Business Intelligence and Big Data Drivers of Organizational Success
The 21st century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under increasing pressure to succeed. The question arises what does success mean, is success a matter of chance and luck, or maybe success is a category t...
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Main Author | |
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Format | eBook |
Language | English |
Published |
United Kingdom
Auerbach Publications
2020
CRC Press Auerbach Publishers, Incorporated |
Edition | 1 |
Subjects | |
Online Access | Get full text |
ISBN | 9781000218282 1000218287 0367373947 9780367622794 0367622793 9780367373948 |
DOI | 10.1201/9780429353505 |
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Abstract | The 21st century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under increasing pressure to succeed. The question arises what does success mean, is success a matter of chance and luck, or maybe success is a category that can be planned and properly supported.
Business Intelligence and Big Data: Drivers of Organizational Success examines how the success of an organization largely depends on the ability to anticipate and quickly respond to challenges from the market, customers and other stakeholders. Success is also associated with the potential to process and analyze a variety of information and the means to use modern information and communication technologies (ICTs). Success also requires creative behaviors and organizational cleverness from an organization.
The book discusses business intelligence (BI) and big data (BD) issues in the context of modern management paradigms and organizational success. It presents a theoretically and empirically grounded investigation into BI and BD application in organizations and examines such issues as:
Analysis and interpretation of the essence of BI and BD
Decision support
Potential areas of BI and BD utilization in organizations
Factors determining the success with using BI and BD
The role of BI and BD in value creation for organizations
Identifying barriers and constrains related to the BI and BD design and implementation
The book presents arguments and evidence confirming that BI and BD may be a trigger for making more effective decisions, improving business processes, and business performance, as well as creating new business. The book proposes a comprehensive framework on how to design and use BI and BD to provide organizational success. |
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AbstractList | The twenty-first century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under increasing pressure to succeed. The questions facing us today are: What does success mean? Is success a matter of chance and luck or perhaps is success a category that can be planned and properly supported?Business Intelligence and Big Data: Drivers of Organizational Success examines how the success of an organization largely depends on the ability to anticipate and quickly respond to challenges from the market, customers, and other stakeholders. Success is also associated with the potential to process and analyze a variety of information and the means to use modern information and communication technologies (ICTs). Success also requires creative behaviors and organizational cleverness from an organization.The book discusses business intelligence (BI) and Big Data (BD) issues in the context of modern management paradigms and organizational success. It presents a theoretically and empirically grounded investigation into BI and BD application in organizations and examines such issues as:Analysis and interpretation of the essence of BI and BDDecision supportPotential areas of BI and BD utilization in organizationsFactors determining success with using BI and BDThe role of BI and BD in value creation for organizationsIdentifying barriers and constraints related to BI and BD design and implementationThe book presents arguments and evidence confirming that BI and BD may be a trigger for making more effective decisions, improving business processes and business performance, and creating new business. The book proposes a comprehensive framework on how to design and use BI and BD to provide organizational success. The book provides a theoretically and empirically grounded discussion how to design and use business intelligence (BI) and Big Data (BD) to benefit organizations. It examines the conceptualization of BI and BD, applications of BI and BD, BI and BD maturity, and factors of BI- and BD-based success, as well as presents an application framework. The 21st century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under increasing pressure to succeed. The question arises what does success mean, is success a matter of chance and luck, or maybe success is a category that can be planned and properly supported. Business Intelligence and Big Data: Drivers of Organizational Success examines how the success of an organization largely depends on the ability to anticipate and quickly respond to challenges from the market, customers and other stakeholders. Success is also associated with the potential to process and analyze a variety of information and the means to use modern information and communication technologies (ICTs). Success also requires creative behaviors and organizational cleverness from an organization. The book discusses business intelligence (BI) and big data (BD) issues in the context of modern management paradigms and organizational success. It presents a theoretically and empirically grounded investigation into BI and BD application in organizations and examines such issues as: Analysis and interpretation of the essence of BI and BD Decision support Potential areas of BI and BD utilization in organizations Factors determining the success with using BI and BD The role of BI and BD in value creation for organizations Identifying barriers and constrains related to the BI and BD design and implementation The book presents arguments and evidence confirming that BI and BD may be a trigger for making more effective decisions, improving business processes, and business performance, as well as creating new business. The book proposes a comprehensive framework on how to design and use BI and BD to provide organizational success. |
Author | Olszak, Celina M |
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Copyright | 2021 Taylor & Francis Group, LLC |
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DOI | 10.1201/9780429353505 |
