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New Paradigms for High Performance Analytical Computing

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, grid computing, business analytics, business metrics, linux, analytical applications, business intelligence, information management, data warehousing
    
Vertica

5 Proven Ways To Make Your Online Advertising Technologies Perform Better

Published By: Mirror Image Internet     Published Date: Jun 07, 2012
This white paper discusses 5 sure-fire ways you can make your advertising technologies perform better to deliver significant business value.
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advertising, ad ops, ad tech, display advertising, online advertising, targeting, data, mobile advertising, dsp, rtb, ad networks, ad exchanges, iab, banner ads, clickthrough, pixel, pixel tracking, mobile device detection, video advertising, interactive advertising
    
Mirror Image Internet

Gain Business Value With The "Perfect Fit" Cloud Analytics Solution

Published By: Teradata     Published Date: Jan 22, 2014
Today's agile businesses are seeking to expand analytics fast, gain flexible analytic deployment options and smooth cash flows. Download this paper to learn how Teradata understands these needs and has engineered a cloud solution that meets organizations' analytic needs.
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cloud analytics, hadoop, analytics, cloud-based analytics, data warehousing, discovery capabilities, data management, cloud computing, infrastructure
    
Teradata

FlexPod Select with Hadoop - Validated Designs From NetApp and Cisco

Published By: NetApp     Published Date: Sep 19, 2013
Learn about FlexPod Select with Hadoop and how this enterprise class Hadoop has validated, pre-configured components that allow for faster deployment, higher reliability, and smoother integration with your existing applications and infrastructure.
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flexpod select, hadoop, netapp, cisco, validated designs, cloudera, hortonworks, data, multi-structured data, application integration, analytical applications, business intelligence, database development, data integration, data quality, data warehousing
    
NetApp

NetApp Open Solution for Hadoop Solutions Guide

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, application integration, analytical applications, business intelligence, configuration management, data integration, data quality, web service management, data warehousing
    
NetApp

ESG Lab Report Validation of NetApp Open Solution for Hadoop

Published By: NetApp     Published Date: Dec 12, 2013
Learn why NetApp Open Solution for Hadoop is better than clusters built on commodity storage. This ESG lab report details the reasons why NetApp's use of direct attached storage for Hadoop improves performance, scalability and availability compared to typical internal hard drive Hadoop deployments.
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netapp, lab validation, distibuted content repositor, big content scalability, enterprise reliability, intelligent object management, application integration, business intelligence, data integration, virtualization, cloud computing
    
NetApp

The State of the Data Warehouse - A Survey of Data Professionals conducted by Dimensional Research

Published By: Snowflake     Published Date: Apr 14, 2015
Find out why data professionals are NOT replacing their data warehouse with Hadoop—read the survey
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dimensional research, data professionals, data warehouse, cloud computing, big data, new technology, human resources services, virtualization
    
Snowflake

Who's Big on Big Data?

Published By: Platfora     Published Date: Aug 03, 2015
A survey of more than 395 C-level executives, sponsored by Platfora, shows that senior leaders are optimistic about the capabilities of big data, but many still struggle with big data applications.
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platfora, big data, hadoop, data center, big data analytics, network management, servers, blade servers, server virtualization, analytical applications, data deduplication, cloud computing, data center design and management, infrastructure management
    
Platfora

The Forrester Wave: Enterprise Data Warehouse

Published By: SnowFlake     Published Date: Jul 08, 2016
In the era of big data, enterprise data warehouse (EDW) technology continues to evolve as vendors focus on innovation and advanced features around in-memory, compression, security, and tighter integration with Hadoop, NoSQL, and cloud. Forrester identified the 10 most significant EDW software and services providers — Actian, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), IBM, Microsoft, Oracle, Pivotal Software, SAP, Snowflake Computing, and Teradata — in the category and researched, analyzed, and scored them. This report details our findings about how well each vendor fulfills our criteria and where they stand in relation to each other to help enterprise architect professionals select the right solution to support their data warehouse platform.
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forrester, enterprise, data, technology, best practices, innovation, security, business integration, business intelligence, business technology
    
SnowFlake

Data Lakes, Purposes, Practices, Patterns and Platforms

Published By: SAS     Published Date: Mar 06, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
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SAS

How to Use Hadoop as a Piece of the Big Data Puzzle

Published By: SAS     Published Date: Sep 13, 2013
Insights from a webinar in the Applying Business Analytics Webinar Series
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sas, hadoop, big data, software framework, webinar, business analytics webinar series, software development, it management
    
