warehouse

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Published By: IBM     Published Date: Oct 13, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, enterprise applications, data management, data center
    
IBM
Published By: Panasonic Business Mobility Solutions     Published Date: Sep 06, 2016
A surprising 80% of the 30 million1 warehouse workers worldwide, in the field of transportation and logistics, are still using pen and paper in a physically-intensive environment that increasingly demands accuracy and real time feedback. With warehouse efficiency, so closely tied to customer satisfaction in areas like ecommerce, the low penetration of digital solutions—20% as recent as 2014, is surprising. Unless an organization has a fully automated warehouse, the job is heavily labor-intensive. VDC research reveals that as long as human labor plays a dominant role in warehousing, any technology that optimizes workflows and improves accuracy will add tremendous value
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mobile workforce, laptops, tablet, mobile computing, productivity, rugged, mobile handheld, mobile scanner, business management
    
Panasonic Business Mobility Solutions
Published By: Pentaho     Published Date: Aug 29, 2016
This white paper covers the many options available for modernizing a data warehouse.
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Pentaho
Published By: Pentaho     Published Date: Aug 22, 2016
This white paper covers the many options available for modernizing a data warehouse.
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big data, data integration, bi systems, hadoop
    
Pentaho
Published By: SAS     Published Date: Aug 03, 2016
No matter the vintage or sophistication of your organization’s data warehouse (DW) and the environment around it, it probably needs to be modernized in one or more ways. That’s because DWs and requirements for them continue to evolve. Many users need to get caught up by realigning the DW environment with new business requirements and technology challenges. Once caught up, they need a strategy for continuous modernization.
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best practices, technology, data, business technology, business analytics, business intelligence, business management
    
SAS
Published By: Cisco     Published Date: Jul 11, 2016
Imagine you manage a warehouse for a small shipping firm. You have a simple job: route packages. But your employer expands to 25 western cities and 50 locations. After further expansion you now need to track packages coming by truck, rail, and plane and route them based on contents and weight to 10,000 different locations worldwide. While keeping traffic in and out tightly secured, making sure each package reaches its destination on time, and without going over budget. You might be wondering how things could get so complicated so quickly. But as an IT professional, you are nodding your head, because it all sounds very familiar. More Users + More Devices = More Complexity
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Cisco
Published By: SnowFlake     Published Date: Jul 08, 2016
Today’s data, and how that data is used, have changed dramatically in the past few years. Data now comes from everywhere—not just enterprise applications, but also websites, log files, social media, sensors, web services, and more. Organizations want to make that data available to all of their analysts as quickly as possible, not limit access to only a few highly-skilled data scientists. However, these efforts are quickly frustrated by the limitations of current data warehouse technologies. These systems simply were not built to handle the diversity of today’s data and analytics. They are based on decades-old architectures designed for a different world, a world where data was limited, users of data were few, and all processing was done in on-premises data centers.
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snowflake, data, technology, enterprise, application, best practices, social media, storage, business intelligence, cloud computing
    
SnowFlake
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, storage, business intelligence, cloud computing
    
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, business intelligence, productivity
    
SnowFlake
Published By: SnowFlake     Published Date: Jul 08, 2016
In the era of big data, enterprise data warehouse (EDW) technology continues to evolve as vendors focus on innovation and advanced features around in-memory, compression, security, and tighter integration with Hadoop, NoSQL, and cloud. Forrester identified the 10 most significant EDW software and services providers — Actian, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), IBM, Microsoft, Oracle, Pivotal Software, SAP, Snowflake Computing, and Teradata — in the category and researched, analyzed, and scored them. This report details our findings about how well each vendor fulfills our criteria and where they stand in relation to each other to help enterprise architect professionals select the right solution to support their data warehouse platform.
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forrester, enterprise, data, technology, best practices, innovation, security, business integration, business intelligence
    
