Use Of Data Analytics In Business
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Win with Advanced Business Analytics
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.
Data Analytics for Business
Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.
Effective Use of Data Analytics and Its Impact on Business Performance Within Small-to-medium-sized Businesses
Business use of data analytics and its potential impact on firm performance have become topics of deep interest within both the business practitioner and academic communities. While previous research has demonstrated relationships between data analytics and firm performance in larger firms, there is limited research on whether and how data analytics is used within and impacts Small-to-Medium-sized Business (SMB) settings. Given the preponderance of SMBs within the US economy, and their contribution to employment and economic activity, it is important for SMB owners to understand what management practices lead to effective use of data analytics that in turn impacts SMB performance. Drawing upon the Resource-Based View (RBV) of the firm and prior empirical research on practices within large firms, this dissertation identifies the resources that are needed to form a Data Analytics Capability (DAC) and examines the relationship between the maturity of DACs and the extent of business value realized. The research model was tested using Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis of survey data gathered from a sample of 300 SMB firms in the US, complemented with qualitative interviews of SMB owners. The results provide evidence that a more developed DAC can lead to higher Data Analytics Business Value across business functions.