Data Analytics Applications- Anti-Analytics

By avoiding common misconceptions, decision-makers can improve outcomes and enhance problem-solving capabilities. The book explains how Anti-Analytics can be used to correct process design, improve decision-making, and improve data analytics procedures. Meet Matt! Matt is the Mathematical and Analytical Thinker as well as the narrator of Anti-Analytics: How Not to and How to Use Data Analytics in Business. Matt explains how managers can successfully apply data analytics to business problems. Matt shares insight into developing a business analytics mindset that fosters the conditions under which organizations can develop business intelligence, create value, and build sustainable competitive advantage. The book introduces the concept of Anti-Analytics, which are the practices and processes preventing the proper adoption and adaptation of analytics-based approaches. The book explains how to: Enhance the sustainability of data analytics projects to achieve higher levels of strategic intelligence Determine the best of the mix of managers and technology to create organizational value Reduce errors in the analysis and design of data analytics systems Anti-analytics and the business analytics mindset can also help organizations manage the uncertainty surrounding AI’s application and integration into broader organizational and societal systems. Because Generative AI models and basic AI solutions are widely accessible, organizations can easily adopt this technology. The real advantage of AI, as well as data analytics, comes from users with an analytical mindset who can manage and operate organizations in ways that solve increasingly complex problems. This book shows how to develop this analytical mindset that can create business solutions delivering value and competitive advantage now and in the future.