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 Olszak, Celina M
Format eBook
LanguageEnglish
Published United Kingdom Auerbach Publications 2020
CRC Press
Auerbach Publishers, Incorporated
Edition1
Subjects
Online AccessGet full text
ISBN9781000218282
1000218287
0367373947
9780367622794
0367622793
9780367373948
DOI10.1201/9780429353505

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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.
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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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
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IBM Model
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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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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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