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Google Exam Professional Data Engineer Topic 3 Question 85 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 85
Topic #: 3
[All Professional Data Engineer Questions]

You operate a database that stores stock trades and an application that retrieves average stock price for a given company over an adjustable window of time. The data is stored in Cloud Bigtable where the datetime of the stock trade is the beginning of the row key. Your application has thousands of concurrent users, and you notice that performance is starting to degrade as more stocks are added. What should you do to improve the performance of your application?

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Suggested Answer: A

Data Fusion's advantages:

Visual interface: Offers a user-friendly interface for designing data pipelines without extensive coding, making it accessible to a wider range of users.

Built-in transformations: Includes a wide range of pre-built transformations to handle common data quality issues, such as:

Data type conversions

Data cleansing (e.g., removing invalid characters, correcting formatting)

Data validation (e.g., checking for missing values, enforcing constraints)

Data enrichment (e.g., adding derived fields, joining with other datasets)

Custom transformations: Allows for custom transformations using SQL or Java code for more complex cleaning tasks.

Scalability: Can handle large datasets efficiently, making it suitable for processing CSV files with potential data quality issues.

Integration with BigQuery: Integrates seamlessly with BigQuery, allowing for direct loading of transformed data.


Contribute your Thoughts:

Jaime
13 hours ago
I disagree, I believe option D) using Cloud Dataflow to write summary of each day's stock trades to an Avro file is the best approach.
upvoted 0 times
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Tiera
5 days ago
I think we should go with option A) Change the row key syntax to begin with the stock symbol.
upvoted 0 times
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