hadoop

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By: BMC Software     Published Date: May 28, 2014
Learn how BMC Control-M for for Hadoop allows IT to extract value from big data, with clear visibility, predictability and increased productivity and efficiency.
Tags : it management, enterprise applications
     BMC Software
By: BMC Software     Published Date: May 28, 2014
"In the paper, “Integrate Big Data into Your Business Processes and Enterprise Systems” you’ll learn how to drive maximum value with an enterprise approach to Big Data. Topics discussed include: • How to ensure that your Big Data projects will drive clearly defined business value • The operational challenges each Big Data initiative must address • The importance of using an enterprise approach for Hadoop batch processing
Tags : it management
     BMC Software
By: BMC Software     Published Date: May 28, 2014
This paper, "Workload Automation – From Application Development to Digital Service Delivery," describes how a workload automation solution can eliminate the manual processes developers now use to define batch workflows and communicate them to schedulers.By extending the use of workload automation to developers, organizations can implement applications faster, slash costs, and increase service quality.
Tags : big data, hadoop, it management, enterprise applications, business technology
     BMC Software
By: TIBCO Software APAC     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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     TIBCO Software APAC
By: Attunity     Published Date: Jan 14, 2019
This whitepaper explores how to automate your data lake pipeline to address common challenges including how to prevent data lakes from devolving into useless data swamps and how to deliver analytics-ready data via automation. Read Increase Data Lake ROI with Streaming Data Pipelines to learn about: • Common data lake origins and challenges including integrating diverse data from multiple data source platforms, including lakes on premises and in the cloud. • Delivering real-time integration, with change data capture (CDC) technology that integrates live transactions with the data lake. • Rethinking the data lake with multi-stage methodology, continuous data ingestion and merging processes that assemble a historical data store. • Leveraging a scalable and autonomous streaming data pipeline to deliver analytics-ready data sets for better business insights. Read this Attunity whitepaper now to get ahead on your data lake strategy in 2019.
Tags : data lake, data pipeline, change data capture, data swamp, hybrid data integration, data ingestion, streaming data, real-time data, big data, hadoop, agile analytics, cloud data lake, cloud data warehouse, data lake ingestion, data ingestion
     Attunity
By: IBM     Published Date: May 17, 2016
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
Tags : ibm, big data, inline analytics, business analytics, roi
     IBM
By: SAS     Published Date: Apr 20, 2015
This conclusions paper introduces key machine learning concepts and describes new SAS solutions – SAS In-Memory Statistics for Hadoop and SAS Visual Statistics – that enable machine learning at scale.
Tags : 
     SAS
By: IBM     Published Date: Feb 22, 2016
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.
Tags : ibm, data, big data, integration, hadoop, enterprise applications, data management, business technology
     IBM
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?
Tags : ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, data management
     IBM
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
By: IBM     Published Date: Oct 13, 2016
IBM InfoSphere Information Server connects to many new ‘at rest’ and streaming big data sources, scales natively on Hadoop using partition and pipeline parallelism, automates data profiling, provides a business glossary, and an information catalog, plus also supports IT.
Tags : ibm, data, analytics, big data, data integration, data management, business technology, data center
     IBM
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, enterprise applications, data management, business technology, data center
     IBM
By: IBM     Published Date: Oct 13, 2016
This e-book highlights the benefits of Hadoop across several industries and explores how IBM® Biglnsights for Apache™ Hadoop® combines open source Hadoop with enterprise-grade management and analytic capabilities.
Tags : ibm, analytics, big data, hadoop, enterprise, ibm biginsights, apache, enterprise management, enterprise applications, data management, business technology
     IBM
By: IBM     Published Date: Jan 27, 2017
As with most innovations in business information technology, the ultimate truth about cloud lies somewhere in between. There is little doubt that cloud-based infrastructures offer an immediate opportunity for smaller organizations to avoid the costly investment needed for a robust on-premises computing environment. Data can be found, processed and managed on the cloud without investing in any local hardware. Large organizations with mature on-premises computing infrastructures are looking to Hadoop platforms to help them benefit from the vast array of structured and unstructured data from cloud-based sources. Organizations have feet in both cloud and on-premises worlds. In fact, one could easily argue that we already live in a “hybrid” world.
Tags : 
     IBM
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.
Tags : 
     IBM
By: IBM     Published Date: Jan 27, 2017
Companies today increasingly look for ways to house multiple disparate forms forms of data under the same roof, maintaining original integrity and attributes. Enter the Hadoop-based data lake. While a traditional on-premise data lake might address the immediate needs for scalability and flexibility, research suggests that it may fall short in supporting key aspects of the user experience. This Knowledge Brief investigates the impact of a data lake maintained in a cloud or hybrid infrastructure.
Tags : 
     IBM
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.
Tags : data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
     IBM
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.
Tags : hadoop, flexibility, scalability, data architecture
     IBM
By: IBM     Published Date: Jul 06, 2017
Companies today increasingly look for ways to house multiple disparate forms of data under the same roof, maintaining original integrity and attributes. Enter the Hadoop-based data lake. While a traditional on-premise data lake might address the immediate needs for scalability and flexibility, research suggests that it may fall short in supporting key aspects of the user experience. This Knowledge Brief investigate the impact of a data lake maintained in a cloud or hybrid infrastucture.
Tags : data lake, user experience, knowledge brief, cloud infrastructure
     IBM
By: IBM     Published Date: Jul 06, 2017
Known by its iconic yellow elephant, Apache Hadoop is purpose-built to help companies manage and extract insight from complex and diverse data environments. The scalability and flexibility of Hadoop might be appealing to the typical CIO but Aberdeen's research shows a variety of enticing business-friendly benefits.
Tags : data management, yellow elephant, business benefits, information management
     IBM
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.
Tags : big data, data integration, bi systems, hadoop
     Pentaho
By: Pentaho     Published Date: Aug 22, 2016
This white paper covers six guidelines product leaders should explore during their embedded analytics evaluation.
Tags : big data, data integration, bi systems, hadoop
     Pentaho
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.
Tags : data, big data, unified data architecture
     Teradata
By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Our recent primary research project solicited feedback from respondents to determine familiarity with, and plans for use of Hadoop ecosystem components. Download this white paper to learn more.
Tags : 
     Waterline Data & Research Partners
By: IBM     Published Date: Jul 05, 2016
This e-book highlights the benefits of Hadoop across several industries and explores how IBM® Biglnsights for Apache™ Hadoop® combines open source Hadoop with enterprise-grade management and analytic capabilities.
Tags : ibm, analytics, big data, hadoop, enterprise, ibm biginsights, apache, enterprise management, knowledge management, enterprise applications, data management
     IBM
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