business intelligence systems

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Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy. IDC believes that this emerging environment is to date still highly undefined, even as businesses must make critical decisions. Should businesses develop in-house or use VARs, systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some hybrid form? Can they use existing infrastructure, or do AI applications and deep learning require new servers with new capabilities? We believe that many of these questions can be
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Group M_IBM Q418
Published By: IBM     Published Date: Oct 03, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business.
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data, enterprise resource planning, customer relationship management, business intelligence, data management systems
    
IBM
Published By: IBM     Published Date: Jan 02, 2014
Business intelligence derived from sophisticated analytics has given large companies an edge for years. It helps them be more competitive, make information---based decisions faster and better, improves operational efficiencies, and boosts the bottom line. Midsize businesses are increasingly eager to reap similar benefits. Business intelligence derived from sophisticated analytics has given large companies an edge for years. It helps them be more competitive, make information---based decisions faster and better, improves operational efficiencies, and boosts the bottom line. Midsize businesses are increasingly eager to reap similar benefits.
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ibm, business analytics, midsize businesses, geeknet, business intelligence, customer volatility, market volatility, variety of data, it managers, implementing analytics, ba systems, ba solutions, in-house analytics, ba capability, scorecarding, time-to-insight, business risk, business planning
    
IBM
Published By: IBM     Published Date: Oct 06, 2014
Business Intelligence (BI) has become a mandatory part of every enterprise’s decision-making fabric. Unfortunately in many cases, with this rise in popularity, came a significant and disturbing complexity. Many BI environments began to have a myriad of moving parts: data warehouses and data marts deployed on multiple platforms and technologies – each requiring significant effort to ensure performance and support for the various needs and skill sets of the business resources using the environment. These convoluted systems became hard to manage or enhance with new requirements. To remain viable and sustainable, they must be simplified. Fortunately today, we have the ability to build simpler BI technical environments that still support the necessary business requirements but without the ensuing management complexity. This paper covers what is needed to simplify BI environments and the technologies that support this simplification.
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data warehouses, bi environments, bi technologies, faster deployments
    
IBM
Published By: Sun Microsystems     Published Date: Jan 11, 2010
In this free webcast, learn how business intelligence is changing-and how to best keep pace with it. The amount of available data is exploding; yet much of it is kept in separate silos, where it can't be combined to form meaningful insights. This webcast introduces the latest business intelligence technology that can help you discover your insight "needle" in a haystack of data.
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sun, webcast, business intelligence, open source, data, data management, sun microsystems, databasing
    
Sun Microsystems
Published By: Attivio     Published Date: Apr 07, 2010
In this paper, well known data management authority Mark Albala proposes replacing the reliance on data models as the fixed navigation scheme used for storing, reporting and analyzing information with a new unified information access capability that enables more agile, insightful and pro-active decisions.
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attivio, post-discovery intelligent application, analytic information delivery, business intelligence, enterprise applications, executive information systems, eis
    
Attivio
Published By: Oracle     Published Date: Feb 26, 2014
This white paper offers a brief overview of how organizations can make best use of social data by implementing a framework to integrate social data with other enterprise and public or curated data. This framework provides a platform for uncovering new insights that can be fed into business intelligence and customer-experience-management systems in near real time to help marketing, sales, service, and commerce teams accelerate decision-making and create long-term, profitable customer relationships.
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oracle, srm, social, social data, enterprise, business intelligence, customer experience management, customer experience, customer relationships, marketing, social media
    
Oracle
Published By: Epicor     Published Date: Jun 22, 2017
If you’ve started to think your lumber and building materials (LBM) business could be getting more from your software, then it might be time for a change. It is no longer sufficient to own a solution that is “good enough.” The most successful LBM companies know that growth comes from integrated online trading, access to business intelligence tools, and using technology to be more efficient. It can be daunting to make the switch to a new enterprise resource planning (ERP) system, and with so many options, it’s hard to know when if you’re choosing the right one. Epicor has provided LBM businesses with the tools needed to make the most informed software choice. The lumber and building materials solutions evaluation kit consists of three white papers that tell you: • How to know when you’ve outgrown your current software solution • How to choose between generic and industry-specific ERP systems • How to outperform in an era of LBM sales growth You’re ready for growth. Learn how Epicor ca
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lumber, building materials, lbm, erp, bistrack, building materials distributors, lumber distributors, lumber manufacturers
    
Epicor
Published By: NetApp     Published Date: Mar 05, 2018
Did you know that by 2020, 50% of analytic queries will be generated using search, natural-language processing or voice, or will be automatically generated? Read the Gartner report Technology Insight for Modern Analytics and Business Intelligence Platforms and find out how to meet the time-to-insight demands of today's competitive business environment. Learn how to: • Determine when to use existing, traditional BI technologies versus modern analytics and BI • Broaden data access beyond relational systems • Adopt new approaches to data modeling
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netapp, database performance, flash storage, data management, cost challenges
    
NetApp
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