Business analytics : a data-driven decision making approach for business
Sahay, Amar,
Business analytics : a data-driven decision making approach for business Amar Sahay. - First edition. - New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, (c)2018. - 1 online resource (xiv, 224 pages) - Big data and business analytics collection, .
Part I. Foundations of business analytics (BA) -- 1. Business analytics (BA) at a glance -- 2. Business intelligence (BI), business analytics (BA), and data analytics -- Part II. Descriptive analytics -- 3. Data, data types, and descriptive statistics -- 4. Descriptive analytics: data visualization -- 5. Data visualization with big data -- 6. Basic analytics tools: describing data numerically: concepts and computer analysis -- 7. Wrap-up, cases, and notes on implementation -- References -- Additional readings -- About the author -- Index.
This book is about Business Analytics (BA)--an emerging area in modern business decision making. The first part provides an overview of the field of Business Intelligence (BI) that looks into historical data to better understand business performance thereby improving performance, and creating new strategic opportunities for growth. Business analytics (BA) is about anticipated future trends of the key performance indicators used to automate and optimize business processes. The three major categories of business analytics--the descriptive, predictive, and prescriptive analytics along with advanced analytics tools are explained. The flow diagrams outlining the tools of each of the descriptive, predictive, and prescriptive analytics are presented. We also describe a number of terms related to business analytics. The second part of the book is about descriptive analytics and its applications. The topics discussed are--Data, Data Types and Descriptive Statistics, Data Visualization, Data Visualization with Big Data, Basic Analytics Tools: Describing Data Numerically--Concepts and Computer Applications. Finally, an overview and a case on descriptive statistics with applications and notes on implementation are presented. The concluding remarks provide information on becoming a certified analytics professional (CAP) and an overview of the second volume of this book which is a continuation of this first volume. It is about predictive analytics which is the application of predictive models to predict future trends. The second volume discusses Prerequisites for Predictive Modeling; Most Widely used Predictive Analytics Models, Linear and Non-linear regression, Forecasting Techniques, Data mining, Simulation, and Data Mining.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781631573323
Management--Statistical methods.
Decision making--Statistical methods.
Business planning.
Strategic planning.
analytics business analytics business intelligence data analysis data mining decision making descriptive analytics machine learning modeling neural networks optimization predictive analytics predictive modeling prescriptive analytics quantitative techniques regression analysis simulation statistical analysis time-series forecasting
HD / .B875 2018
Business analytics : a data-driven decision making approach for business Amar Sahay. - First edition. - New York, New York (222 East 46th Street, New York, NY 10017) : Business Expert Press, (c)2018. - 1 online resource (xiv, 224 pages) - Big data and business analytics collection, .
Part I. Foundations of business analytics (BA) -- 1. Business analytics (BA) at a glance -- 2. Business intelligence (BI), business analytics (BA), and data analytics -- Part II. Descriptive analytics -- 3. Data, data types, and descriptive statistics -- 4. Descriptive analytics: data visualization -- 5. Data visualization with big data -- 6. Basic analytics tools: describing data numerically: concepts and computer analysis -- 7. Wrap-up, cases, and notes on implementation -- References -- Additional readings -- About the author -- Index.
This book is about Business Analytics (BA)--an emerging area in modern business decision making. The first part provides an overview of the field of Business Intelligence (BI) that looks into historical data to better understand business performance thereby improving performance, and creating new strategic opportunities for growth. Business analytics (BA) is about anticipated future trends of the key performance indicators used to automate and optimize business processes. The three major categories of business analytics--the descriptive, predictive, and prescriptive analytics along with advanced analytics tools are explained. The flow diagrams outlining the tools of each of the descriptive, predictive, and prescriptive analytics are presented. We also describe a number of terms related to business analytics. The second part of the book is about descriptive analytics and its applications. The topics discussed are--Data, Data Types and Descriptive Statistics, Data Visualization, Data Visualization with Big Data, Basic Analytics Tools: Describing Data Numerically--Concepts and Computer Applications. Finally, an overview and a case on descriptive statistics with applications and notes on implementation are presented. The concluding remarks provide information on becoming a certified analytics professional (CAP) and an overview of the second volume of this book which is a continuation of this first volume. It is about predictive analytics which is the application of predictive models to predict future trends. The second volume discusses Prerequisites for Predictive Modeling; Most Widely used Predictive Analytics Models, Linear and Non-linear regression, Forecasting Techniques, Data mining, Simulation, and Data Mining.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat reader.
9781631573323
Management--Statistical methods.
Decision making--Statistical methods.
Business planning.
Strategic planning.
analytics business analytics business intelligence data analysis data mining decision making descriptive analytics machine learning modeling neural networks optimization predictive analytics predictive modeling prescriptive analytics quantitative techniques regression analysis simulation statistical analysis time-series forecasting
HD / .B875 2018