data warehouse

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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
    
IBM
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
    
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?
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ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse
    
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
    
IBM
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
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
While any number of reasons can prompt a change in data warehouse solutions, there are four key facts you need to know to help you make the right choice: 1. Complexity stifles business 2. Speed is business-friendly 3. Cost reduction is crucial 4. Analytics: The key to current and future success This e-book will explore those facts and explain why they are essential when evaluating your data warehouse options.
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IBM
Published By: IBM     Published Date: Mar 29, 2017
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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data, warehouse, modernization, ibm, cloud
    
IBM
Published By: IBM     Published Date: Mar 29, 2017
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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cloud, analytics, data, organization, ibm
    
IBM
Published By: IBM     Published Date: Mar 30, 2017
In today’s competitive on-line world, the speed of change in customer behaviour is increasing. In addition, in industries such as retail banking, car insurance and to some extent retail, the Internet has become the dominant way in which customers interact with an organisation. Yet in many data warehouses today, being able to analyse customer on-line behaviour is often not possible because the clickstream web log data needed to do this is missing. It is a key point because customer access to the web has made loyalty cheap.
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cyber attacks, data protection, it security, security solutions, system protector, web security, analytics
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
Are you looking to add new data domains or solve new business problems? IBM InfoSphere MDM comprises a complete MDM suite with multi-domain MDM capabilities and built-in domain patterns. IBM offers several editions of InfoSphere MDM, each designed to integrate with your existing architectures and business processes. You can choose the platform that best meets your immediate and long-term needs.
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cloud data, online marketing, customer acquisition, mobile marketing, social marketing, data warehouse, data storage, data collection
    
IBM
Published By: IBM     Published Date: Nov 08, 2017
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, ibm, deployment models
    
IBM
Published By: IBM APAC     Published Date: Aug 25, 2017
The world of business analytics is evolving rapidly, and while there are multiple emerging trends of note, two stand out as particularly impactful. First, there is an expanding and increasingly diverse audience of users that are becoming more analytically active. From mid-level Line-of-Business staff to senior executives on mahogany row, more users in more job functions are taking an increased level of ownership in the insight that fuels their decisions and the underlying data that supports that insight.
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data integration, data security, data optimization, data virtualization, database security
    
IBM APAC
Published By: IBM Software     Published Date: Feb 07, 2011
See what BI can do for your company in this complete four-chapter Shortcut Guide to BI success. Learn practical, affordable tips for creating or expanding your BI strategy.
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ibm cognos express, midsize companies, business intelligence, data mining, data warehouse, reporting
    
IBM Software
Published By: Informatica     Published Date: Oct 26, 2007
The goal of pervasive BI applications is to take the data that produced the back office ROI of more than 400% and deliver it to front-line employees in a form appropriate to their job functions – with similar results. There are thousands of business process steps in a typical enterprise where pervasive BI insights can be added. What are leading companies doing with pervasive BI?
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business intelligence, database, enterprise data warehouse, data mart, data warehouse, data mining, active data warehousing, active data warehouse
    
Informatica
Published By: Infosys     Published Date: May 30, 2018
Enterprises often accord the lowest priority for modernizing systems running business-critical applications, for fear of disruption of business as well as the time it would take for the new system to stabilize and come up to speed. A large telecom company had the same fears when they decided to modernize the reporting data warehouse which produced reports critical for making business decisions. See how Infosys helped and the five key takeaways from the project.
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data, fortress, modernize, business, applications, telecom
    
Infosys
Published By: Infosys     Published Date: Jun 12, 2018
Enterprises often accord the lowest priority for modernizing systems running business-critical applications, for fear of disruption of business as well as the time it would take for the new system to stabilize and come up to speed. A large telecom company had the same fears when they decided to modernize the reporting data warehouse which produced reports critical for making business decisions. See how Infosys helped and the five key takeaways from the project.
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data, fortress, modernize, business, applications, telecom
    
