How does automating data collection and preparation processes affect the overall project time?1 pointAutomating data collection and preparation can reduce data preparation time by up to 50 percentAutomating data collection and preparation minimizes the need for data understandingAutomating data collection and preparation prolongs the data science project timelineAutomating data collection and preparation processes significantly reduces data collection

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

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

Adventure Works is considering automating its data ingestion process to accommodate a recent increase in data volume and variety. As a data analyst, you need to advise on this decision. What would you say are the benefits of automating data ingestion? 1 pointAutomating the process can enhance operational efficiency and reduce manual labor.Automating the process will eliminate the need for data governance and quality control measures.Automating the process will eliminate the need for data cleansing and preparation.Automating the process decreases the risk of data errors and inconsistencies.

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

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