big data integration

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Aberdeen Customer Derivative

Published By: Adobe     Published Date: Nov 07, 2013
Aberdeen's Insights provide the analyst's perspective on the research as drawn from an aggregated view of research surveys, interviews, and data analysis.
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adobe, aberdeen group, analyst insight, technology tools, buying behavior, customer experience management, cem, buyer interactions, customer engagement programs, adobe customers outperform, company brand awareness, big data, structured data, data quality, data integration, customer segmentation, customer empowerment, quality of service, content management
    
Adobe

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 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

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

The Evolution of Big Data

Published By: Datastax     Published Date: Apr 04, 2017
As the big data ecosystem continues to expand, new technologies are addressing the requirements for managing, processing, analyzing, and storing data to help companies benefit from the rich sources of information flowing into their organizations. From NoSQL databases to open source projects to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance, and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
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evolution, big data, technology, datastax, nosql
    
Datastax

Cloud For Dummies E-Book

Published By: Group M_IBM Q418     Published Date: Oct 02, 2018
Organizations are faced with providing secure authentication, authorization, and Single Sign On (SSO) access to thousands of users accessing hundreds of disparate applications. Ensuring that each user has only the necessary and authorized permissions, managing the user’s identity throughout its life cycle, and maintaining regulatory compliance and auditing further adds to the complexity. These daunting challenges are solved by Identity and Access Management (IAM) software. Traditional IAM supports on-premises applications, but its ability to support Software-as-a-Service (SaaS)-based applications, mobile computing, and new technologies such as Big Data, analytics, and the Internet of Things (IoT) is limited. Supporting on-premises IAM is expensive, complex, and time-consuming, and frequently incurs security gaps. Identity as a Service (IDaaS) is an SaaS-based IAM solution deployed from the cloud. By providing seamless SSO integration to legacy on-premises applications and modern cloud-
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Group M_IBM Q418

The Big Data Zoo —Taming the Beasts

Published By: IBM     Published Date: Sep 27, 2013
With so much talk about big data and the possibilities it can offer, the truth behind what big data is—and what it can do for businesses—can be hard to determine. However, according to Dr. Barry Devlin of 9sight Consulting, the truth behind all the talk is not hard to see, provided that organizations are willing to return to the principles of good data management processes. According to Dr. Devlin’s white paper “The Big Data Zoo—Taming the Beasts”, data is still data, whether big or small. It needs to be managed effectively if organizations want to be gain value from it. Although big data may present special challenges for IT organizations, the principles of data management haven’t changed.
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big data, data management, data warehousing, data analysis, platform integration, it management, enterprise applications, platforms, business technology
    
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, software, automation, it management, enterprise applications
    
IBM

Analytics: The real-world use of Big Data

Published By: IBM     Published Date: Jan 02, 2014
This study highlights the phases of the big data journey, the objectives and challenges of midsize organizations taking the journey, and the current state of the technology that they are using to drive results. It also offers a pragmatic course of action for midsize companies to take as they dive into this new era of computing.
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ibm, analytics, global business service, big data, business value, it professionals, volume, velocity, variety, customer analytics, trends and insights, information management, data security, integration, variety of data, analytic accelerator, infrastructure, data management, identity management, application integration
    
IBM

The Big Data Zoo—Taming the Beasts

Published By: IBM     Published Date: Jan 09, 2014
According to Dr. Barry Devlin of 9sight Consulting, the truth behind all the talk about big data and the possibilities it can offer is not hard to see, provided that organizations are willing to return to the principles of good data management processes.
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ibm, big data, 9sight consulting, data, it management, maximize business, deployment, business opportunities, big data usage, data warehouse, data center, business analytics, big data offerings, core business data, analytic data, puredata system, data virtualization, data integration, data types, data quality
    
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, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence, virtualize data, it management, data management, business intelligence
    
IBM

The Fundamentals of Data Lifecycle Management in the Era of Big Data

Published By: IBM     Published Date: May 02, 2014
This eBookoutlines the best practices for data lifecycle management and how InfoSphere Optimsolutions enable organizations to support and implement them.
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ibm, 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, big data strategy, it management
    
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, policy rates, customer retention, claims data, transaction data
    
IBM

Digital reinvention - Trust, transparency and technology in the insurance world of tomorrow

Published By: IBM     Published Date: May 27, 2014
If insurers want to succeed in today's digital world, they need to create experiences and business models that are orchestrated, symbiotic, contextual and cognitive.
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ibm, big data, insurance, digital insurer, business model, insurance industry, technology, integration, social business, it management
    
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

Back to basics: Fundamentals of test data management

Published By: IBM     Published Date: May 28, 2014
The right test data management solution accelerates time to value for business-critical applications and builds relationships and efficiencies across the organization. IBM InfoSphere Optim Test Data Management closes the gap between DBAs and application developers by providing all teams with accurate, appropriately masked and protected data for their work. Developers can confirm that new application functionalities perform as expected. QA staff can validate that the application performs as intended based on the test cases, and that integrations work properly. And business leaders can be more confident that competitive functionality will be delivered on time with less risk.
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ibm, ibm infosphere, ibm optim solutions, ibm test data, test data management, dba, database management, big data, applications, business critical applications, integrations, it management, data management, business technology, data center
    
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

Big Data Integration and Governance Considerations for Healthcare

Published By: IBM     Published Date: Oct 01, 2014
This white paper discusses how IBM InfoSphere can support the integration and governance of Big Data in healthcare. The white paper reviews three case studies including predictive analytics with Electronic Medical Records, time series data in a neonatal intensive care unit and predictive pathways for disease.
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big data, data integration, healthcare, data management, business activity monitoring, business analytics
    
IBM

Addressing customer analytics with effective data matching

Published By: IBM     Published Date: Nov 06, 2014
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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big data, data integration, analytics, customer matching, ibm, networking, data management, data center, research
    
IBM

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, infrastructure, mobile computing, mobile data systems, best practices, server virtualization, data integration, data center design and management, infrastructure management
    
IBM

Who's afraid of the big (data) bad wolf? Survive the big data storm by getting ahead of integration

Published By: IBM     Published Date: Jul 08, 2015
Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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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

Who's afraid of the big (data) bad wolf? Survive the big data storm by getting ahead of integration

Published By: IBM     Published Date: Oct 19, 2015
This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
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ibm, integration, data volume, business technology, information, it management, knowledge management, data management
    
IBM
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