warehouse

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Published 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
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warehousing infrastructure, ibm, business intelligence, data warehouse, dynamic warehousing, data warehouse model, master data, data management, data protection, data warehousing
    
IBM
Published By: AWS     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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AWS
Published By: OpTier     Published Date: Mar 11, 2013
In the Information Technology (IT) industry, 2012 has been the year of Big Data. From a standing start toward the end of the last decade, Big Data has become one of the most talked about topics.
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optier, big data, enterprise data warehouse, edw, nosql
    
OpTier
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: Oracle     Published Date: Jan 09, 2019
Speed has become the necessary basis of competition. See how Oracle aims to help clients with this through their vision for autonomous database.
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Oracle
Published 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.
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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, data warehousing
    
IBM
Published By: Zebra Technologies     Published Date: Jun 21, 2017
Zebra’s Warehouse Vision Survey revealed transformational changes in North America for asset visibility, warehouse productivity and supply chain integration. Download now!
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Zebra Technologies
Published 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
Published 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
Published By: Oracle     Published Date: Sep 21, 2018
Agility and speed are required in the cloud economy. Modernize data warehouses with built-in adaptive machine learning to eliminate manual labor for administrative tasks. With Oracle, businesses can now build data warehouses or data marts in minutes.
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Oracle
Published By: Gleanster Research     Published Date: Oct 11, 2012
Authored by two luminary Business Intelligence (BI) industry analysts. This 9 page report exposes best practices on Self-Service BI. The findings come from a Q3'12 survey on BI, which captured the experiences of 327 organizations.
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business intelligence, cio, self-service, business analytics, data warehouse, data, analysis
    
Gleanster Research
Published By: Epicor     Published Date: Aug 02, 2012
The capabilities that enterprise resource planning (ERP) systems enable in wholesale and distribution have a wide umbrella of influence throughout an organization. Using ERP data to make better business decisions while cutting your costs is only one way you can make the most of your system.
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wholesale distribution, leading wholesalers, leading distributors, erp strategies, erp capabilities, cross functional teams, full visibility, operations and transactions, technology aids, erp modules and extensions, forecasting, demand planning, transportation management, warehouse management, supply chain planning, supplier relationship management, distribution requirements planning, optimization, measurable benefits, social media
    
Epicor
Published By: HighJump Software     Published Date: May 11, 2010
The question for today's supply chain professional isn't whether your ERP offers warehouse management functionality. The question is whether you'll actually be able to achieve efficient order fulfillment operations when using it.
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highjump, erp, warehouse, supply chain, wms, warehouse management, tco, enterprise resource planning, enterprise software, supply chain management, total cost of ownership
    
HighJump Software
Published By: Teradata     Published Date: Jan 30, 2015
Data from the Internet of Things makes an integrated data strategy more vital than ever.
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teradata, internet, things, iot, data, warehouse, analytics, patchwork, value, development, integration, supply chain, inventory, sales, market demand, channel partners, deployment, hadoop, aster, discovery
    
Teradata
Published By: Oracle Corporation     Published Date: May 11, 2012
Exadata Hybrid Columnar Compression is an enabling technology for two new Oracle Exadata Storage Server features: Warehouse Compression and Archive Compression. We will discuss each of these features in detail later in this paper, but first let's explore Exadata Hybrid Columnar Compression - the next generation in compression technology.
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oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands, enterprise applications, data management
    
Oracle Corporation
Published By: SRC,LLC     Published Date: Jun 01, 2009
To mine raw data and extract crucial insights, business decision‐makers need fast and comprehensive access to all the information stored across their enterprise, regardless of its format or location. Furthermore, that data must be organized, analyzed and visualized in ways that permit easy interpretation of market opportunities growth, shifts and trends and the business‐process changes required to address them. Gaining a true perspective on an organization’s customer base, market area or potential expansion can be a challenging task, because companies use so many relational databases, data warehouse technologies, mapping systems and ad hoc data repositories to gather and house information for a wide variety of specialized purposes.
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src, enterprise, enterprise applications, convergence, compared, counted, combined, reorganized, analyzed, visualized, mapped, database, gis, geographic business intelligence, data independence, etl, csv, delimited text file, mdb (both for microsoft access, esri personal geodatabase
    
SRC,LLC
Published By: Collaborative Consulting     Published Date: Dec 23, 2013
There are some surprisingly straightforward reasons behind the glitches, delays, and cost-overruns that can bedevil data warehouse initiatives. ...The first is simply confusing expectations with requirements. But four other troublemakers can also lead to big problems for developers, IT departments, and organizations seeking to maximize the business value of information.
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collaborative consulting, data warehouse, failed projects, business intelligence, business solution, meet expectations, big data, profile importance, cloud vendors, data quality, business goals, complicated architectures, avoid wasted expense, data management, data center
    
Collaborative Consulting
Published By: IBM     Published Date: May 17, 2016
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
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ibm, big data, inline analytics, business analytics, roi, business intelligence
    
IBM
Published By: Attunity     Published Date: Feb 12, 2019
How can enterprises overcome the issues that come with traditional data warehousing? Despite the business value that data warehouses can deliver, too often they fall short of expectations. They take too long to deliver, cost too much to build and maintain, and cannot keep pace with changing business requirements. If this all rings a bell, check out Attunity’s knowledge brief on data warehouse automation with Attunity Compose. The solution automates the design, build, and deployment of data warehouses, data marts and data hubs, enabling more agile and responsive operation. The automation reduces time-consuming manual coding, and error-prone repetitive tasks. Read the knowledge brief to learn more about your options.
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dwa, data warehouse automation, etl development, extract transform load tools, etl tools, data warehouse, data marts, data hubs data warehouse lifecycle, data integration, change management, data migration, consolidating data, cloud data warehousing, data warehouse design, attunity compose
    
Attunity
Published By: Oracle     Published Date: Apr 28, 2014
Perfect order fulfillment requires companies to have seamless integration of all supply chain execution (SCE) including, logistics processes from manufacturing, transportation, warehouse, global trade to mobile and RFID. Recent research from Gartner reveals that most supply chain organizations continue to operate as functional silos – warehousing, transportation and manufacturing – with minimal, if any, process integration and synchronization between execution silos. The Gartner Research report provides key insights into how supply chain and IT leaders can transform logistics by breaking down functional silos, and designing business processes that span, optimize and synchronize across traditional functional domains.
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oracle, logistics, value chain execution, silos
    
Oracle
Published By: Zebra Technologies     Published Date: Jul 06, 2017
Gerencie sem esforço sua frota de impressoras de código de barras térmicas para maior controle e melhores resultados. Este documento aborda desafios como provisionamento problemático, dores de cabeça de segurança e monitoramento 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: 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
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