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Keywords | Customer Profitability Data Sets Bi Capability Data Warehouse Information Builders Generalized Regression Neural Network Business Case Multiple Linear Regression Business Processes CRM System Maturity Model Bi Model Bi Solution NoSQL Database Bi System IBM Model Bi Tool ITSM Bi Big Data Big Data Adoption Apache Hadoop Bi Project Bi Maturity OLAP Cube |
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PublicationCentury | 2000 |
PublicationDate | 2020 2021 2020-11-18 |
PublicationDateYYYYMMDD | 2020-01-01 2021-01-01 2020-11-18 |
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PublicationDecade | 2020 |
PublicationPlace | United Kingdom |
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PublicationYear | 2020 2021 |
Publisher | Auerbach Publications CRC Press Auerbach Publishers, Incorporated |
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Snippet | The 21st century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under... The book provides a theoretically and empirically grounded discussion how to design and use business intelligence (BI) and Big Data (BD) to benefit... The twenty-first century is a time of intensifying competition and progressive digitization. Individual employees, managers, and entire organizations are under... |
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SourceType | Aggregation Database Publisher |
SubjectTerms | Big data Business intelligence General management |
Subtitle | Drivers of Organizational Success |
TableOfContents | Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- About the Author -- Preface -- 1. Changing Business Environments and Decision Support Systems -- Changing Business Environments -- Growing Information Flows -- New Organizational Structures and a New Distribution of Decision-Making Powers -- New Professions and Fields of Employment -- Customers -- Competition -- Stakeholders -- New Conflicts and Threats -- Resource-based View -- Information and Knowledge - Organization's Strategic Resources -- Knowledge Management -- Creative Employees and Creative Organizations -- Information Communication Technology (ICT) as a Driver of Change and Innovation -- Information Communication Technology (ICT) in Business Value Creation -- Computer Decision Support Systems -- Designing Decision Support Systems -- References -- 2. Business Intelligence in Management of Organizations -- The Essence of Business Intelligence -- Business Intelligence Generations -- Architecture of Business Intelligence Systems -- Data Warehouse -- Extraction-Transformation-Load -- Online Analytical Processing -- Data Extraction -- Visualization and Dashboards -- Models of Business Intelligence Systems -- Data Marts -- BI-Predictive Analysis -- Business Activity Monitoring -- Real-Time BI -- Corporate BI -- BI Portals -- BI Networks -- BI-Business Performance Management -- Development of Business Intelligence Systems -- Business Intelligence Competence Center -- References -- 3. Big Data for Business Intelligence -- Era of Data-intensive Computing -- Big Data Term - Interpretation -- Big Data V Model -- Volume -- Velocity -- Variety -- Veracity -- Visualization -- Variability -- Value -- Techniques for Big Data Analyzing -- Data Mining -- Regression Models -- Time Series Model -- Classification -- Association Rules -- Clustering -- Text Mining -- Web Mining Maturity Models for Business Intelligence -- TDWI's Business Intelligence Model -- Gartner's Maturity Model -- AMR Research's Business Intelligence/Performance Management Maturity Model, version 2 -- Business Information Maturity Model -- Business Intelligence Maturity Hierarchy -- Infrastructure Optimization Maturity Model -- Business Intelligence Development Model -- Lauder of Business Intelligence -- Hewlett Package Business Intelligence Maturity Model -- Information Evaluation Model SAS -- Watson Model -- The Teradata Maturity Model -- Business Intelligence Maturity Models Based on Analytical Capabilities -- Model Proposed by Davenport and Harris -- Model Based on Dynamic Capabilities Business Intelligence -- Big Data Maturity Models -- The TDWI Big Data Maturity Model -- Big Data and Analytics Maturity Model (IBM model) -- Dell Data Maturity Model -- Big Data Business Model Maturity Index -- The Hortonworks Big Data Maturity Model -- Critical Success Factors for Implementing Business Intelligence and Big Data in Organizations -- CSFs for Business Intelligence and Big Data Use -- Big Data-Based Business Value Creation -- Conclusions -- References -- Index Graph Mining -- Network Analysis -- Machine Learning -- Deep Learning -- Neural Networks -- Genetic Algorithms -- Spatial Analysis -- Search-Based Application -- Big Data Technologies -- NoSQL -- Big Table -- Apache Cassandra -- Google File System -- Apache Hadoop -- MapReduce -- Mashup -- Big Data Management -- References -- 4. Analysis of Business Intelligence and Big Data Adoption in Organizations -- Areas of Business Intelligence and Big Data Utilization in Organizations -- Business Intelligence and Big Data in Relational Marketing -- Analysis of Websites -- Designing and Analyzing Marketing Campaigns -- Recommender Systems -- Price Comparison Websites -- Group Shopping -- Customer Relationship Management Systems -- Business Intelligence and Big Data-Based Analyses in Customer Relationship Management -- Customer Profitability -- Customer Time Value -- Customer Segmentation and Profiling -- Market Basket Analysis -- Customer Loyalty and Migration Analysis -- Customer Behavior Analysis -- Fraud Detection -- Business Intelligence and Big Data in Planning and Budgeting -- Business Intelligence and Big Data in Sales and Distribution -- Business Intelligence and Big Data in Insurance -- Business Intelligence and Big Data in Credit Risk Assessment -- Business Intelligence and Big Data in Engineering and Manufacturing -- Business Intelligence and Big Data in Telecommunications -- Business Intelligence and Big Data in Energy Sector -- Business Intelligence and Big Data in the Financial and Banking Sector -- Business Intelligence and Big Data in Logistics Industry -- Business Intelligence and Big Data in Health Care -- Business Intelligence and Big Data in Human Resources Management -- References -- 5. Measurement and Assessment of Business Intelligence and Big Data Development in Organizations -- Maturity Models |
Title | Business Intelligence and Big Data |
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