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business intelligence data warehouse

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Published By: Oracle EMEA     Published Date: Apr 15, 2019
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; it’s a whole new approach to getting more value from your data. Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results. Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployed—either on premises or in the cloud—they face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets. Oracle has a better way. Download this whitepaper to f
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Oracle EMEA
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
Published By: Teradata     Published Date: Jan 28, 2015
Althrough Hadoop and related technologies have been with us for several years, most business intelligence (BI) professionals and their business counterparts still harbor a few misconceptions that need to be corrected about Hadoop and related technologies such as MapReduce. This webcast presents the 10 most common myths about Hadoop, then corrects them. The goal is to clarify what Hadoop is and does relative to BI, as well as in which business and technology situations Hadoop-based BI, data warehousing and analytics can be useful.
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teradata, business, intelligence, hadoop, data, integration, analytics, mapreduce, warehouse
    
Teradata
Published By: Attunity     Published Date: Feb 12, 2019
Read this checklist report, with results based on the Eckerson Group’s survey and the Business Application Research Center (BARC), on how companies using the cloud for data warehousing and BI has increased by nearly 50%. BI teams must address multiple issues including data delivery, security, portability and more before moving to the cloud for its infinite scalability and elasticity. Read this report to understand all 7 seven considerations – what, how and why they impact the decision to move to the cloud.
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cloud, business intelligence, analytics, cloud data, data lake, data warehouse automation tools, dwa, data warehouse, security and compliance, data movement, hybrid cloud, hybrid cloud environment, cross-platform automation, portability
    
Attunity
Published By: EMC Corporation     Published Date: Jul 07, 2013
Forward-looking enterprises know there's more to big data than strong and managing large volumes of information. Big data presents an opportunity to leverage analytics and experiment with all available data to derive value never before possible with traditional business intelligence and data warehouse platforms. Through a modern, big data platform that facilitates self-service and collaborative analytics across all data, organizations become more agile and are able to innovate in new ways.
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enterprises, storage, information management, technology, platform, big data analytics, emc, self service, business intelligence, security, enterprise applications
    
EMC Corporation
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: SRC,LLC     Published Date: Jun 01, 2009
Companies spend millions of dollars every year on building data warehouses, buying business intelligence (BI) software tools and managing their analytic processes in the hope of gaining consumer insight and winning market share. Yet, many companies fail to realize the full benefits of their technology investments because they are hamstrung by the layers of expertise and the complexity of technology tools needed to integrate various data warehouses and associated tools within their existing analytic environments. Since analysis is only as good as the accessibility, timeliness and accuracy of the information being analyzed, the interoperability of any data warehouse with any analytic environment is essential to achieving insightful, actionable analysis and making better decisions.
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src, enterprise, streamline, analytics, economy, analytic imperative, business intelligence, seamless, data warehouse, interoperability, analytic environment, data assets, report generation, output options, total cost of ownership, tco, roi, return on investment, olap, enterprise applications
    
SRC,LLC
Published By: Oracle Corporation     Published Date: May 11, 2012
This whitepaper provides an overview of Oracle's capabilities for data warehousing and discusses the key features and technologies by which Oracle-based business intelligence and data warehouse systems integrate information and scale to analyze data.
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oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands, enterprise applications
    
Oracle Corporation
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