WPC 300 Business Analytics 2026 – 100 Questions on ETL, Analytics Types & Decision Biases Exam

This document contains approximately 100 exam-style questions with verified answers based on business analytics concepts and frameworks, aligned with Bulletproof Problem Solving by Charles Conn & Robert McLean and foundational analytics coursework. It provides comprehensive coverage of analytics types, ETL processes, data classification, and decision-making biases used in business and data-driven environments. The content is structured in a clear Q&A format to support both conceptual understanding and exam-focused preparation. As shown in the document (page 1), analytics is defined as the process of developing actionable decisions based on insights derived from historical data, combining statistics, management science, and technology. Early sections (pages 2–4) outline the agile analytics process, including business discovery, data discovery, data preparation, modeling, and evaluation. The document also explains key data concepts such as primary vs secondary data and the ETL process (extract, transform, load), with examples of data cleaning, formatting, and loading into data warehouses. Mid-sections (pages 4–6) focus on the four major types of analytics: descriptive (what happened), explanatory/diagnostic (why it happened), predictive (what will happen), and prescriptive (what should be done). The document also highlights differences between analytics and heuristics, emphasizing structured, data-driven decision-making versus experience-based approaches. Later sections (pages 6–10) provide detailed coverage of decision-making biases such as anchoring bias, sunk-cost fallacy, availability heuristic, and overconfidence, along with data classification types (nominal, ordinal, interval, ratio) and statistical concepts like population vs sample and measures of central tendency (mean, median, mode). This resource is ideal for students enrolled in WPC 300 or similar Business Analytics, Data Science, or Decision-Making courses. It is suitable for courses such as Business Analytics, Data Analysis, Statistics for Business, and Decision Sciences. Additionally, it benefits business students, analysts, and professionals seeking to strengthen their understanding of analytics frameworks, data processing, and cognitive biases in decision-making. Keywords: WPC 300 exam questions, business analytics fundamentals, descriptive predictive prescriptive analytics, ETL process extract transform load, primary vs secondary data analytics, agile analytics process business discovery, decision making biases anchoring sunk cost availability, heuristics vs analytics decision making, data types nominal ordinal interval ratio, population vs sample statistics, measures of central tendency mean median mode, data warehouse ETL systems, business data analysis concepts, predictive modeling basics, analytics exam prep