5.Question 5____________ is ideal for data lakes where transformations on data are applied before raw data is loaded into the data lake.1 pointETL (Extract-Transform-Load) ProcessData PipelineBatch Processing Stream Processing

3.Question 3What is the Extract, Transform, and Load (ETL) process’s primary purpose in data management?1 pointTo create data pipelines for real-time data movement.To manage data repositories and databases.To extract data from data repositories and store it in raw form.To convert raw data into analysis-ready data by extracting, cleaning, standardizing, and transforming it.

.Question 1Which Data Science category do you extract, transform, and load data?1 pointData VisualizationData ManagementData Integration and TransformationModel Building

Which of the following is a reason for storing data in a data lake?1 pointIt is ready for applying to analytics and extracting reports. The structure and goal of the data is known and well defined.Future unknown values may be found in the data. 5.Question 5Which of the following computing environments is likely to

1.Question 1Which API does Apache Spark Structured Streaming use for processing streaming data? 1 pointDataFrame and Dataset APIs Kafka Streaming API Spark Streaming API Spark SQL API 2.Question 2Which output mode in Spark Structured Streaming is particularly useful for managing late-arriving data points? 1 pointOverwrite mode Append mode Update mode Complete mode 3.Question 3Which Spark feature allows you to query a dataframe? 1 pointPipeline SparkSQL DataFrame RDD 4.Question 4Which transformer/extractor counts the occurrences of each term in the text and constructs a vector representation? 1 pointStringIndexer StopWordsRemover StandardScaler CountVectorizer 5.Question 5In a certain SparkML pipeline, there are these 3 stages StandardScaler, VectorAssembler, and Linear Regression. Which of the following is the correct order? 1 pointVectorAssembler, StandardScaler, Linear Regression Linear Regression, StandardScaler, VectorAssembler StandardScaler, Linear Regression, VectorAssembler StandardScaler, VectorAssembler, Linear Regression 6.Question 6In which phase of the ETL are you likely to encounter "save data to parquet file"? 1 pointLoad Model Building Transform Extract 7.Question 7What does a StringIndexer do? 1 pointConverts categorical string columns into numerical indices. Converts numerical columns into strings. Indexes strings so that they can be accessed quicker. Converts floating point columns into string indices. 8.Question 8What does a Tokenizer do? 1 pointConverts text into words. Converts text into symbols called tokens. Assigns a token to each row of the dataset. Is used to compress text. 9.Question 9Which Pyspark component is used to load a stored model? 1 pointPipelineModel Pipeline Model ModelLoader 10.Question 10In which phase of the ETL process would you typically perform "data validation"? 1 pointLoad Extract Model Building Transform

Which of the following is a primary step in data processing?a. Data analysisb. Data collectionc. Data interpretationd. Data visualization