analytical data

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Published By: IBM     Published Date: Mar 05, 2014
For many years, companies have been building data warehouses to analyze business activity and produce insights for decision makers to act on to improve business performance. These traditional analytical systems are often based on a classic pattern where data from multiple operational systems is captured, cleaned, transformed and integrated before loading it into a data warehouse. Typically, a history of business activity is built up over a number of years allowing organizations to use business intelligence (BI) tools to analyze, compare and report on business performance over time. In addition, subsets of this data are often extracted from data warehouses into data marts that have been optimized for more detailed multi-dimensional analysis.
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ibm, big data, data, big data platform, analytics, data sources, data complexity, data volume, data generation, data management, storage, acceleration, business intelligence, data warehouse
    
IBM
Published By: Cisco     Published Date: Dec 21, 2016
Self-service analytics implies that users design and develop their own reports and do their own data  analysis with minimal support by IT. Most recently, due to the availability of tools, such as those from Qlik,  Spotfire, and Tableau, self-service analytics has become immensely popular. Besides powerful analytical  and visualization capabilities, they all support functionality for accessing and integrating data sources.  With respect to this aspect of data integration four phases can be identified in the relatively short history  of self-service analytics. This whitepaper describes these four phases in detail and shows how the tools  Cisco Data Preparation (CDP) and Cisco Information Server (CIS) for data virtualization can strengthen and  enrich the self-service data integration capabilities of tools for reporting and analytics.  
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Cisco
Published By: IBM     Published Date: Jul 22, 2014
Listen to an interactive discussion (socialcast) with a select group of IBM Data Scientists that goes beyond the tools and tackles new ways your business can use data.
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ibm, it operations analytics, it operations, analytical applications, data, big data, it app infrastructure, cloud, data science, ibm software
    
IBM
Published By: IBM     Published Date: Jan 14, 2015
Decision makers need data and they need it now. As the pace of business continues to accelerate, organizations are leaning heavily on data warehouses to deliver analytical grist for the mill of daily decisions. This Research Report from Aberdeen Group examines the benefits of data warehouse solutions that offer rapid information delivery while minimizing complexity for users and IT.
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aberdeen group, data warehouse, data center, data management, analytic tools, collaboration, data trust, data analytics
    
IBM
Published By: IBM     Published Date: Jul 15, 2015
The Forrester Wave.
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big data, analytics solutions, evaluate, analytical data, strategy
    
IBM
Published By: SPSS     Published Date: Mar 31, 2009
This whitepaper details how predictive analysis can help your business.  Predictive analytics help you make better, faster decisions, giving your organization a significant competitive advantage in the technology sector.
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spss, predictive analysis, roi, data, data driven decision making, mitigate risk, fraud, real time intelligence, data analysis, analytical methods, strategic planning, customer intimacy, crm, best practices, business intelligence, statistics, statistical analysis, data management, decision-making
    
SPSS
Published By: SPSS     Published Date: Jun 30, 2009
In an intensely competitive marketplace, knowledge is power. The more an airline can learn about what its customers like and don't like about its offerings, the more effective it can be at building customer loyalty and maximizing its revenues.
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spss, american airlines, customer loyalty, maximize revenues, roi, specialized market intelligence, production of information, increased productivity, best practices, statistical analysis, analytical methods, statistics, crm, consumer research, data trends, program macros, research, data management, decision-making
    
SPSS
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
This whitepaper details how predictive analysis can help your business.  Predictive analytics help you make better, faster decisions, giving your organization a significant competitive advantage in the marketing sector.
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spss, predictive analysis, roi, data, data driven decision making, mitigate risk, fraud, real time intelligence, data analysis, analytical methods, strategic planning, customer intimacy, crm, best practices, business intelligence, statistics, statistical analysis, data management, decision-making, web analytics
    
SPSS, Inc.
Published By: SPSS, Inc.     Published Date: Mar 31, 2009
In an intensely competitive marketplace, knowledge is power. The more an airline can learn about what its customers like and don't like about its offerings, the more effective it can be at building customer loyalty and maximizing its revenues.
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spss, american airlines, customer loyalty, maximize revenues, roi, specialized market intelligence, production of information, increased productivity, best practices, statistical analysis, analytical methods, statistics, crm, consumer research, data trends, program macros, research, data management, decision-making, web analytics
    
