Microsoft Certified Azure Data Fundamentals · Free Practice Question Medium
Question 32
What technologies are commonly used for processing and querying data stored in data lakes?
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A
Traditional relational database management systems (RDBMS)
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B
Data warehousing tools optimized for SQL queries.
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C
Distributed processing frameworks like Spark or Hadoop.
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D
Data visualization tools for creating reports and dashboards.
Reveal correct answer
Correct answer: C
Explanation
Data lakes often store large amounts of data. Distributed processing frameworks like Apache Spark or Hadoop are well-suited for handling such large datasets. These frameworks can process data in parallel across multiple machines, significantly improving processing speed and efficiency compared to traditional single-machine processing. They also provide tools for querying and analyzing data in data lakes.
Reference: https://azure.microsoft.com/en-ca/solutions/data-lake
A. Traditional relational database management systems (RDBMS) are not commonly used for processing and querying data stored in data lakes. Data lakes typically store unstructured or semi-structured data at a large scale, which is not well-suited for traditional RDBMS systems designed for structured data.
B. Data warehousing tools optimized for SQL queries are not typically used for processing and querying data stored in data lakes. Data lakes are designed to store raw, unstructured data, while data warehousing tools are optimized for structured data and may not be the best fit for querying data lakes.
C. Distributed processing frameworks like Spark or Hadoop are commonly used for processing and querying data stored in data lakes. These frameworks are designed to handle large volumes of data in a distributed and parallel manner, making them well-suited for the scale and complexity of data lakes.
D. Data visualization tools are not typically used for processing and querying data stored in data lakes. While these tools are important for creating reports and dashboards to visualize data, they are not the primary technologies used for processing and querying raw data stored in data lakes.
Discussion
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