apache hadoop

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By: StreamSets     Published Date: Sep 24, 2018
The advent of Apache Hadoop™ has led many organizations to replatform their existing architectures to reduce data management costs and find new ways to unlock the value of their data. One area that benefits from replatforming is the data warehouse. According to research firm Gartner, “starting in 2018, data warehouse managers will benefit from hybrid architectures that eliminate data silos by blending current best practices with ‘big data’ and other emerging technology types.” There’s undoubtedly a lot to ain by modernizing data warehouse architectures to leverage new technologies, however the replatforming process itself can be harder than it would at first appear. Hadoop projects are often taking longer than they need to create the promised benefits, and often times problems can be avoided if you know what to avoid from the onset.
Tags : replatforming, age, data, lake, apache, hadoop
     StreamSets
By: WANdisco     Published Date: Oct 15, 2014
In this Gigaom Research webinar, the panel will discuss how the multi-cluster approach can be implemented in real systems, and whether and how it can be made to work. The panel will also talk about best practices for implementing the approach in organizations.
Tags : wandisco, wan, wide area network, hadoop, clusters, clustering, load balancing, data, big data, data storage, storage
     WANdisco
By: BlueData     Published Date: Mar 13, 2018
In a benchmark study, Intel compared the performance of Big Data workloads running on a bare-metal deployment versus running in Docker containers with the BlueData software platform. This landmark benchmark study used unmodified Apache Hadoop* workloads
Tags : big data, big data analytics, hadoop, apache spark, docker
     BlueData
By: IBM     Published Date: Feb 03, 2016
The more real-time and granular your data is, the more responsive and competitive your organization can become.
Tags : ibm, data management, apache, hadoop, analytics
     IBM
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 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: Hortonworks     Published Date: Apr 05, 2016
Download this whitepaper to learn how Hortonworks Data Platform (HDP), built on Apache Hadoop, offers the ability to capture all structured and emerging types of data, keep it longer, and apply traditional and new analytic engines to drive business value, all in an economically feasible fashion. In particular, organizations are breathing new life into enterprise data warehouse (EDW)-centric data architectures by integrating HDP to take advantage of its capabilities and economics.
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     Hortonworks
By: Altiscale     Published Date: Oct 19, 2015
In this age of Big Data, enterprises are creating and acquiring more data than ever before. To handle the volume, variety, and velocity requirements associated with Big Data, Apache Hadoop and its thriving ecosystem of engines and tools have created a platform for the next generation of data management, operating at a scale that traditional data warehouses cannot match.
Tags : big data, analytics, nexgen, hadoop, apache, networking
     Altiscale
By: Teradata     Published Date: Feb 26, 2013
This report explores the evolution of big data analytics and its maturity within the enterprise. It discusses the approaches and economics to using a Discovery platform and Apache Hadoop within the same unified analytical architecture.
Tags : big data analytics, experiences with teradata, apache hadoop, analytics, discovery platform, apache hadoop, teradata, it management, data management, business technology, data center
     Teradata
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: 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.
Tags : teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, framework, apache, hadoop, architecture, warehouse, optimization, security, scalability, consistency, flexibility, data management
     Teradata
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.
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: 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: Intel     Published Date: Jun 22, 2015
Until recently, we used the Intel® Distribution for Apache Hadoop Software (IDH) to support our original three business intelligence (BI) big data use cases, and it delivered results worth millions of dollars to Intel.
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     Intel
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: 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
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     IBM
By: IBM     Published Date: Apr 29, 2015
IBM InfoSphere BigInsights for Hadoop enables organizations to efficiently manage and mine large volumes of diverse data for valuable insights. IBM builds on a 100% Apache Hadoop foundation with common tools such as spreadsheets, R analytics and SQL access for greater usability.
Tags : bigsheets, data management, business intelligence, workload optimization, data, sql
     IBM
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
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: 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: IBM     Published Date: Feb 03, 2016
Learn why advanced analytics tools are essential to sustain a competitive advantage. This white paper reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics.
Tags : ibm, data management, apache, hadoop, analytics
     IBM
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.
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
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