SPSS, Inc.
Published By: SAS     Published Date: Apr 25, 2017
Are you a marketing leader on the path to modernizing your marketing organization? Are you a marketing analyst championing analytical transformation in your campaigns? If you answered yes to either question, this e-book is for you. It offers a practical account of how to create a new marketing culture that adds value through data and analytics. You’ll meet marketing leaders from Comerica, Lenovo, RCI, SAS and Visa – and read how they’re implementing analytics, redefining marketing strategies and transforming their cultures. By sharing their perspectives, we hope to provide a new set of best practices to guide your analytical transformation – and to help you reinvent your marketing organization for the digital age.
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SAS
Published By: SAS     Published Date: Jun 05, 2017
If you’re dealing with large amounts of data and complex problems, you might be ready to hire a data scientist. But what will you ask in the interview, and how will you evaluate the candidates? In this e-book, we provide 20 interview questions, so you can walk right into the interview knowing what to ask. We also profile three working data scientists, so you can better understand the backgrounds and habits of this new breed of analytical data expert. Whether you’re hiring your first data scientist or your fifteenth, we hope this e-book helps you find the right candidate.
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SAS
Published By: SAS     Published Date: Oct 18, 2017
Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications such as driverless cars. This paper, based on presentations by SAS Data Scientist Wayne Thompson, introduces key machine learning concepts and describes SAS solutions that enable data scientists and other analytical professionals to perform machine learning at scale. It tells how a SAS customer is using digital images and machine learning techniques to reduce defects in the semiconductor manufacturing process.
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SAS
Published By: DataSynapse     Published Date: Feb 26, 2007
Today's business drives application use, but it is how these applications are deployed and managed that can deliver differentiation value to the business. Whether your challenge is one of scale, optimization, heterogeneity or complexity – learn how flexibility can be built in at the application layer.  Download this analyst bulletin today!
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application integration, desktop management, analytical applications, enterprise applications, application performance management, datasynapse, data synapse, application layer
    
DataSynapse
Published By: WorldTelemetry, Inc.     Published Date: Mar 26, 2007
Business Intelligence Software are applications that build on existing data warehouses and provide analytical processing tools that allow users to more effectively analyze such data. This, in turn, permits businesses to more rapidly develop existing and new analyses and reports for improved decision-making power and information dissemination capacity.
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analytical applications, business analytics, business metrics, business intelligence, enterprise software, bi software, world telemetry, worldtelemetry
    
WorldTelemetry, Inc.
Published By: IBM Software     Published Date: Oct 05, 2010
Read how Business analytics investments are more important than ever for business competitiveness and profitability and are becoming increasingly essential to maximize a company's return on investment.
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ibm cognos, business analytics, business intelligence, bi investment, analytical methods, business planning, data analysis
    
IBM Software
Published By: Sage     Published Date: Oct 17, 2019
Imagine a factory which connects information and interconnectivity—a model of quiet efficiency. Where intelligent machines collaborate with each other, run by a team of analytical, well-trained workers. A center of innovation—the hub of a supply chain that combines customers, suppliers, distributors, and partners with advanced analytical systems. Now imagine the future—the Smart Factory, where there’s minimal downtime, neglect, waste, and inefficiency. Where factory managers, financial experts and boardroom executives use cutting-edge technology to understand data and production—reaching the pinnacle of technology and manufacturing development. The Smart Factory dream is closer than you think.
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Sage
Published By: IBM     Published Date: Jul 05, 2018
Scalable data platforms such as Apache Hadoop offer unparalleled cost benefits and analytical opportunities. IBM helps fully leverage the scale and promise of Hadoop, enabling better results for critical projects and key analytics initiatives. The end-to- end information capabilities of IBM® Information Server let you better understand data and cleanse, monitor, transform and deliver it. IBM also helps bridge the gap between business and IT with improved collaboration. By using Information Server “flexible integration” capabilities, the information that drives business and strategic initiatives—from big data and point-of- impact analytics to master data management and data warehousing—is trusted, consistent and governed in real time. Since its inception, Information Server has been a massively parallel processing (MPP) platform able to support everything from small to very large data volumes to meet your requirements, regardless of complexity. Information Server can uniquely support th
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IBM
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
Published By: TIBCO Software     Published Date: May 31, 2018
Predictive analytics, sometimes called advanced analytics, is a term used to describe a range of analytical and statistical techniques to predict future actions or behaviors. In business, predictive analytics are used to make proactive decisions and determine actions, by using statistical models to discover patterns in historical and transactional data to uncover likely risks and opportunities. Predictive analytics incorporates a range of activities which we will explore in this paper, including data access, exploratory data analysis and visualization, developing assumptions and data models, applying predictive models, then estimating and/or predicting future outcomes. Download now to read on.
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TIBCO Software
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