warehouse

Results 126 - 150 of 289Sort Results By: Published Date | Title | Company Name
Published By: Zebra Technologies     Published Date: Jun 21, 2017
Redefining supply chain automation in the age of digital technology. Download now to learn more!
Tags : 
    
Zebra Technologies
Published By: Zebra Technologies     Published Date: Jun 21, 2017
Best practices for integrating mobile, wireless and data capture technologies into warehouse management. Download now!
Tags : 
    
Zebra Technologies
Published By: Sage     Published Date: Jul 08, 2015
Download this research survey to learn more about the returns of technology investments for small and midsize companies.
Tags : 
technology investments, small company, midsize company, efficiency, technology integration, mobile technology, warehouse logistics, small business
    
Sage
Published By: Oracle     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
Tags : 
    
Oracle
Published By: Oracle     Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure 1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data. In-memory databases have helped address p
Tags : 
    
Oracle
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.
Tags : 
replatforming, age, data, lake, apache, hadoop
    
StreamSets
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.
Tags : 
practices, modern, data, performance
    
StreamSets
Published By: VMware Dell     Published Date: Jun 05, 2008
Radiator Express Warehouse (1800Radiator), a fast-growing automotive parts distributor, found that it was running at maximum power and its racks were full. Using VMware virtualization technology, the company was able to take 31 physical servers out of production, resulting in a 25 percent reduction in power and cooling costs.
Tags : 
virtualization, vmware, virtual infrastructure, x86, server consolidation, server containment, business continuity, disaster recovery, energy savings, vmware infrastructure 3, vi3, vmware, server virtualization, green computing, power and cooling
    
VMware Dell
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.
Tags : 
sap, business intelligence, business insight, business transparency, cross-enterprise data, inter-enterprise data, data integration, enterprise applications, data management, international computing
    
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
Tags : 
pentaho, data warehouse, modernization, big data, bug data analytics, best practices, networking, it management, wireless, platforms, data management
    
Pentaho
Published By: AWS     Published Date: Aug 20, 2018
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 querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
Tags : 
    
AWS
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.
Tags : 
    
Epson
Published By: Motorola Solutions     Published Date: Apr 26, 2019
ffective communications are the foundation for any good team, and the transportation and logistics (T&L) sector is no exception. Charged with managing the warehousing, inventory, and movement of freight across the supply chain — both through internal and external distribution networks — T&L professionals rely on high levels of team collaboration to get the job done right. By helping companies leverage the knowledge, talents, and insights of their people, effective team communications ensures that customers get their deliveries when, how, and where they want them. Meeting those expectations in today’s fast-paced, demanding distribution environment requires reliable, clear voice and data logistics communications that start at the warehouse and end at the point of delivery. In this white paper, we explore the key challenges that T&L companies are facing in today’s business environment and hear how instant push-to-talk and advanced video surveillance can help them develop streamlined suppl
Tags : 
    
Motorola Solutions
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
Tags : 
    
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.
Tags : 
    
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.
Tags : 
    
CA Technologies EMEA
Published By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
Tags : 
    
Amazon Web Services
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.
Tags : 
    
Amazon Web Services
Published 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
Tags : 
    
Amazon Web Services
Published By: Epicor     Published Date: Aug 03, 2012
As the saying goes, what you can't measure, you can't manage. You may understand the importance of Key Performance Indicators (KPIs), but how do you measure them?
Tags : 
gross margin, epicor, sales per employee, inventory turns, service level, days sales outstanding, average collection period, days payables outstanding, average payables period, cash conversion cycle, inventory control, warehouse fulfillment, purchasing, sales, finance
    
Epicor
Published By: IBM     Published Date: May 30, 2012
Learn how CPG and Wholesale Distributors are becoming more efficient, more innovative, more agile, and more competitive.
Tags : 
cpg, wholeshale, real time, plant floor, retail, ibm, rfid, bar code, manufacturing, factory, warehouse, zebra, mobile computing, mobile data systems, mobile workers, business analytics, business management, sales automation, supply chain management, workforce management
    
IBM
Start   Previous    1 2 3 4 5 6 7 8 9 10 11 12    Next    End
Search Resource Library      

Add Resources

Get your company's resources in the hands of targeted business professionals.