big data integration

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Forrester Webinar Series (Recorded Feb-March 2013)

Published By: TIBCO     Published Date: May 15, 2013
•Big Data + Integration •Integration In the Age of The Customer •Impact of Mobile
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big data, architecture, mobile, integration, customer, webinar, application integration, application performance management
    
TIBCO

Gartner MQ For DI

Published By: IBM     Published Date: Apr 18, 2017
The data integration tool market was worth approximately $2.8 billion in constant currency at the end of 2015, an increase of 10.5% from the end of 2014. The discipline of data integration comprises the practices, architectural techniques and tools that ingest, transform, combine and provision data across the spectrum of information types in the enterprise and beyond — to meet the data consumption requirements of all applications and business processes. The biggest changes in the market from 2015 are the increased demand for data virtualization, the growing use of data integration tools to combine "data lakes" with existing integration solutions, and the overall expectation that data integration will become cloud- and on-premises-agnostic.
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data integration, data security, data optimization, data virtualization, database security, data analytics, data innovation
    
IBM

Harnessing the power of big data and analytics for insurance

Published By: IBM     Published Date: May 27, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media
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ibm, big data, analytics, insurance, insurance industry, big data solutions, integration, risk assessment
    
IBM

How to Enable High-Performance ELT Processing

Published By: AWS     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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AWS

How to Enable High-Performance ELT Processing

Published By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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Amazon Web Services

How YARN Opens Doors to Easier Programming Tools for Hadoop 2.0 Users

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, network management
    
RedPoint Global

IBM BigInsights BigIntegrate and BigQuality: Information Empowerment for Your Big Data Ecosystem

Published By: IBM     Published Date: Jan 14, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
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ibm, biginsights, bigintegrate, bigquality, data, ecosystem, governance, integration
    
IBM

IBM BigInsights BigIntegrate and BigQuality: Information Empowerment for Your Big Data Ecosystem

Published By: IBM     Published Date: Apr 18, 2016
"Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need."
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ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality
    
IBM

IBM BigInsights BigIntegrate and BigQuality: Information Empowerment for Your Big Data Ecosystem

Published By: IBM     Published Date: Jul 06, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
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ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality
    
IBM

IBM Information Governance Catalog

Published By: IBM     Published Date: Jul 05, 2018
IBM® Information Governance Catalog helps you understand your information and foster collaboration between business and IT by establishing a common business vocabulary on the front end, and managing data lineage on the back end. By leveraging the comprehensive capabilities in Information Governance Catalog, you are better able to align IT with your business goals. Information Governance Catalog helps organizations build and maintain a strong data governance and stewardship program that can turn data into trusted information. This trusted information can be leveraged in various information integration and governance projects, including big data integration, master data management (MDM), lifecycle management, and security and privacy initiatives. In addition, Information Governance Catalog allows business users to play an active role in information-centric projects and to collaborate with their IT teams without the need for technical training. This level of governance and collaboration c
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IBM

IBM PureData for Transactions Overview

Published By: IBM     Published Date: Dec 18, 2013
Learn about 3 optimizations of IBM PureData System for Transactions that can help your organization meet today's big data challenges.
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ibm, ibm puredata for transactions, data, big data, data center, data management, optimization, integration
    
IBM

Information Empowerment for Your Evolving Data Ecosystem

Published By: IBM     Published Date: Apr 18, 2016
By using InfoSphere 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.
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ibm, big data, ibm infosphere, information empowerment, data integration, data management
    
IBM

Integrating and Governing Big Data

Published By: IBM     Published Date: May 02, 2014
The end-to-end information integration capabilities of IBM® InfoSphere® Information Server are designed to help organizations understand, cleanse, monitor, transform and deliver data—as well as collaborate to bridge the gap between business and IT.
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ibm, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility
    
IBM

Integrating and governing big data

Published By: IBM     Published Date: Feb 22, 2016
IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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ibm, data, big data, integration, governance, iig, infosphere, enterprise applications
    
IBM

Integrating and governing Big Data: Does Big data spell big trouble for integration

Published By: IBM     Published Date: Jul 08, 2015
While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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IBM

Integrating Hadoop into BI and Data Warehousing – Best Practices Report

Published By: Pentaho     Published Date: Feb 26, 2015
This TDWI Best Practices report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies.
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big data, big data analytics, data warehousing technologies, data storage, business intelligence, data integration, enterprise applications, data management
    
Pentaho

Integration von Big Data in Geschäftsprozesse und Unternehmenssysteme

Published By: BMC Software     Published Date: Jul 22, 2015
Integrieren Sie Ihrer Big Data Initiativen in Ihre Unternehmensweiten Geschäftsprozesse. Gerne machen wir Sie damit vertraut, wie sie mit Control-M für Hadoop die Anwendungsentwicklung beschleunigen und die Unternehmensintegration vereinfachen können. Besprochene Themen schließen folgende Punkte ein: * Wie können Sie mit einem Enterprise Scheduler für Hadoop, weitere Automationsinseln vermeiden. * Wie kann sichergestellt werden, dass Sie aus ihren Big Data Initiativen den gewünschten Mehrwert erhalten. * Wie können Sie mit Ihren Big Data initiativen sich den administrativen Herausforderungen & Bedürfnissen stellen und mögliche Konfrontationen erfolgreich meistern.
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BMC Software

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

On Demand: Taming the Beast: Extracting Value from Hadoop

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
    
Enterprise Management Associates

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
    
Pentaho

Redefining networks for cloud, analytics, mobile, social and security

Published By: IBM     Published Date: Jun 16, 2015
This paper explores the implications of cloud, big data and analytics, mobile, social business and the evolving IT security landscape on data center and enterprise networks and the changes that organizations will need to make in order to capitalize on these technology force.
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cloud computing, mobility, big data, business analytics, it security landscape, enterprise networks, cloud integration, virtualization
    
IBM

Scaling Data Integration to Handle Big Data

Published 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.
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ibm, data, analytics, big data, data integration, data management, business technology, data center
    
IBM

Scaling Data Integration to Handle Big Data

Published By: IBM     Published Date: Oct 03, 2017
The demand for new data about customers, customer behaviour, product usage, asset performance, and operational processes is growing rapidly. Almost every industry wants new data. Some examples of this are: • Financial services organisations want more data to improve risk decisions, for ‘Know Your Customer (KYC) compliance and for a 360 degree view of financial crime. • Utilities companies want smart meter data to give them deeper understanding of customer and grid usage and to allow them to exploit pricing elasticity. They also want sensor data to monitor grid health, to optimise field service and manage assets. Download now to learn more!
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scaling data, big data, customer behavior, product usage, data integration
    
IBM

Seven principles for achieving high performance and scalability for information integration

Published By: IBM     Published Date: Jul 26, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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scalability, data warehousing, resource planning
    
IBM

Seven Principles for Achieving High Performance and Scalability for Information Integration

Published By: IBM     Published Date: Oct 17, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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IBM
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