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Published By: Adobe     Published Date: Aug 02, 2017
With Adobe Analytics and Adobe Audience Manager—both part of Adobe Marketing Cloud—media companies can overcome today’s audience intelligence challenges. Adobe Analytics is an industry-leading solution for applying real time analytics and detailed segmentation across all of your marketing channels. A unified platform and customer ID unlock powerful customer intelligence and help you discover and retain high-value audiences. Make forward-looking decisions with its predictive intelligence capabilities, and find out which of your marketing efforts are paying off with its attribution functionality.
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goals and kpis, data warehouse, resource management, insight loop, content and campaigns, audience optimisation
    
Adobe
Published 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.
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big data, analytics, nexgen, hadoop, apache, networking
    
Altiscale
Published By: Amazon Web Services     Published Date: Jun 20, 2018
Data and analytics have become an indispensable part of gaining and keeping a competitive edge. But many legacy data warehouses introduce a new challenge for organizations trying to manage large data sets: only a fraction of their data is ever made available for analysis. We call this the “dark data” problem: companies know there is value in the data they collected, but their existing data warehouse is too complex, too slow, and just too expensive to use. A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated q
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Aug 20, 2018
A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 04, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technology
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Amazon Web Services
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
Published By: Amazon Web Services     Published Date: Sep 05, 2018
AbeBooks, with Amazon Redshift, has been able to upgrade to a comprehensive data warehouse with the enlistment of Matillion ETL for Amazon Redshift. In this case study, we share AbeBooks’ data warehouse success story.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
IDC’s research has shown the movement of most IT workloads to the cloud in the coming years. Yet, with all the talk about enterprises moving to the cloud, some of them still wonder if such a move is really cost effective and what business benefits may result. While the answers to such questions vary from workload to workload, one area attracting particular attention is that of the data warehouse. Many enterprises have substantial investments in data warehousing, with an ongoing cost to managing that resource in terms of software licensing, maintenance fees, operational costs, and hardware. Can it make sense to move to a cloud-based alternative? What are the costs and benefits? How soon can such a move pay itself off? Download now to find out more.
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Amazon Web Services
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Die Recherchen von IDC haben ergeben, dass in den nächsten Jahren die meisten IT-Workloads in die Cloud verschoben werden. Doch neben all den positiven Berichten über Unternehmen, die in die Cloud umziehen, gibt es auch Unternehmen, die sich noch immer fragen, ob ein solcher Wechsel wirklich kosteneffizient ist und welche Vorteile sich aus einem solchen ergeben. Während die Antworten auf solche Fragen von Workload zu Workload variieren, gibt es ein Element, das besondere Aufmerksamkeit auf sich zieht: das Data-Warehouse.
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Amazon Web Services
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
Tags : 
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 05, 2018
AbeBooks, with Amazon Redshift, has been able to upgrade to a comprehensive data warehouse with the enlistment of Matillion ETL for Amazon Redshift. In this case study, we share AbeBooks’ data warehouse success story.
Tags : 
    
Amazon Web Services
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technolog
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Amazon Web Services
Published By: Attivio     Published Date: Aug 20, 2010
With the explosion of unstructured content, the data warehouse is under siege. In this paper, Dr. Barry Devlin discusses data and content as two ends of a continuum, and explores the depth of integration required for meaningful business value.
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attivio, data warehouse, unified information, data, content, unstructured content, integration, clob, blob, business intelligence, data quality, data warehousing
    
Attivio
Published By: Attivio     Published Date: Aug 20, 2010
Current methods for accessing complex, distributed information delay decisions and, even worse, provide incomplete insight. This paper details the impact of Unified Information Access (UIA) in improving the agility of information-driven business processes by bridging information silos to unite content and data in one index to power solutions and applications that offer more complete insight.
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attivio, data warehouse, unified information, data, content, unstructured content, integration, clob, blob, data warehousing
    
Attivio
Published By: Aventail     Published Date: Oct 26, 2007
The goal of pervasive BI applications is to take the data that produced the back office ROI of more than 400% and deliver it to front-line employees in a form appropriate to their job functions – with similar results. There are thousands of business process steps in a typical enterprise where pervasive BI insights can be added. What are leading companies doing with pervasive BI?
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business intelligence, database, enterprise data warehouse, data mart, data warehouse, data mining, active data warehousing, active data warehouse, informatica
    
Aventail
Published By: AWS - ROI DNA     Published Date: Jun 12, 2018
Traditional databases and data warehouses are evolving to capture new data types and spread their capabilities in a hybrid cloud architecture, allowing business users to get the same results regardless of where the data resides. The details of the underlying infrastructure become invisible. Self-managing data lakes automate the provisioning, reliability, performance and cost, enabling data access and experimentation.
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AWS - ROI DNA
Published By: CA Technologies EMEA     Published Date: Aug 03, 2017
Tenuto conto del fatto che la GDPR è stato annunciato formalmente solo di recente, si evidenzia un buon livello di consapevolezza tra i partecipanti. Una volta informati sul regolamento, l'88% degli intervistati ha dichiarato che la propria azienda deve affrontare difficoltà tecnologiche per la compliance alla GDPR. Il percorso verso la compliance è percepito come molto laborioso.
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generazione di dati sintetici, virtualizzazione di servizi, controllo e protezione dei database, masking dei dati, warehouse dei dati, ca technologies, gdpr
    
CA Technologies EMEA
Published By: Calpont     Published Date: Mar 13, 2012
In this white paper you will find insight as to how the Calpont InfiniDB database performs far beyond the abilities of a row-based database.
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data warehouse, warehouse, benhcmark, infinidb, calpont, row-based, warehouse, mpp, parallel processing, columns, rows, column, row, data management
    
Calpont
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