with the many new sources of data, organizations look for ways to relieve pressure from their existing systems. That’s where Hadoop and NoSQL come in.
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MapR Technologies
Published By: MapR Technologies     Published Date: Aug 01, 2018
How do you get a machine learning system to deliver value from big data? Turns out that 90% of the effort required for success in machine learning is not the algorithm or the model or the learning - it's the logistics. Ted Dunning and Ellen Friedman identify what matters in machine learning logistics, what challenges arise, especially in a production setting, and they introduce an innovative solution: the rendezvous architecture. This new design for model management is based on a streaming approach in a microservices style. Rendezvous addresses the need to preserve and share raw data, to do effective model-to-model comparisons and to have new models on standby, ready for a hot hand-off when a production model needs to be replaced.
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MapR Technologies
Published By: MapR Technologies     Published Date: Aug 04, 2018
Legacy infrastructures simply cannot handle the workloads or power the applications that will drive business decisively forward in the years ahead. New infrastructure, new thinking and new approaches are in the offing, all driven by the mantra 'transform or die.' This book is meant for IT architects; developers and development managers; platform architects; cloud specialists; and big data specialists. For you, the goal is to help create a sense of urgency you can present to your CXOs and others whose buy-in is needed to make essential infrastructure investments along the journey to digital transformation.
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MapR Technologies
Published By: MapR Technologies     Published Date: Jul 26, 2013
Enterprises are faced with new requirements for data. We now have big data that is different from the structured, cleansed corporate data repositories of the past.Before, we had to plan out structured queries. In the Hadoop world, we don’t have to sort data according to a predetermined schema when we collect it. We can store data as it arrives and decide what to do with it later. Today, there are different ways to analyze data collected in Hadoop—but which one is the best way forward?
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white paper, hadoop, nosql, mapr, mapr technologies
    
MapR Technologies
Published By: Pentaho     Published Date: Feb 26, 2015
This eBook from O’Reilly Media will help you navigate the diverse and fast-changing landscape of technologies for processing and storing data (NoSQL, big data, MapReduce, etc).
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data systems, data-intensive applications, scalability, maintainability, data storage, application development, analytical applications, data integration, data quality, data warehousing
    
Pentaho
Published By: Teradata     Published Date: Jan 28, 2015
Althrough Hadoop and related technologies have been with us for several years, most business intelligence (BI) professionals and their business counterparts still harbor a few misconceptions that need to be corrected about Hadoop and related technologies such as MapReduce. This webcast presents the 10 most common myths about Hadoop, then corrects them. The goal is to clarify what Hadoop is and does relative to BI, as well as in which business and technology situations Hadoop-based BI, data warehousing and analytics can be useful.
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teradata, business, intelligence, hadoop, data, integration, analytics, mapreduce, warehouse
    
Teradata
Published By: Teradata     Published Date: Jun 12, 2013
Download this paper to learn how Unified Data Architecture™ can bridge the gap between the business language of SQL, the extreme processing power of MapReduce, and the big data residing in Hadoop to provide a unified, high-performance big data analytics system for the enterprise.
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data, big data, unified data architecture, finance
    
Teradata
Published By: Vertica     Published Date: Oct 30, 2009
Independent research firm Knowledge Integrity Inc. examine two high performance computing technologies that are transitioning into the mainstream: high performance massively parallel analytical database management systems (ADBMS) and distributed parallel programming paradigms, such as MapReduce, (Hadoop, Pig, and HDFS, etc.). By providing an overview of both concepts and looking at how the two approaches can be used together, they conclude that combining a high performance batch programming and execution model with an high performance analytical database provides significant business benefits for a number of different types of applications.
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vertica, analytical computing, adbms, mapreduce, application management, data management, data mining, analytical applications, business intelligence, information management, data warehousing
    
Vertica
Published By: IBM     Published Date: Nov 16, 2015
The report is sponsored by vendor firms Actian Corporation, Cloudera, Exasol, IBM, MapR Technologies, MarkLogic, Pentaho, SAS, Talend, and Trillium Software.
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ibm, tdwi, enterprise, information technology, data management, business technology
    
IBM
Published By: RedPoint Global     Published Date: Sep 22, 2014
Download this paper to learn why the power of Hadoop 2.0 lies in enabling applications to run inside Hadoop, without the constraints of MapReduce.
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redpoint, mapreduce, big data, hadoop, data integration, data management, yarn
    
RedPoint Global
Published By: Altiscale     Published Date: Aug 25, 2015
Weren't able to attend Hadoop Summit 2015? No sweat. Learn more about the latest Big Data technologies in these technical presentations at this recent leading industry event. The Big Data experts at Altiscale - the leader in Big Data as a Service - have been busy at conferences. To see all four presentations (in slides and youtube video), click here. https://www.altiscale.com/educational-slide-kit-2015-big-data-conferences-nf/ • Managing Growth in Production Hadoop Deployments • Running Spark & MapReduce Together in Production • YARN and the Docker Ecosystem • 5 Tips for Building a Data Science Platform
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hadoop, hadoop technologies, hadoop information
    
Altiscale
Published By: MapR Technologies     Published Date: Dec 12, 2013
Evaluator Group looks at what will make Hadoop an enterprise data center-grade analytics platform.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
    
MapR Technologies
Published By: MapR Technologies     Published Date: Dec 12, 2013
When used effectively, Hadoop can deliver unparalleled value in revealing new analytics-driven revenue streams, improving customer acquisition and retention, as well as increasing operational efficiencies. The Hadoop Buyer's Guide is an invaluable resource for those investigating or evaluating Hadoop---from understanding how Hadoop can solve your data challenges, to what to look for when selecting a solution, to comparing vendors, and preparing for implementation and future success. Download the guide, and get everything you need to know about choosing the right Hadoop distribution for your business success.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr
    
MapR Technologies
Published By: MapR Technologies     Published Date: Dec 12, 2013
This independent whitepaper from the Kusnetzky Group Analyst describes the promise and challenges surrounding Big Data. It also validates the M7 solution from MapR, which simplifies big data management by consolidating disparate solutions into a single, enterprise-ready platform.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr, analytical applications
    
MapR Technologies
Published 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
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr, infrastructure management
    
MapR Technologies
Published 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.
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big data, big data analytics, hadoop, apache hadoop, structured data, unstructured data, business analytics, metadata, analytics, mapreduce, data, data center, mapr, infrastructure management
    
MapR Technologies
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