2.3.3 Module 2 Quiz – Data Collection and Gathering Exam Answers Full 100% 2023 2024
2.3.3 Module 2 Quiz – Data Collection and Gathering Exam Answers consist of all questions and answers with clear explanations. To get full 100%, you have to review all these questions below.
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The four V’s of Big Data are volume, velocity, variety, and veracity. What is meant by variety?
- The volume of data in motion.
- The amount of data cleaning that is required.
- The rate at which data is generated.
- The data type that is not ready for processing and analysis.
Answers Explanation & Hints:
The variety in the four V’s of Big Data refers to the different types and sources of data that are available. This includes both structured and unstructured data from a variety of sources such as social media, sensors, web logs, and more. With the increasing availability of new data sources and formats, managing and analyzing such a variety of data can be challenging. The variety of data can affect the way it is stored, processed, and analyzed. This requires specialized tools and techniques to handle different types of data in order to extract meaningful insights and value from it.
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What big data term includes reducing the amount of data cleaning that is required?
- Volume
- Variety
- Velocity
- Veracity
Answers Explanation & Hints:
The big data term that includes reducing the amount of data cleaning that is required is veracity. Veracity refers to the quality or trustworthiness of the data, and it encompasses data accuracy, consistency, completeness, and reliability. By ensuring data veracity, it is possible to reduce the amount of data cleaning and preparation required before it can be used for analysis. This includes identifying and addressing issues with data quality, such as missing values, inconsistencies, errors, and duplication. By improving the veracity of data, it becomes more reliable and valuable for decision-making purposes.
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What is the correct order of the stages in the data pipeline?
- Ingestion, Transformation, Analysis, Storage
- Ingestion, Analysis, Transformation, Storage
- Ingestion, Storage, Transformation, Analysis
- Ingestion, Transformation, Storage, Analysis
Answers Explanation & Hints:
The correct order of the stages in the data pipeline is: Ingestion, Transformation, Storage, Analysis.
- Ingestion: This is the stage where data is collected from various sources and brought into the data pipeline. This can involve data streaming or batch processing techniques.
- Transformation: Once data has been collected, it needs to be transformed into a format that can be processed and analyzed. This can include cleaning, normalization, and structuring the data.
- Storage: After transformation, data needs to be stored in a way that makes it accessible for analysis. This can involve a variety of storage options such as data warehouses, data lakes, or cloud storage.
- Analysis: The final stage of the data pipeline involves the use of tools and techniques to analyze the data and extract insights from it. This can include visualization tools, machine learning algorithms, or statistical analysis.