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Integration Challenges for Analytics, Business Intelligence, and Data Mining

Integration Challenges for Analytics, Business Intelligence, and Data Mining
Author: Azevedo, Ana
Publisher: IGI Global
Total Pages: 250
Release: 2020-12-11
Genre: Computers
ISBN: 1799857832
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As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.

Integration of Data Mining in Business Intelligence Systems

Integration of Data Mining in Business Intelligence Systems
Author: Azevedo, Ana
Publisher: IGI Global
Total Pages: 340
Release: 2014-09-30
Genre: Computers
ISBN: 1466664789
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Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

Business Intelligence, Analytics, and Data Science

Business Intelligence, Analytics, and Data Science
Author: Ramesh Sharda
Publisher: Pearson
Total Pages: 515
Release: 2016-12-12
Genre: Business & Economics
ISBN: 0134635310
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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For courses on Business Intelligence or Decision Support Systems. A managerial approach to understanding business intelligence systems. To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice.

Business Intelligence Guidebook

Business Intelligence Guidebook
Author: Rick Sherman
Publisher: Newnes
Total Pages: 551
Release: 2014-11-04
Genre: Computers
ISBN: 0124115284
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Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors’ tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you’ll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. Provides practical guidelines for building successful BI, DW and data integration solutions. Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses Describes best practices and pragmatic approaches so readers can put them into action. Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.

Win with Advanced Business Analytics

Win with Advanced Business Analytics
Author: Jean-Paul Isson
Publisher: John Wiley & Sons
Total Pages: 416
Release: 2012-09-25
Genre: Business & Economics
ISBN: 1118417089
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Plain English guidance for strategic business analytics and big data implementation In today's challenging economy, business analytics and big data have become more and more ubiquitous. While some businesses don't even know where to start, others are struggling to move from beyond basic reporting. In some instances management and executives do not see the value of analytics or have a clear understanding of business analytics vision mandate and benefits. Win with Advanced Analytics focuses on integrating multiple types of intelligence, such as web analytics, customer feedback, competitive intelligence, customer behavior, and industry intelligence into your business practice. Provides the essential concept and framework to implement business analytics Written clearly for a nontechnical audience Filled with case studies across a variety of industries Uniquely focuses on integrating multiple types of big data intelligence into your business Companies now operate on a global scale and are inundated with a large volume of data from multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third party vendor data, macroeconomic data, etc. Packed with case studies from multiple countries across a variety of industries, Win with Advanced Analytics provides a comprehensive framework and applications of how to leverage business analytics/big data to outpace the competition.

Integration of Data Mining in Business Intelligence Systems

Integration of Data Mining in Business Intelligence Systems
Author: Ana Azevedo
Publisher:
Total Pages:
Release: 2015
Genre: Business intelligence
ISBN: 9781322212548
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"This book investigates the incorporation of data mining into business technologies used in the decision making process, emphasizing cutting-edge research and relevant concepts in data discovery and analysis"--

Business Intelligence and Data Mining

Business Intelligence and Data Mining
Author: Anil Maheshwari
Publisher: Business Expert Press
Total Pages: 226
Release: 2014-12-31
Genre: Business & Economics
ISBN: 1631571214
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“This book is a splendid and valuable addition to this subject. The whole book is well written and I have no hesitation to recommend that this can be adapted as a textbook for graduate courses in Business Intelligence and Data Mining.” Dr. Edi Shivaji, Des Moines, Iowa “As a complete novice to this area just starting out on a MBA course I found the book incredibly useful and very easy to follow and understand. The concepts are clearly explained and make it an easy task to gain an understanding of the subject matter.” -- Mr. Craig Domoney, South Africa. Business Intelligence and Data Mining is a conversational and informative book in the exploding area of Business Analytics. Using this book, one can easily gain the intuition about the area, along with a solid toolset of major data mining techniques and platforms. This book can thus be gainfully used as a textbook for a college course. It is also short and accessible enough for a busy executive to become a quasi-expert in this area in a couple of hours. Every chapter begins with a case-let from the real world, and ends with a case study that runs across the chapters.

Real-world Data Mining

Real-world Data Mining
Author: Dursun Delen
Publisher: Pearson Education
Total Pages: 289
Release: 2015
Genre: Business & Economics
ISBN: 0133551075
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As business becomes increasingly complex and global, decision-makers must act more rapidly and accurately, based on the best available evidence. Modern data mining and analytics is indispensable for doing this. Real-World Data Mining demystifies current best practices, showing how to use data mining and analytics to uncover hidden patterns and correlations, and leverage these to improve all business decision-making. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, Delen provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: data mining processes, methods, and techniques; the role and management of data; tools and metrics; text and web mining; sentiment analysis; and integration with cutting-edge Big Data approaches. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials.

Research Anthology on Big Data Analytics, Architectures, and Applications

Research Anthology on Big Data Analytics, Architectures, and Applications
Author: Information Resources Management Association
Publisher: Engineering Science Reference
Total Pages: 0
Release: 2022
Genre: Big data
ISBN: 9781668436622
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Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Managerial Perspectives on Intelligent Big Data Analytics

Managerial Perspectives on Intelligent Big Data Analytics
Author: Sun, Zhaohao
Publisher: IGI Global
Total Pages: 335
Release: 2019-02-22
Genre: Computers
ISBN: 1522572783
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Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.