Paper Title
SIMPLIFYING BUSINESS ANALYTICS TOOLS AND TECHNIQUES FOR THE IMPLEMENTATION OF DATA MINING, DATA VISUALIZATION, AS WELL AS INFERENTIAL STATISTICAL ANALYSIS, FOR BUSINESSES, SMALL AND LARGE.

Abstract
Abstract - Procuring and interpreting business related data, for any size business, is the key to success in the modern commercial era. Over six decades ago, John Tukey defined data analysis as "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise, more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data.” The academic discipline of Business Analytics focuses on tips to accomplish the mining, visualization, and analysis goals derived from various business-related datasets. If data mining/visualization/analysis efforts posses misuse of applicable tools, and/or technique flaws, the business knowledge discovery process could vary well provide zero insight for decision making! This presentation discusses the contemporary environment of business data mining, and data visualization, including techniques that most certainly mislead most visualization audiences. A progression layout of the evolution in the field of business data analytics is described. EDA (exploratory data analysis), visualizing time series versus cross-sectional data, data display networks, and data mapping are addressed concepts, as well as methods and tools for static and interactive graphics in business processes. Quantitative analytics tools, that likely all conference attendees have learned in their schooling years, will be championed, with contemporary business environment examples. Finally, contemporary software packages utilized in business analytics data mining, visualization, and quantitative analysis are examined.