warehouses

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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: SAS     Published Date: Nov 10, 2014
Learn how this upcoming year should be the year you make your big data actionable and see what else you should be doing to maximize its potential.
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sas, data integration, data evolution, comprehensive data, data management, data virtualization, data warehouses, data profiling, metadata management
    
SAS
Published 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.
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sap, business intelligence, business insight, business transparency, cross-enterprise data, inter-enterprise data, data integration
    
SAP Inc.
Published By: Pentaho     Published Date: Apr 28, 2016
As data warehouses (DWs) and requirements for them continue to evolve, having a strategy to catch up and continuously modernize DWs is vital. DWs continue to be relevant, since as they support operationalized analytics, and enable business value from machine data and other new forms of big data. This TDWI Best Practices report covers how to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. This report covers: • The many options – both old and new – for modernizing a data warehouse • New technologies, products, and practices to real-world use cases • How to extend the lifespan, range of uses, and value of existing data warehouses
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pentaho, data warehouse, modernization, big data, bug data analytics, best practices
    
Pentaho
Published By: Epson     Published Date: Nov 21, 2017
A customer may store heavy file boxes in one of its warehouses, but Fireproof Records Center spends a lot of time strategizing about the paperless office. Based in Grove City, Ohio, the company helps businesses in central Ohio manage information more efficiently, offering a suite of cloud document management and scanning tools, including the easy-to-use Epson WorkForce® color document scanner.
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Epson
Published By: Motorola Solutions     Published Date: Jun 05, 2019
THE TIME IS NOW TO CREATE AN ENGAGING SHOPPING EXPERIENCE FOR EVERY CUSTOMER. In the world of retail, the customer is always right. That’s why retailers today must ensure their staff is well-informed, well-coordinated, armed and ready with the right information to satisfy customers in stores. Whether it’s a customer’s question about a product or a request for a different size, shoppers expect retail associates to be empowered with accurate answers and attentive service. Above all, stores need to rely on strong communication technologies so retailers can deliver a seamless experience for shoppers and keep them coming back. When retailers create an engaging experience, customer interactions turn into transactions and occasional buyers turn into loyal brand advocates. Motorola Solutions Two-Way Business Radios are helping retailers across the nation enhance customer and employee interactions, efficiency and safety both in stores and warehouses – but which business radio model is right for
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Motorola Solutions
Published By: BMC ASEAN     Published Date: Dec 18, 2018
Big data projects often entail moving data between multiple cloud and legacy on-premise environments. A typical scenario involves moving data from a cloud-based source to a cloud-based normalization application, to an on-premise system for consolidation with other data, and then through various cloud and on-premise applications that analyze the data. Processing and analysis turn the disparate data into business insights delivered though dashboards, reports, and data warehouses - often using cloud-based apps. The workflows that take data from ingestion to delivery are highly complex and have numerous dependencies along the way. Speed, reliability, and scalability are crucial. So, although data scientists and engineers may do things manually during proof of concept, manual processes don't scale.
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BMC ASEAN
Published By: CA Technologies EMEA     Published Date: Apr 10, 2018
Effective Competition Depends on Continuous Delivery of Quality Software In today’s application economy every company is a software company, no matter what industry it is in: • Shipping companies depend on logistics software to efficiently route packages, arrange drivers and automate warehouses. • Retail companies rely on software to manage inventory, engage with customers online and to give in-store associates the tools they need to answer customer questions on the spot. • Marketing firms lean on applications to gather consumer data and parse it, automate communication with prospects and effectively manage advertising campaigns. The examples are endless. The point is that in order to compete today, every business must be able to quickly build and tweak software to adjust to always evolving market demands. Ultimately, business success depends on faster development iterations while still maintaining the high quality of service expected by customers, stakeholders and end users.
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CA Technologies EMEA
Published By: Gigaom     Published Date: Sep 16, 2019
We’ve heard it before. A data warehouse is a place for formally-structured, highly-curated data, accommodating recurring business analyses, whereas data lakes are places for “raw” data, serving analytic workloads, experimental in nature. Since both conventional and experimental analysis is important in this data-driven era, we’re left with separate repositories, siloed data, and bifurcated skill sets. Or are we? In fact, less structured data can go into your warehouse, and since today’s data warehouses can leverage the same distributed file systems and cloud storage layers that host data lakes, the warehouse/lake distinction’s very premise is rapidly diminishing. In reality, business drivers and business outcomes demand that we abandon the false dichotomy and unify our data, our governance, our analysis, and our technology teams. Want to get this right? Then join us for a free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and special guest, Dav
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Gigaom
Published By: Oracle     Published Date: Apr 16, 2018
A velocidade e o volume de entrada de dados estão gerando demandas esmagadoras sobre os data marts tradicionais, os data warehouses e os sistemas analíticos. Uma solução em nuvem de data warehouse tradicional pode ajudar os clientes a suprirem tais demandas? Muitos clientes estão comprovando o valor dos data warehouses na nuvem através dos ambientes de testes ou de inovação, dos data marts na área de negócios e backup de banco de dados.
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clientes, estao, migrando, data, warehouses, nuvem
    
