warehouses

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Published By: Gigaom     Published Date: Oct 15, 2019
Data pipelines are a reality for most organizations. While we work hard to bring compute to the data, to virtualize and to federate, sometimes data has to move to an optimized platform. While schema-on-read has its advantages for exploratory analytics, pipeline-driven schema-on-write is a reality for production data warehouses, data lakes and other BI repositories. But data pipelines can be operationally brittle, and automation approaches to date have led to a generation of unsophisticated code and triggers whose management and maintenance, especially at-scale, is no easier than the manually-crafted stuff. But it doesn’t have to be that way. With advances in machine learning and the industry’s decades of experience with pipeline development and orchestration, we can take pipeline automation into the realm of intelligent systems. The implications are significant, leading to data-driven agility while eliminating denial of data pipelines’ utility and necessity. To learn more, join us fo
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Gigaom
Published By: HERE Technologies     Published Date: Sep 26, 2019
A utomobile manufacturers find meeting the requirements of a just - in - time supply chain one of their biggest challenges , but with advances in location technology manufacturers can meet even the strictest shipping deadlines . With better visibility across the supply chain auto manufacturers can drive down costs, improve efficiency and support proactive decision making. By reading this eBook, you’ll discover how to p repar e your supply chain for the future wit h the application of location intelligence to: ? Gain location - based insights to help optimize processes and inform decision making ? Set accurate ETAs with reliable real - time information ? Use real - time visibility to proactively solve problems ( like bottlenecks ) as they occur ? Gain comprehensive coverage of assets and trace them across factories, warehouses, showrooms and in transit
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HERE Technologies
Published By: HERE Technologies     Published Date: Sep 26, 2019
Misplacing sizable, expensive tooling equipment inside large industrial complexes, factories and warehouses is a problem that doesn't get the attention it deserves. When essential inventory gets lost, whole production lines can grind to a halt. Indoor tracking is the optimal way to keep tabs on all mobile equipment around the factory floor. As one of the world's leading location platforms, HERE shares insights and solutions for implementing indoor tracking in a way that can streamline and optimize production processes. Read the eBook to discover how to: • locate inventory and assets quickly to lower downtime and improve job satisfaction • save money spent on replacing lost tools and wasted employee time • use insights into asset utilization for forecasting or maintenance schedules.
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HERE Technologies
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: 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: Zaloni     Published Date: Apr 24, 2019
Why your data catalog won’t deliver significant ROI According to Gartner, organizations that provide access to a curated catalog of internal and external data assets will derive twice as much business value from their analytics investments by 2020 than those that do not. That’s a ringing endorsement of data catalogs, and a growing number of enterprises seem to agree. In fact, the global data catalog market is expected to grow from US$210.0 million in 2017 to US$620.0 million by 2022, at a Compound Annual Growth Rate (CAGR) of 24.2%. Why such large and intensifying demand for data catalogs? The primary driver is that many organizations are working to modernize their data platforms with data lakes, cloud-based data warehouses, advanced analytics and various SaaS applications in order to grow profitable digital initiatives. To support these digital initiatives and other business imperatives, organizations need more reliable, faster access to their data. However, modernizing data plat
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Zaloni
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: 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: RSM US     Published Date: Apr 01, 2019
Middle market companies face a host of warehousing challenges that can limit growth and potentially hamper sustainability. Your organization must work to understand these issues and develop solutions to store, manage and move goods more effectively and therefore increase efficiency and productivity. With competition growing and new enhancements reaching the market on a regular basis, your company must be proactive to build and retain a competitive advantage. While each company is different, with unique issues and goals, the following four struggles are common across companies and their warehouses.
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RSM US
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 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: 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: 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: Google     Published Date: Jan 24, 2019
Modernizing your data warehouse is one way to keep up with evolving business requirements and harness new technology. For many companies, cloud data warehousing offers a fast, flexible, and cost-effective alternative to traditional on-premises solutions. This report sponsored by Google Cloud, TDWI examines the rise of cloud-based data warehouses and identifies associated opportunities, benefits, and best practices. Learn more about cloud data warehousing with strategic advice from Google experts.
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Google
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: Google     Published Date: Oct 26, 2018
Modernizing your data warehouse is one way to keep up with evolving business requirements and harness new technology. For many companies, cloud data warehousing offers a fast, flexible, and cost-effective alternative to traditional on-premises solutions. This report sponsored by Google Cloud, TDWI examines the rise of cloud-based data warehouses and identifies associated opportunities, benefits, and best practices. Learn more about cloud data warehousing with strategic advice from Google experts.
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Google
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: 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: 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: MacroAir     Published Date: Apr 26, 2018
Large industrial facilities such as warehouses and manufacturing plants present a huge operational challenge because of their size. With extremely tall ceilings and a lot of square footage to cool or heat, keeping occupants comfortable is difficult. The solution: MacroAir big industrial ceiling fans. MacroAir large industrial fans create a more comfortable climate and reduce energy costs for large industrial facilities. MacroAir invented the large industrial ceiling fan in 1998 to deliver a cost-effective climate control solution by generating large amounts of airflow. MacroAir’s big industrial fans produce a cooling effect, help control the effects of humidity, and can also help conserve heat in colder months by pushing warm air that is trapped at the ceiling toward the walls and down to the floor at occupant level. MacroAir big industrial ceiling fans create an environment where employee’s feel comfortable, which results in increased productivity and improved industrial operations.
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industrial fans, industrial facilities, macroair fans, commercial fans
    
MacroAir
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: 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: Group M_IBM Q1'18     Published Date: Jan 23, 2018
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
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data warehouse, analytics, hybrid data warehouse, development model
    
Group M_IBM Q1'18
Published By: Oracle     Published Date: Nov 28, 2017
Today’s leading-edge organizations differentiate themselves through analytics to further their competitive advantage by extracting value from all their data sources. Other companies are looking to become data-driven through the modernization of their data management deployments. These strategies do include challenges, such as the management of large growing volumes of data. Today’s digital world is already creating data at an explosive rate, and the next wave is on the horizon, driven by the emergence of IoT data sources. The physical data warehouses of the past were great for collecting data from across the enterprise for analysis, but the storage and compute resources needed to support them are not able to keep pace with the explosive growth. In addition, the manual cumbersome task of patch, update, upgrade poses risks to data due to human errors. To reduce risks, costs, complexity, and time to value, many organizations are taking their data warehouses to the cloud. Whether hosted lo
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Oracle
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