SAS

O’Reilly eBook: Designing Data Intensive Applications

Published By: Pentaho     Published Date: Jan 16, 2015
Download if you need to make decisions about the architecture of the systems you work on. Sponsored by Pentaho.
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embedded, big data, nosql, hadoop, customer analytics, data integration, data delivery, data management, business intelligence, data center
    
Pentaho

O’Reilly eBook: Field Guide to Hadoop

Published By: Pentaho     Published Date: Jan 16, 2015
This ebook is recommended for IT managers, developers, data analysts, system architects, and similar technical workers, who are faced with having to replace current systems and skills with the new set required by NoSQL and Hadoop, or those who want to deepen their understanding of complementary technologies and databases. Sponsored by Pentaho.
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big data, hadoop, data delivery, data management, business intelligence, data center
    
Pentaho

Splice Machine: SQL-on-Hadoop® Evaluation Guide

Published By: Splice Machine     Published Date: Feb 17, 2014
Hadoop has become popular to store massive data sets because it can distribute them across inexpensive commodity servers. Click here to learn more from this free report.
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big data, hadoop, data centers, massive data, servers, virutalization, blades, cloud, splice, splice machine, backup and recovery, blade servers, storage management, storage virtualization, cloud computing, data center design and management, colocation and web hosting
    
Splice Machine

The Big Deal about Big SQL? Introducing Relational DBMS Users to IBM SQL Technology for Hadoop

Published By: IBM     Published Date: May 02, 2014
This paper introduces you to Big SQL, answering many of the common questions that relational database management system (DBMS) users have about this IBM technology.
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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, it management, application performance management, best practices, change management
    
IBM

Architecting a Big Data Platform for Analytics by Mike Ferguson

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, best practices, business intelligence
    
IBM

Making the case for data lifecycle management

Published By: IBM     Published Date: May 28, 2014
Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.
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ibm, data lifecycle management, infosphere optim, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence, virtualize data, lifecycle management
    
IBM

Business Driven Governance: Managing Policies for Data Retention

Published By: IBM     Published Date: May 28, 2014
Different types of data have different data retention requirements. In establishing information governance and database archiving policies, take a holistic approach by understanding where the data exists, classifying the data, and archiving the data. IBM InfoSphere Optim™ Archive solution can help enterprises manage and support data retention policies by archiving historical data and storing that data in its original business context, all while controlling growing data volumes and improving application performance. This approach helps support long-term data retention by archiving data in a way that allows it to be accessed independently of the original application.
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ibm, data retention, information governance, archiving, historical data, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence
    
IBM

Big Data Integration and Governance Considerations for Healthcare

Published By: IBM     Published Date: Aug 05, 2014
There is a lot of discussion in the press about Big Data. Big Data is traditionally defined in terms of the three V’s of Volume, Velocity, and Variety. In other words, Big Data is often characterized as high-volume, streaming, and including semi-structured and unstructured formats. Healthcare organizations have produced enormous volumes of unstructured data, such as the notes by physicians and nurses in electronic medical records (EMRs). In addition, healthcare organizations produce streaming data, such as from patient monitoring devices. Now, thanks to emerging technologies such as Hadoop and streams, healthcare organizations are in a position to harness this Big Data to reduce costs and improve patient outcomes. However, this Big Data has profound implications from an Information Governance perspective. In this white paper, we discuss Big Data Governance from the standpoint of three case studies.
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ibm, data, big data, information, healthcare, governance, technology, it management, data management
    
IBM

Addressing Customer Analytics With Effective Data Matching

Published By: IBM     Published Date: Jan 09, 2015
With the advent of big data, organizations worldwide are attempting to use data and analytics to solve problems previously out of their reach. Many are applying big data and analytics to create competitive advantage within their markets, often focusing on building a thorough understanding of their customer base.
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ibm, big data, insights, infosphere, data management, dashboards, value, data matching, analytics, challenges, hadoop, knowledge management, business technology
    
IBM

Hadoop for the Enterprise

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

Scaling Data Integration to Handle Big Data

Published By: IBM     Published Date: Jan 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.
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ibm, data integration, infosphere, information server, partition, data profiling, knowledge management, data management, business technology, data center
    
IBM

Seven Reasons You Need Predictive Analytics Today

Published 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.
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ibm, data management, apache, hadoop, analytics
    
IBM

Big computing for big data: Ignite your predictive analytics with Spark

Published 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.
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ibm, data management, apache, hadoop, analytics
    
IBM
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