Data Handling and Wrangling Quiz

Which of the following is a challenge in handling large volumes of data?

• Storage

• Processing time

• Data inconsistency

• All of the above

Which framework is widely used for handling large-scale data processing?

• Pandas

• NumPy

• Apache Spark

• Matplotlib

Which database type is most suitable for handling large datasets efficiently?

• Relational Databases (SQL)

• NoSQL Databases

• Flat files

• Excel Sheets

Which technique is commonly used to store and retrieve large-scale data efficiently?

• Distributed File Systems

• Indexing

• Data Partitioning

• All of the above

Which of the following is a way to improve performance when handling large datasets?

• Using parallel processing

• Storing data in JSON format

• Avoiding data compression

• Using CSV instead of Parquet

What is data wrangling?

• Cleaning and structuring data for analysis

• Converting raw data into a usable format

• Removing all outliers

• Storing data in databases

Which of the following is NOT a step in data wrangling?

• Data cleaning

• Data transformation

• Data visualization

• Ignoring missing values

Which Python library is most commonly used for data wrangling?

• TensorFlow

• Pandas

• OpenCV

• Matplotlib

Which method is used to convert unstructured data into structured data?

• Data Mining

• Data Collection

• Data Wrangling

• Data Storage

What is the main goal of data wrangling?

• Making data suitable for analysis

• Eliminating data sources

• Making data visualization easier

• Storing data in an unstructured format