hadoop solutions

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Published By: Dell EMC     Published Date: Oct 08, 2015
This paper discusses how the many Dell | Cloudera Hadoop solutions help organizations of all sizes, and with a variety of needs and use cases, tackle their big data requirements.
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Dell EMC
Published By: IBM     Published Date: Apr 19, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. 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. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, data management
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. 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. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, knowledge management, data management, data center
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. 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. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, data management, business technology, data center
    
IBM
Published By: Splunk     Published Date: Sep 17, 2012
Splunk has become a critical real-time monitoring and analytics tool for Bronto. Read more about Bronto Software's hard and soft ROI's by using Splunk versus extending their Hadoop deployment.
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roi, enterprise management associates, real time monitoring, analytics, hadoop, email delivery system, enterprise business solutions, data management, business technology
    
Splunk
Published By: Snowflake     Published Date: Jan 25, 2018
Compared with implementing and managing Hadoop (a traditional on-premises data warehouse) a data warehouse built for the cloud can deliver a multitude of unique benefits. The question is, can enterprises get the processing potential of Hadoop and the best of traditional data warehousing, and still benefit from related emerging technologies? Read this eBook to see how modern cloud data warehousing presents a dramatically simpler but more power approach than both Hadoop and traditional on-premises or “cloud-washed” data warehouse solutions.
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Snowflake
Published By: Enterprise Management Associates     Published Date: Aug 25, 2015
This webinar talks about various issues organization's deal with on a daily basis and how Hadoop can offer solutions.
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ema, hadoop, big data analytics, predictive insights, data lake architecture, hadoop adoption, enterprise management, business intelligence, data warehousing, data integration, data visualization, data analyst
    
Enterprise Management Associates
Published By: NetApp     Published Date: Sep 19, 2013
Download this solutions guide to get a technical overview on building Hadoop on NetApp E-series storage and learn how it will effectively help deliver big analytics with pre-engineered, compatible, and supported solutions ultimately reducing the cost, schedule, and risk of do-it-yourself systems.
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netapp, open solution, hadoop, solutions guide, e-series storage, big analytics, big data
    
NetApp
Published By: IBM     Published Date: May 02, 2014
These traditional analytical systems are often based on a classic pattern where data from multiple operational systems is captured, cleaned, transformed and integrated before loading it into a data warehouse.
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ibm, big data platform, architecting big data, analytics, intelligent business strategies, data complexity, data types, workload growth, workload complexity, big data analytic applications, operational decisions, multi-structured data, querying data, scalable data management, analytical ecosystem, hadoop solutions, it management, data management, data center
    
IBM
Published By: Altiscale     Published Date: Dec 16, 2014
This webinar will explore the merits of the Hadoop SaaS approach, relative to competing cloud and on-premise Hadoop solutions that exist today.
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altiscale, hadoop, saas, hadoop saas, cloud service
    
Altiscale
Published By: SAS     Published Date: Apr 25, 2017
Organizations in pursuit of data-driven goals are seeking to extend and expand business intelligence (BI) and analytics to more users and functions. Users want to tap new data sources, including Hadoop files. However, organizations are feeling pain because as the data becomes more challenging, data preparation processes are getting longer, more complex, and more inefficient. They also demand too much IT involvement. New technology solutions and practices are providing alternatives that increase self-service data preparation, address inefficiencies, and make it easier to work with Hadoop data lakes. This report will examine organizations’ challenges with data preparation and discuss technologies and best practices for making improvements.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Want to get even more value from your Hadoop implementation? Hadoop is an open-source software framework for running applications on large clusters of commodity hardware. As a result, it delivers fast processing and the ability to handle virtually limitless concurrent tasks and jobs, making it a remarkably low-cost complement to a traditional enterprise data infrastructure. This white paper presents the SAS portfolio of solutions that enable you to bring the full power of business analytics to Hadoop. These solutions span the entire analytic life cycle – from data management to data exploration, model development and deployment.
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SAS
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