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business intelligence processes

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Published By: FICO     Published Date: Nov 30, 2016
Historically, manufacturers have “looked to the past” to help predict what they need to do in the future. This would include basic business intelligence, powered by spreadsheets, and even manual processes. The challenge is that what will happen may be something outside of what the past can predicts – who, 25 years ago, would have considered the Internet as a primary vehicle for commerce, or that Big Data would become both a treasure and a tragedy for organizations? Consider other factors, such as regulations, largely transient customers (where loyalty and brand aren’t what they used to be), disruptors (such as new entrants and technologies), and the need for manufacturers to “move faster than ever” – in effect, to be able to plan for the future before it happens.
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manufacturing optimizations, enterprise software, infrastructure, networking, it management, knowledge management, enterprise applications, data management
    
FICO
Published By: IBM     Published Date: Sep 11, 2017
This book is written for readers who have varying levels of familiarity with ODM. It doesn’t focus on any particular vendor’s offering; instead, it talks about the features of ODM as a model for managing operational decision-making. This book isn’t about offline business intelligence systems. While those systems are very valuable, the focus of this book is on automated decisions that can be executed in real time in conjunction with your business applications and processes.
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odm, management, operation-decision making, intelligence systems
    
IBM
Published By: FICO - APAC     Published Date: Jul 10, 2017
Historically, manufacturers have “looked to the past” to help predict what they need to do in the future. This would include basic business intelligence, powered by spreadsheets, and even manual processes.
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FICO - APAC
Published By: SAP Inc.     Published Date: Jul 28, 2009
While historically consumer packaged goods (CPG) organizations have made significant investments in data collection and integration, much of the data stored in their IT infrastructures has not been analyzed or deployed to further the firms' business performance.  Those enterprises that learn to effectively harness the vast quantities of information generated by their IT systems - both within and outside the corporation - will enjoy a substantial competitive advantage.
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sap, business intelligence, business processes, consumer packaged goods, integrating cross-enterprise processes, data management
    
SAP Inc.
Published By: SAP Inc.     Published Date: Jul 28, 2009
Hospitals from across the world are facing increased pressure to improve operations from multiple directions. Legal requirements, an aging population in many developed countries, and an ever-increasing need to be service-oriented are forcing hospitals to do more with less. Those that learn to effectively harness the information generated by their IT systems will enjoy substantial productivity improvements.
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sap, business intelligence, healthcare sector, healthcare industry, bi applications, bi tools, inter-departmental processes, enterprise applications
    
SAP Inc.
Published By: FICO     Published Date: Jun 06, 2017
Historically, manufacturers have “looked to the past” to help predict what they need to do in the future. This would include basic business intelligence, powered by spreadsheets, and even manual processes.
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manufacturing, manufacturing optimization, solutions
    
FICO
Published By: FICO     Published Date: Mar 02, 2018
Improved availability of data and new technologies that use it are disrupting our lives, influencing the way we interact with other, and the way we gather and consume information to make decisions. Businesses too are living in a time of continuous technological upheaval. The application of key technologies such as Machine Learning and Artificial Intelligence and Optimization, are fundamentally changing the manner in which businesses make decisions. This paper is your first step in understanding: • how you can leverage and operationalize analytics in your everyday business processes • improve customer relationships • grow revenue in an increasingly competitive world
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fico, customers, analytic, management, applications, solutions
    
FICO
Published By: SRC,LLC     Published Date: Jun 01, 2009
Companies spend millions of dollars every year on building data warehouses, buying business intelligence (BI) software tools and managing their analytic processes in the hope of gaining consumer insight and winning market share. Yet, many companies fail to realize the full benefits of their technology investments because they are hamstrung by the layers of expertise and the complexity of technology tools needed to integrate various data warehouses and associated tools within their existing analytic environments. Since analysis is only as good as the accessibility, timeliness and accuracy of the information being analyzed, the interoperability of any data warehouse with any analytic environment is essential to achieving insightful, actionable analysis and making better decisions.
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src, enterprise, streamline, analytics, economy, analytic imperative, business intelligence, seamless, data warehouse, interoperability, analytic environment, data assets, report generation, output options, total cost of ownership, tco, roi, return on investment, olap, enterprise applications
    
SRC,LLC
Published By: Vertica     Published Date: Aug 15, 2010
If you are responsible for BI (Business Intelligence) in your organization, there are three questions you should ask yourself: - Are there applications in my organization for combining operational processes with analytical insight that we can't deploy because of performance and capacity constraints with our existing BI environment?
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business intelligence, vertica, aggregated data, olap, rolap, sql, query, data warehouse, oltp, business analytics, linux, application integration, analytical applications, data integration, data mining, data quality, service oriented architecture, web service management, information management, data warehousing
    
