warehouse

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Published By: Infor     Published Date: Mar 03, 2017
The goal of warehouse operations is perfect order fulfillment: to deliver exactly the items a customer ordered, on time and with optimal efficiency. The warehouse module of an enterprise resource planning (ERP) solution can help smaller warehouses achieve this goal. But ERP warehouse modules have limitations that can make it smarter for companies with more complex operations to turn to the added capabilities of an advanced warehouse management system (WMS).
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enterprise resource planning, erp, erp solutions
    
Infor
Published By: StreamSets     Published Date: Sep 24, 2018
Treat data movement as a continuous, ever-changing operation and actively manage its performance. Before big data and fast data, the challenge of data movement was simple: move fields from fairly static databases to an appropriate home in a data warehouse, or move data between databases and apps in a standardized fashion. The process resembled a factory assembly line.
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practices, modern, data, performance
    
StreamSets
Published By: NAVEX Global     Published Date: Mar 21, 2018
Good analysis and benchmarking of hotline data helps organisations answer crucial questions about their ethics and compliance programme. Comparing internal data year over year to help answer these questions is important. But getting a broader perspective on how your performance matches up to industry norms is critical. To help, each year NAVEX Global takes anonymised data collected through our hotline and incident management systems to create these reports. This particular report is the second NAVEX Global benchmark report we have published that focuses specifically on the status of ethics and compliance hotline services in the EMEA and APAC regions. This benchmark only takes reporting data from organisations that has its data warehoused in Europe—a subset of the data used in our global hotline report.
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NAVEX Global
Published By: Teradata     Published Date: May 02, 2017
Read this article to discover the 4 things no data warehouse should be without.
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cloud data, cloud security, cloud management, storage resource, computing resources, data warehousing, data storage, cloud efficiency
    
Teradata
Published By: StreamSets     Published Date: Sep 24, 2018
The advent of Apache Hadoop™ has led many organizations to replatform their existing architectures to reduce data management costs and find new ways to unlock the value of their data. One area that benefits from replatforming is the data warehouse. According to research firm Gartner, “starting in 2018, data warehouse managers will benefit from hybrid architectures that eliminate data silos by blending current best practices with ‘big data’ and other emerging technology types.” There’s undoubtedly a lot to ain by modernizing data warehouse architectures to leverage new technologies, however the replatforming process itself can be harder than it would at first appear. Hadoop projects are often taking longer than they need to create the promised benefits, and often times problems can be avoided if you know what to avoid from the onset.
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replatforming, age, data, lake, apache, hadoop
    
StreamSets
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: SAS     Published Date: Nov 10, 2014
Learn how data is evolving and the 7 reasons why a comprehensive data management platform supersedes the data integration toolbox that you are using these days.
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sas, data integration, data evolution, comprehensive data, data management, data virtualization, data warehouses, data profiling, metadata management
    
SAS
Published By: Teradata     Published Date: Jan 16, 2015
This Neil Raden paper describes the current need for data warehousing, why SAP® BW is an incomplete choice and how Teradata Analytics for SAP® Solutions is a superior option. Download now!
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teradata, sap solutions, data warehouse, extracted data
    
Teradata
Published By: IBM     Published Date: Jul 05, 2016
In an environment where data is the most critical natural resource, speed-of-thought insights from information and analytics are a critical competitive imperative.
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ibm, data warehouse, big data, analytics, data warehouse, business intelligence
    
IBM
Published By: Teradata     Published Date: May 02, 2017
A Great Use of the Cloud: Recent trends in information management see companies shifting their focus to, or entertaining a notion for the first time of a cloud-based solution. In the past, the only clear choice for most organizations has been on-premises data—oftentimes using an appliance-based platform. However, the costs of scale are gnawing away at the notion that this remains the best approach for all or some of a company’s analytical needs. This paper, written by McKnight Consulting analysts William McKnight and Jake Dolezal, describes two organizations with mature enterprise data warehouse capabilities, that have pivoted components of their architecture to accommodate the cloud.
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data projects, data volume, business data, cloud security, data storage, data management, cloud privacy, encryption, security integration
    
Teradata
Published By: Infor     Published Date: Aug 04, 2011
AB World Foods has a highly complex supply chain, driven in part by the nature of its globally sourced and distributed products as well as by the demands of growth and acquisition. With Infor SCM Demand Planning, the company cut costs while also improving service levels.
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infor, ab world food, scm, enterprise business software, customer relationship management, enterprise asset management, enterprise resource planning, financial management, human capital management, product lifecycle, supplier relationship, supply chain management, business-specific inventory, transportation logistics, warehouse software, service oriented architecture
    
Infor
Published By: AWS     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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AWS
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: Infor     Published Date: Aug 04, 2011
Find out what characteristics you should take into account when selecting Sales and Operations Technology and how Infor10 Sales & Operations Planning respond to those needs today.
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infor, aberdeen, s&op, infor10, sales and operations, sales & operations, scm, enterprise business software, customer relationship management, enterprise asset management, enterprise resource planning, financial management, human capital management, product lifecycle, supplier relationship, supply chain management, business-specific inventory, transportation logistics, warehouse software, service oriented architecture
    
Infor
Published 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
Published By: IBM     Published Date: Mar 29, 2017
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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cloud, analytics, data, organization, ibm
    
IBM
Published By: Group M_IBM Q119     Published Date: Mar 04, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
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Group M_IBM Q119
Published By: Group M_IBM Q119     Published Date: Mar 11, 2019
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud
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Group M_IBM Q119
Published By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
One of the biggest changes faces organizations making purchasing and deployment decisions about analytic databases -- including relational data warehouses -- is whether to opt for a cloud solution.
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Group M_IBM Q2'19
Published By: Zebra Technologies     Published Date: Jul 06, 2017
Gestione sin esfuerzo su flota de impresoras térmicas de códigos de barras para un control más estricto y mayores resultados. Este artículo cubre desafíos como aprovisionamiento problemático, dolores de cabeza de seguridad y monitoreo confuso.
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printer intelligence, industrial printers, desktop printers, mobile printers, highly durable printers, improving warehouse, manufacturing productivity, shipping accuracy, inventory accuracy, price management accuracy
    
Zebra Technologies
Published 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.
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data warehousing, data management, database management, database administration, dba, business intelligence, ibm, leveraging information, li campaign, ibm li
    
IBM
Published 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.
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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
Published By: IBM     Published Date: May 02, 2014
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.
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ibm, big data platform, architecting big data, analytics, intelligent business strategies, data complexity, data types, workload growth, workload complexity, big data analytic applications, operational decisions, multi-structured data, querying data, scalable data management, analytical ecosystem, hadoop solutions
    
IBM
Published By: SAS     Published Date: Sep 08, 2010
This paper describes five business analytics styles used today and the building blocks required in implementing these styles. It is important to consider which of these styles is valid for your organization now and into the future.
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sas, reporting, data warehouses, business activity monitoring, data integration
    
SAS
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