SnowFlake
Published By: IBM     Published Date: Jul 05, 2016
Cloud-based data warehousing as-a-service, built for analytics
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ibm, dashdb, data, analytics, data warehouse, cloud, analytics, business insights, knowledge management, enterprise applications, data management, data center
    
IBM
Published By: IBM     Published Date: Jul 05, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, knowledge management, data management, data center
    
IBM
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, knowledge management, data management, data center
    
IBM
Published By: Cisco     Published Date: Jun 21, 2016
Imagine you manage a warehouse for a small shipping firm. You have a simple job: route packages. But your employer expands to 25 western cities and 50 locations. After further expansion you now need to track packages coming by truck, rail, and plane and route them based on contents and weight to 10,000 different locations worldwide. While keeping traffic in and out tightly secured, making sure each package reaches its destination on time, and without going over budget.
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Cisco
Published By: Kaspersky Lab Australia and New Zealand     Published Date: Jun 09, 2016
Chemist warehouse is one of Australia's most remarkable business success stories, doubling sales and growing its national store network from 100 to more than 400 stores in just five years.
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kaspersky, kaspersky endpoint security, security, security application, kaspersky solutions, security solutions, application security, authentication, encryption, security management, security policies
    
Kaspersky Lab Australia and New Zealand
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: 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, networking, it management, wireless, platforms, data management
    
Pentaho
Published By: IBM     Published Date: Apr 19, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, data management
    
IBM
Published By: Hortonworks     Published Date: Apr 05, 2016
Download this whitepaper to learn how Hortonworks Data Platform (HDP), built on Apache Hadoop, offers the ability to capture all structured and emerging types of data, keep it longer, and apply traditional and new analytic engines to drive business value, all in an economically feasible fashion. In particular, organizations are breathing new life into enterprise data warehouse (EDW)-centric data architectures by integrating HDP to take advantage of its capabilities and economics.
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Hortonworks
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: Enterprise Management Associates     Published Date: Nov 23, 2015
Join John Myers, managing research director at leading IT analyst firm Enterprise Management Associates (EMA), and Heine Krog Iversen, CEO at TimeXtender, for a discussion on how to improve your organization’s responsiveness to business change and how to adapt to a data-driven environment. Attendees will gain insight on: How data-driven organizations are changing business and technology Which data sources are empowering data-driven organizations and challenging IT departments How IT departments and analytical teams can get ahead of data-driven change How data warehouse automation enables not only data-driven business stakeholders, but proactive IT departments
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data warehouse, data automation, data driven organization, it departments, organization responsiveness, data warehousing
    
Enterprise Management Associates
Published By: Cisco     Published Date: Nov 18, 2015
Imagine you manage a warehouse for a small shipping firm. You have a simple job: route packages. But your employer expands to 25 western cities and 50 locations. After further expansion you now need to track packages coming by truck, rail, and plane and route them based on contents and weight to 10,000 different locations worldwide. While keeping traffic in and out tightly secured, making sure each package reaches its destination on time, and without going over budget. You might be wondering how things could get so complicated so quickly. But as an IT professional, you are nodding your head, because it all sounds very familiar.
Tags : 
cisco, network, business growth, virtual network, networking, security
    
Cisco
Published By: IBM     Published Date: Nov 16, 2015
As vendors continue to evolve their solutions to fit these changing requirements, IBM remains a leader in this Gartner Magic Quadrant.
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ibm, data warehouse, data management, analytics, gartner, data center
    
IBM
Published By: IBM     Published Date: Nov 16, 2015
The market offers an array of choices to organizations planning new data warehouses to manage large and varied data sets. Most vendors emphasize the speed of their products, but few address the real need: to increase speed efficiently, which reduces complexity and cost by simplifying data warehousing.
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ibm, organization, puredata, analytics, research, data warehouse, knowledge management, data management
    
IBM
Published By: IBM     Published Date: Nov 09, 2015
In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative.
Tags : 
ibm, data warehouse, big data, data management, data center
    
IBM
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