Vertica
Published By: SAP     Published Date: Jul 17, 2012
Although IDC is expecting worldwide spending on business analytics software to be $33 billion in 2012, technology is only part of the story. The growing demand for faster response and deeper business insight is forcing companies to adopt a more pervasive approach to business intelligence (BI) that supports evidence-based decision making. Higher BI and analytics competency and pervasiveness are achieved when organizational culture, business processes, and technologies are designed and implemented with the goal of improving or automating all strategic, operational, and tactical decision making capabilities of all stakeholders. Access this paper to learn essential best practices for creating a solid BI and analytics strategy.
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sap, best practices, business intelligence, analytics strategy, technology
    
SAP
Published By: SAP     Published Date: May 15, 2008
Read this white paper by Don Tapscott and explore the criteria best-in-class hospitals use for selecting business intelligence solutions. Companies that learn to effectively harness the information generated by their IT systems will enjoy substantial productivity improvements.
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sap, business intelligence, healthcare sector, healthcare industry, bi applications, bi tools, inter-departmental processes
    
SAP
Published By: SAP     Published Date: Apr 13, 2011
With the business intelligence functionality in SAP® Business All-in-One solutions, your company can gain visibility, insight, operational alignment, and accountability to increase revenue, margins, and liquidity; streamline processes; improve agility; and become a best-run business.
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sap solutions, small businesses, midsize companies, business intelligence, sap business all-in-one, erp, transparency, best practices, business process management
    
SAP
Published By: SAP     Published Date: Apr 13, 2011
SAP® BusinessObjectsT Edge BI software is ideal for midsize companies wanting to improve business intelligence (BI) processes and get an edge on the competition. It can help you address just about any BI requirement - and leverage the applications, data sources, and platforms your company already uses.
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sap businessobjects edge bi, business intelligence processes, midsize companies, data management, data integration, data warehouse, business intelligence, data warehousing
    
SAP
Published By: SAS     Published Date: Mar 06, 2018
Known for its industry-leading analytics, data management and business intelligence solutions, SAS is focused on helping organizations use data and analytics to make better decisions, faster. The combination of self-service BI and analytics positions you for improved productivity and smarter business decisions. So you can become more competitive as you use all your data to take better actions. Instead of depending on hunch-based choices, you can make decisions that are truly rooted in discovery and analytics. And you can do it through an interface that anyone can use. At last, your business users can get close enough to the data to manipulate it and draw their own reliable, fact-based conclusions. And they can do it in seconds or minutes, not hours or days. Equally important, IT remains in control of data access and security by providing trusted data sets and defined processes that promote the valuable, user-generated content for reuse and consistency. But, they are no longer forced
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SAS
Published By: SAS     Published Date: Mar 06, 2018
These emerging technologies and solutions certainly are not unique to financial services. But Stewart, a business director of security intelligence solutions within the SAS Security Intelligence Practice, sees particular interest and application in AML circles. "There remain a good number of manual processes within financial crimes departments in financial institutions, and AI can help automate some of those rote tasks such as document review or alert triage," he says. "Due to investments in technology, there is a lower barrier of entry for midsized institutions. "And finally, there's this anxiety over the unknown - those risks they are not able to detect, that may be hidden using traditional techniques - so they're hoping that more advanced, unsupervised learning techniques can be used to identify those edge cases or behaviors that are out of norm." In an interview about analytics and the AML paradigm shift, Stewart discusses: • The new industry intrigue with artificial intelligence a
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SAS
Published By: SAS     Published Date: Apr 04, 2018
Location analytics is the process of integrating geographical data into business intelligence (BI) and analytics-led decision making. Location analytics creates meaningful insight from relationships found in geospatial data to solve a broad variety of business and social problems. Location data is found everywhere – with an item or a device, in a conversation or behavior, in machines or sensors, tied to a customer or competitor, attached to a database record or recorded from vehicles or other moving objects. Organizations want to take advantage of location data to improve decisions, create better customer engagement and experiences, reduce risks and automate business processes.
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SAS
Published By: IBM     Published Date: Nov 08, 2013
Because all processes should be aligned to customer metrics, process improvement is an important goal for organizations in every industry. This paper illustrates the impact analytics can make on business processes through real-world examples based on IBM client experiences, and describes the steps organizations can take to refine quality, warranty, financial, inventory and other processes that are essential to achieving operational excellence.
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ibm, embedding business analytics, organizational processes, business analytics, building smarter processes, insight and alignment, consistent information, accurate information, business intelligence, connect business processes, performance management, customer metrics, internal processes, external processes, competitive benchmarking, critical insight and alignment, business process management, content integration, productivity
    
IBM
Published By: SAS     Published Date: Apr 25, 2017
Organizations in pursuit of data-driven goals are seeking to extend and expand business intelligence (BI) and analytics to more users and functions. Users want to tap new data sources, including Hadoop files. However, organizations are feeling pain because as the data becomes more challenging, data preparation processes are getting longer, more complex, and more inefficient. They also demand too much IT involvement. New technology solutions and practices are providing alternatives that increase self-service data preparation, address inefficiencies, and make it easier to work with Hadoop data lakes. This report will examine organizations’ challenges with data preparation and discuss technologies and best practices for making improvements.
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SAS
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