warehouse performance

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By: Teradata     Published Date: Jan 30, 2015
Enterprise Hadoop Implementation with Teradata and Hortonworks
Tags : ncr, big data, data warehouse, enterprise hadoop, hadoop implementation, teradata, hortonworks, performance data, data management
     Teradata
By: Group M_IBM Q418     Published Date: Oct 15, 2018
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data. Getting data governance right is critical to your business success. That means ensuring your data is clean, of excellent quality, and of verifiable lineage. Such governance principles can be applied in Hadoop-like environments. Hadoop is designed to store, process and analyze large volumes of data at significantly lower cost than a data warehouse. But to get the return on investment, you must infuse data governance processes as part of offloading.
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     Group M_IBM Q418
By: Group M_IBM Q3'19     Published Date: Jun 27, 2019
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data.
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     Group M_IBM Q3'19
By: Canon Business Process Services, Inc.     Published Date: Aug 17, 2015
Every business day, corporate campuses across the country function like small cities requiring highly specialized facilities and logistics management services. This paper will explore effective and efficient Corporate Campus Logistics Services to ensure the efficient flow of materials and people at large multi-building office campuses serving thousands of employees. Corporate facilities, real estate management, logistics and procurement teams as well as commercial real estate management companies are charged with sourcing the services that are the underpinnings of these mega-campuses. It’s an effort that spans a wide range—coordinating the receipt and distribution of supplies, equipment and packages; safely transporting thousands of employees as well as suppliers and contractors to locations within the campus; tracking and warehousing countless materials to support daily planned and unplanned workplace needs. Learn more about lowering costs, streamlining operational efficiency and gaining high employee satisfaction.
Tags : canon business process services, outsourcing services, managed services, logistics services, warehouse management, facilities management, commercial real estate management, corporate real estate management, business operations, vendor management, performance management, service level agreements, slas, knowledge management, business technology
     Canon Business Process Services, Inc.
By: SAP Inc.     Published Date: Jul 28, 2009
Although many organizations have made significant investments in data collection and integration (through data warehouses and the like), it is a rare enterprise that can analyze and redeploy its accumulated data to actually drive business performance.  In the years to come, as globalization and increased reliance on the Internet further complicate, accelerate and intensify marketplace conditions, actionable business intelligence promises to deliver a formidable competitive advantage to firms that leverage its power.
Tags : sap, business intelligence, business insight, business transparency, cross-enterprise data, inter-enterprise data, data integration, enterprise applications, data management
     SAP Inc.
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
By: Zebra Technologies     Published Date: May 02, 2018
By 2022, only 12 percent of warehouse operations will use pen and paper, according to a recent Zebra study. Why are manual processes vanishing? Because automation and connectivity enable the modern warehouse to stay compliant, deliver on time and ensure more overall customer satisfaction, every single time. You can create a more efficient, compliant and profitable warehouse. Learn how with our free eBook, 6 Steps to Flawless Fulfillment. You’ll discover actionable strategies to: Deploy industrial wireless solutions to optimize team productivity and workflow. Improve staff communications and management to maximize on-the-job efficiency and effectiveness. Streamline order picking processes to cut costs and save time. Create advanced inventory and storage capabilities to improve efficiency and accuracy. Upgrade inbound handling operations to process more shipments, more accurately. Turnaround outbound performance to deliver the ‘last mile’ in flawless fulfillment.
Tags : warehouse, operations, zebra, study, automation, customer
     Zebra Technologies
By: Oracle Corporation     Published Date: May 11, 2012
This white paper presents two case studies that illustrate how Oracle Exadata increased storage capacity for data warehouses by 150%, reduced operational and database running costs by 50%, and on average improved database query performance by 10x.
Tags : oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands, enterprise applications, data management
     Oracle Corporation
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
By: IBM     Published Date: Dec 30, 2008
Most long-standing data warehouses are designed to support a relatively small number of users who access information to support strategic decisions, financial planning and the production of standard reports that track performance. Today, many more users need to access information in context and on demand so that critical functions are optimized to run efficiently. Learn how to create a roadmap for a truly dynamic warehousing infrastructure, and move ahead of your competition with your business intelligence system
Tags : warehousing infrastructure, ibm, business intelligence, data warehouse, dynamic warehousing, data warehouse model, master data, data management
     IBM
By: IBM     Published Date: Feb 02, 2009
Learn how IBM’s change data capture technology can be used in conjunction with IBM’s performance management solutions from Cognos to provide access to the trusted information that systems and employees need to make informed decisions at the speed of business.
Tags : ibm, information management software, performance management, business intelligence, ibm cognos, bi-ready data, departmental reporting with ibm cognos, in-memory data store, operational data stores, enterprise data warehouse, ibm® infosphere change data capture, cdc, kpi, cognos now!, operational data store, ods, ibm infosphere datastage, enterprise applications
     IBM
By: Netezza IBM US     Published Date: Mar 27, 2012
IBM Netezza data warehouse appliances push the limits of analytics by fusing our ground breaking data warehouse appliances with high performance, scalable analytics that can process massive data to solve complex problems orders of magnitude faster than typical solutions. IBM Netezza Analytics, IBM's embedded advanced analytics platform delivered with every appliance, enables the development and deployment of analytics to drive game changing results.
