wpc 300 final Study Guide Exam latest 2024/2025

wpc 300 final Study Guide Exam latest 2024/2025 Principles of Problem Framing - CORRECT ANSWER-Tell, find and routinize Tell an interesting and complete story - CORRECT ANSWER-The problem you address should be meaningful Solution could be reused for related problems Assumptions, boundaries Find an appropriate solution framework - CORRECT ANSWER-Break down the problem into pieces Iterative process (agile vs waterfall) Identify appropriate analytical/modeling techniques Routinize the procedure - CORRECT ANSWER-Documentation Next similar questions can be solved quickly Build a system (macros, codes, programs) Analytics - CORRECT ANSWER-is the process of developing actionable decisions or recommendations for actions based on insights generated from historical data Primary Data - CORRECT ANSWER-Survey Interviews (marketing firm's telephone interviews) Used a lot in marketing research Secondary Data - CORRECT ANSWER-Firm's proprietary database Internet data (crawlers) [scarpy, beautifulsoup] Stock/capital market data [compustat, CRSP] Accounting disclosure data [ from 10K, 10Q] Simulated Data - CORRECT ANSWER-Data based on assumption and simulation Used a lot in scheduling, routing and queuing Data Extraction - CORRECT ANSWER-Extract data from primary/secondary source. Data Transformation - CORRECT ANSWER-Transform / clean data into proper format or structure for the purpose of querying & analysis Data Load - CORRECT ANSWER-Load data into final target database, more specifically an operational data store, data mart or data warehouse Descriptive Analytics - CORRECT ANSWER-- This is a preliminary stage of data processing that creates a summary of historical data to yield useful information and possibly prepare the data for further analysis. Questions: (1) What happened? (2) What is happening? Methods: (1) Standard reporting (2) Dashboards (3) Visual analytics Outcome: Well defined business problems and opportunities Diagnostic/Explanatory Analytics - CORRECT ANSWER-- this is about looking into the past and determining why a certain thing happened. This type of analytics usually revolves around working on a dashboard. Question: (1) Why did it happen? (2) How did it happen? Methods: Inferential Statistics, Visual analytics Outcome: Discover/Understand causal relationships of an outcome