Select the correct statement about the Data Preparation stage of the data science methodology.1 pointThe Data Preparation stage involves handling missing and improperly coded data and can include using text analysis to structure unstructured or semi-structured text dataThe Data Preparation stage cannot be accelerated using automationThe Data Preparation stage is typically the least time-consuming methodological stepData scientists only use feature engineering when manually preparing the data

How does the Data Preparation stage affect the next steps in a data science project?1 pointThe Data Preparation stage ensures data visualization accuracy.The Data Preparation stage defines the problem statement.The Data Preparation stage provides clean and formatted data for analysis.The Data Preparation stage determines the project timelin

Select the correct statements that describe what data scientists do during the Data Preparation stage.1 pointDuring the Data Preparation stage, data scientists determine the timing of eventsDuring the Data Preparation stage, data scientists separate data and data sources.During the Data Preparation stage, data scientists define the variables to be used in the model.During the Data Preparation stage, data scientists ignore missing data

Question 2Which of the following statements represents the essential characteristics of the data science methodology?1 pointData Science Methodology is a highly iterative process. At any point in the methodology, data scientists can decide to repeat a stage or revisit a prior stage and work forward from that previous stage.Data Science Methodology stages and work ends immediately ends when the data scientist deploys the model.Data Science Methodology has no endpoint because data collection occurs before identifying the data requirements.Data Science Methodology stages immediately end after data scientists deploy the code because no feedback is required

Why is the Data Preparation stage considered time-consuming for a data science project?1 pointThis stage requires creating advanced data visualizations.This stage involves transforming data into a usable formatThis stage requires a deep understanding of machine learningThis stage involves running complex algorithm

Which of the following is a NOT stage of the data preparation process?a.questionnaire checkingb.editingc.transcribingd.data cleaninge.All of the above are stages of the data preparation process