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To complete the sentence, select the appropriate option in the answer area.

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Disadvantages of non-relational databases include:
Data Consistency — non-relational databases do not perform ACID transactions.

Note: Relational databases are optimized for writes. They are optimized for consistency and availability. Advantages of relational databases include simplicity, ease of data retrieval, data integrity, and flexibility.

Incorrect Answers:
Use a relational database when data that you work with is structured, and the structure is not subject to frequent changes.
Use Cloud storage (no relational database) for geographically distributed writes.


Reference:

https://towardsdatascience.com/choosing-the-right-database-c45cd3a28f77



Which component of Azure Data Factory enables you to define a sequence of activities including for each iterators?

  1. control flow
  2. linked services
  3. datasets
  4. the integration runtime

Answer(s): A



Which clause should you use in a select statement to combine rows in one table with rows in another table?

  1. JOIN
  2. VALUES
  3. set
  4. KEY

Answer(s): A


Reference:

https://www.tutorialspoint.com/sql/sql-using-joins.htm



Which three actions are used when performing diagnostic analytics?


  1. • Identify data anomalies
    • Collect anomaly-related data
    • Discover relationships and trends that explain anomalies.

  2. • Identify data anomalies
    • Predict when anomalies are likely to recur
    • Use analytical tools such as decision trees and regression.

  3. • Apply serf-learning loops to draw inferences from anomalies.
    • Predict when anomalies are likely to recur
    • Use analytical tools such as decision trees and regression.

  4. • Identify data anomalies
    • Use machine learning to find patterns in large datasets.
    • Discover relationships and trends that explain anomalies.

Answer(s): A



Which three actions are used when performing diagnostic analytics?


  1. • Identify data anomalies
    • Collect anomaly-related data
    • Discover relationships and trends that explain anomalies.

  2. • Identify data anomalies
    • Predict when anomalies are likely to recur
    • Use analytical tools such as decision trees and regression.

  3. • Apply serf-learning loops to draw inferences from anomalies.
    • Predict when anomalies are likely to recur
    • Use analytical tools such as decision trees and regression.

  4. • Identify data anomalies
    • Use machine learning to find patterns in large datasets.
    • Discover relationships and trends that explain anomalies.

Answer(s): A




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