Infosys
Published By: Juniper Networks     Published Date: Oct 19, 2015
Datacenters are the factories of the Internet age, just like warehouses, assembly lines, and machine shops were for the industrial age. Over the course of the past several years, riding the wave of modernization, datacenters have become the heart and soul of the financial industry, which each year invests over $480 billion in datacenter infrastructure of hardware, software, networks, and security and services.
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juniper, datacenter, threat, ciso, enterprise, data, customer
    
Juniper Networks
Published By: Matillion     Published Date: May 12, 2011
This whitepaper explains the importance of Business Intelligence to midsize companies, examines the challenges found in BI projects and explains how to be successful in improving visibility in your business.
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business intelligence, management information, dashboard, dashboards, analysis, analytics, data warehouse, reports
    
Matillion
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
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Motorola Solutions
Published By: NAVEX Global     Published Date: Mar 21, 2018
Good analysis and benchmarking of hotline data helps organisations answer crucial questions about their ethics and compliance programme. Comparing internal data year over year to help answer these questions is important. But getting a broader perspective on how your performance matches up to industry norms is critical. To help, each year NAVEX Global takes anonymised data collected through our hotline and incident management systems to create these reports. This particular report is the second NAVEX Global benchmark report we have published that focuses specifically on the status of ethics and compliance hotline services in the EMEA and APAC regions. This benchmark only takes reporting data from organisations that has its data warehoused in Europe—a subset of the data used in our global hotline report.
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NAVEX Global
Published By: NEC     Published Date: Aug 26, 2014
In addition to high reliability and availability, enterprise mission critical applications, data centers operating 24x7, and data analysis platforms all demand powerful data processing capabilities and stability. The NEC PCIe SSD Appliance for Microsoft® SQL Server® is a best-practice reference architecture for such demanding workloads. It comprises an Express 5800 Scalable Enterprise Server Series with Intel® Xeon® processor E7 v2 family CPUs, high-performance HGST FlashMAX II PCIe server-mounted flash storage, and Microsoft® SQL Server® 2014. When compared with the previous reference architecture based on a server with the Intel® Xeon® processor E7 family CPUs, benchmark testing demonstrated a performance improvement of up to 173% in logical scan rate in a data warehouse environment. The testing also demonstrated consistently fast and stable performance in online transaction processing (OLTP) that could potentially be encountered.
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sql, datacenter, servers, virtualization, customer value, analytics, application owners, system integrators
    
NEC
Published By: Netezza IBM US     Published Date: Mar 27, 2012
Forrester's interviews with Epsilon, a multichannel marketing services provider, and subsequent financial analysis based on assumptions that Forrester used illustrate the potential ROI from the use of IBM Netezza appliances and concluded that IBM Netezza Data Warehouse Appliances provide competitive differentiation through faster analytics while reducing capital and operational costs.
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ibm, technology, netezza, data warehouse, analytics, roi, enterprise
    
Netezza IBM US
Published By: Netezza IBM US     Published Date: Mar 27, 2012
IBM Netezza data warehouse appliances push the limits of analytics by fusing our ground breaking data warehouse appliances with high performance, scalable analytics that can process massive data to solve complex problems orders of magnitude faster than typical solutions. IBM Netezza Analytics, IBM's embedded advanced analytics platform delivered with every appliance, enables the development and deployment of analytics to drive game changing results.
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ibm, technology, netezza, analytics, enterprise analytics
    
Netezza IBM US
Published By: Netezza IBM US     Published Date: Mar 27, 2012
This powerful, high-performance, scalable, simple-to-use advanced analytics platform delivered with every IBM Netezza data warehouse appliance, delivers on the promise of tapping into unleashed business potential.
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technology, ibm, netezza, advanced analytics, enterprise, business analytics, optimization
    
Netezza IBM US
Published By: Netezza IBM US     Published Date: Mar 27, 2012
Across all industries, Revolution R Enterprise advanced analytics platform leverages the capabilities of IBM Netezza Analytics on IBM Netezza's family of data warehouse appliances, merging high-performance, scalable data warehouse technology with advanced in-database analytics and massively parallel capabilities
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ibm, technology, netezza, analytics, enterprise analytics
    
Netezza IBM US
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