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wpc 300 final Study Guide Exam latest 2024/2025

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Voorbeeld 3 van de 21 pagina's

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 Predictive Analytics - CORRECT ANSWER-- Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future. Question: (1) What will happen next? (2) Why will it happen next? Methods: (1) Data mining (2) Text mining (3) Forecasting Outcome: Accurate projections of future outcomes and events Prescriptive Analytics - CORRECT ANSWER-- Prescriptive analytics answers the question of what to do by providing information on optimal decisions based on the predicted future scenarios. The key to prescriptive analytics is being able to use big data, contextual data and lots of computing power to produce answers in real time. Question: (1) What should be done about it? (2) Why should you do it? Methods: (1) Optimization (2) Simulation (3) Expert systems Outcome: Best possible business decision and outcome


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