Oracle
Published By: Oracle     Published Date: Apr 16, 2018
La velocidad y el volumen de los datos entrantes están dando lugar a una gran demanda en los centros de datos tradicionales, repositorios de datos empresariales y sistemas analíticos. ¿Puede una solución de almacén de datos tradicional en la nube ayudar a los clientes a satisfacer estas demandas? Muchos clientes están comprobando el valor de los repositorios de datos en la nube a través de entornos “de prueba”, repositorios de datos según el área de negocios y respaldos de base de datos.
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clientes, trasladan, sus, data, warehouses
    
Oracle
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: 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
    
SRC,LLC
Published By: DataFlux     Published Date: Jan 07, 2011
This white paper introduces and examines a breakthrough platform solution designed to drive parallel-process data integration - without intensive pre-configuration - and support full-lifecycle data management from discovery to retirement.
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dataflux, enterprise data, data integration, configuration, lifecycle data management, data warehouses
    
DataFlux
Published 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.
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oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands
    
Oracle Corporation
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: Vertica     Published Date: Mar 15, 2010
In a world of growing data volumes and shrinking IT budgets, it is critical to think differently about the efficiency of your database and storage infrastructure. The Vertica Analytic Database is a high-performance, scalable and cost-effective solution that can bring dramatic savings in hardware, storage and operational costs.
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vertica, ec2, cdr, elastic, saas, cdr, cloud computing, data management, ad-hoc, business intelligence, cloud, cloudbased applications, analytic, saas, dbms, mpp
    
Vertica
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
    
IBM
Published By: IBM     Published Date: Feb 02, 2009
A comprehensive solution for leveraging data in today's retail environment. From customer data to product placement statistics, retail organizations are constantly juggling information. As the sheer amount of data continues to grow, it becomes increasingly difficult to manage. Not only does data come in many different forms—such as reports, memos and e-mails—but often it’s scattered across multiple repositories.
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ibm, ibm balanced warehouses, ibm master data management server, ibm omnifind, ibm industry data models, dynamic warehousing, retail buyer’s guide, leveraging data, customer data, product placement statistics, data management, scalable system, customer relationships, cross-sell, up-sell opportunities, db2 warehouse, oltp-based transactional data server, information management software
    
IBM
Published By: IBM     Published Date: Feb 02, 2009
A comprehensive solution for leveraging data in today's financial industry. Most organizations realize that the key to success lies in how well they manage data—and the banking industry is no exception. From customer statistics to strategic plans to employee communications, financial institutions are constantly juggling endless types of information.
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ibm, information management software, leveraging data, dynamic warehousing, data management, improve customer service, real-time risk analysis, analytics capabilities, information on demand framework, ibm db2 warehouse, ibm master data management server, ibm omnifind, ibm industry data models, ibm balanced warehouses, oltp-based transactional data
    
IBM
Published By: IBM     Published Date: Jun 15, 2009
The ability to make quick, well-informed decisions is critical to competitiveness and growth for most companies. Read the white paper to see how Data warehouse solutions can deliver business insight across virtually any business process or function. And also how they're particularly valuable for understanding sales, profiling customers and analyzing business costs.
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ibm, data warehouses, warehouse, data, data solutions, sales, business costs, olap, online, analytical processing, customer relationship management, crm, ibm db2 warehouse, regulatory, compliance
    
IBM
Published By: Tyco Integrated Security     Published Date: Mar 09, 2016
Whether it’s worrying about a possible break-in or an employee theft, protecting your business is always a concern. For busy warehouses and manufacturing companies, the worry is even greater, as time lost to responding to a crime means revenue loss. With expensive inventory, an active production site, and workers entering and leaving around the clock, reliable security is a must.
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tyco, security, threat, employee theft
    
Tyco Integrated Security
Published By: Zebra Technologies     Published Date: Jan 30, 2019
Don’t let your legacy devices hold you back. Watch these three exclusive 2018 webinars to learn how Zebra can help you and your organization modernize your warehouse. Webinar #1: The Age of Android in the Enterprise Zebra’s Kevin Lollock, Regional Product Manager, Mobile Computing OS and Developer Platforms will unpack the vast migration to Android™ and the opportunities available for your warehouse and distribution centers. Webinar #2: Modernize the Warehouse with Android Warehouses without Windows®? Mark Wheeler, Zebra’s Director of Supply Chain Solutions discusses the migration to Android devices and shares a vision of the warehouse of the future. Webinar #3: How to Start your OS Migration Zebra’s Ritesh Gupta, Lead for Zebra Learning Services simplifies the steps of migrating to Android devices, including key considerations for planning, management, support and security. Get free access to these Webinars today!
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Zebra Technologies
Published By: SnowFlake     Published Date: Jul 08, 2016
Data today comes from diverse sources in diverse forms and needs to be analyzed by ever more users as quickly as possible. Those demands are stressing the limitations of traditional data warehouses and data platforms. Snowflake has reinvented the data warehouse, making it possible to bring all your business data together in a single system that can support all your users and workloads. Built from the cloud up as a software service, Snowflake eliminates the cost, complexity, and inflexibility of existing solutions while allowing you to use the tools and skills you already have.
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snowflake, data, technology, best practices, solutions, cloud support
    
SnowFlake
Published By: SnowFlake     Published Date: Jul 08, 2016
This EMA case study profiles the implementation of the Snowflake Elastic Data Warehouse, a new generation of cloud-based data warehouses, by Accordant Media. This document details significant tangible and intangible improvements and opportunities the Snowflake solution created for the Accordant Media infrastructure and analytical teams.
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snowflake, media, data, technology, cloud-based data, best practices
    
SnowFlake
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