Google Certified Professional – Data Engineer Free Questions

1. Your company built a TensorFlow neutral-network model with a large number of neurons and layers. The model fits well for the training data.

However, when tested against new data, it performs poorly.

What method can you employ to address this?

2. You are building a model to make clothing recommendations. You know a user’s fashion preference is likely to change over time, so you build a data pipeline to stream new data back to the model as it becomes available.

How should you use this data to train the model?

3. You designed a database for patient records as a pilot project to cover a few hundred patients in three clinics. Your design used a single database table to represent all patients and their visits, and you used self-joins to generate reports. The server resource utilization was at 50%. Since then, the scope of the project has expanded. The database must now store 100 times more patient records. You can no longer run the reports, because they either take too long or they encounter errors with insufficient compute resources.

How should you adjust the database design?

4. You create an important report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. You notice that visualizations are not showing data that is less than 1 hour old.

What should you do?

5. An external customer provides you with a daily dump of data from their database. The data flows into Google Cloud Storage GCS as comma-separated values (CSV) files. You want to analyze this data in Google BigQuery, but the data could have rows that are formatted incorrectly or corrupted.

How should you build this pipeline?

6. Your weather app queries a database every 15 minutes to get the current temperature. The frontend is powered by Google App Engine and server millions of users.

How should you design the frontend to respond to a database failure?

7. You are creating a model to predict housing prices. Due to budget constraints, you must run it on a single resource-constrained virtual machine.

Which learning algorithm should you use?

8. You are building new real-time data warehouse for your company and will use Google BigQuery streaming inserts. There is no guarantee that data will only be sent in once but you do have a unique ID for each row of data and an event timestamp. You want to ensure that duplicates are not included while interactively querying data.

Which query type should you use?

9. Your company is in a highly regulated industry. One of your requirements is to ensure individual users have access only to the minimum amount of information required to do their jobs. You want to enforce this requirement with Google BigQuery.

Which three approaches can you take? (Choose three.)

10. Your company handles data processing for a number of different clients. Each client prefers to use their own suite of analytics tools, with some allowing direct query access via Google BigQuery. You need to secure the data so that clients cannot see each other’s data. You want to ensure appropriate access to the data.

Which three steps should you take? (Choose three.)