Tags : ibm, technology, netezza, analytics, enterprise analytics, business technology
     Netezza IBM US
By: Netezza IBM US     Published Date: Mar 27, 2012
Across all industries, Revolution R Enterprise advanced analytics platform leverages the capabilities of IBM Netezza Analytics on IBM Netezza's family of data warehouse appliances, merging high-performance, scalable data warehouse technology with advanced in-database analytics and massively parallel capabilities
Tags : ibm, technology, netezza, analytics, enterprise analytics, business technology
     Netezza IBM US
By: IBM     Published Date: Nov 18, 2013
Speed, simplicity and affordability: 3 capabilities businesses need from their warehousing environment. IBM DB2 with BLU Acceleration gives organizations a complete, multipurpose environment to rapidly distill insight from their data, make timely decisions and capitalize on opportunities.
Tags : ibm, ibm db2, blu acceleration, speed, acceleration, warehouse, warehousing environment, multipurpose environment, data, data management, data warehouse, warehouse performance, business technology, data center
     IBM
By: IBM     Published Date: Mar 05, 2014
For many years, companies have been building data warehouses to analyze business activity and produce insights for decision makers to act on to improve business performance. 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. Typically, a history of business activity is built up over a number of years allowing organizations to use business intelligence (BI) tools to analyze, compare and report on business performance over time. In addition, subsets of this data are often extracted from data warehouses into data marts that have been optimized for more detailed multi-dimensional analysis.
Tags : ibm, big data, data, big data platform, analytics, data sources, data complexity, data volume, data generation, data management, storage, acceleration, business intelligence, data warehouse
     IBM
By: IBM     Published Date: Oct 06, 2014
Business Intelligence (BI) has become a mandatory part of every enterprise’s decision-making fabric. Unfortunately in many cases, with this rise in popularity, came a significant and disturbing complexity. Many BI environments began to have a myriad of moving parts: data warehouses and data marts deployed on multiple platforms and technologies – each requiring significant effort to ensure performance and support for the various needs and skill sets of the business resources using the environment. These convoluted systems became hard to manage or enhance with new requirements. To remain viable and sustainable, they must be simplified. Fortunately today, we have the ability to build simpler BI technical environments that still support the necessary business requirements but without the ensuing management complexity. This paper covers what is needed to simplify BI environments and the technologies that support this simplification.
Tags : data warehouses, bi environments, bi technologies, faster deployments, knowledge management
     IBM
By: Oracle Corporation     Published Date: May 11, 2012
By using the Oracle Exadata Database Machine as your data warehouse platform you have a balanced, high performance hardware configuration. This paper focuses on the other two corner stones, data modeling and data loading.
Tags : oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands, enterprise applications, data management
     Oracle Corporation
By: NEC     Published Date: Aug 26, 2014
In addition to high reliability and availability, enterprise mission critical applications, data centers operating 24x7, and data analysis platforms all demand powerful data processing capabilities and stability. The NEC PCIe SSD Appliance for Microsoft® SQL Server® is a best-practice reference architecture for such demanding workloads. It comprises an Express 5800 Scalable Enterprise Server Series with Intel® Xeon® processor E7 v2 family CPUs, high-performance HGST FlashMAX II PCIe server-mounted flash storage, and Microsoft® SQL Server® 2014. When compared with the previous reference architecture based on a server with the Intel® Xeon® processor E7 family CPUs, benchmark testing demonstrated a performance improvement of up to 173% in logical scan rate in a data warehouse environment. The testing also demonstrated consistently fast and stable performance in online transaction processing (OLTP) that could potentially be encountered.
Tags : sql, datacenter, servers, virtualization, customer value, analytics, application owners, system integrators, big data, reliability, enterprise, availability, serviceability, processor, enterprise applications, storage
     NEC
By: IBM     Published Date: May 30, 2008
WinterCorp analyzes IBM's DB2 Warehouse and how it addresses twin challenges facing enterprises today: improving the value derived from the torrents of information processed every day, while lowering costs at the same time. Discover why WinterCorp believes the advances in data clustering strategies and intelligent software compression algorithms in IBM's Data Warehouse improves performance of business intelligence queries by radically reducing the I/O's needed to resolve them.
Tags : data warehousing, data management, database management, database administration, dba, business intelligence, ibm, leveraging information, li campaign, ibm li
     IBM
By: AWS     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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     AWS
By: Oracle     Published Date: Jan 09, 2019
The Accenture Oracle data team has more than 20,000 professionals, who aid in delivering 50 billion transactions a day across more than three exabytes of data for clients globally. Accenture Oracle data specialists recently put the Oracle Autonomous Data Warehouse to a rigorous performance test to provide a real-life application usage experience. The data was then extrapolated and expanded to nine years’ worth of data to test the performance. Learn directly from Accenture experts about testing methodology and results that enable them to deliver more data intelligence faster to the enterprise and transform the way people live and work.
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     Oracle
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