Professional-Data-Engineer Exam Question 166
The _________ for Cloud Bigtable makes it possible to use Cloud Bigtable in a Cloud Dataflow pipeline.
Professional-Data-Engineer Exam Question 167
You use a dataset in BigQuery for analysis. You want to provide third-party companies with access to the same dataset. You need to keep the costs of data sharing low and ensure that the data is current. Which solution should you choose?
Professional-Data-Engineer Exam Question 168
You want to analyze hundreds of thousands of social media posts daily at the lowest cost and with the fewest steps.
You have the following requirements:
- You will batch-load the posts once per day and run them through the
Cloud Natural Language API.
- You will extract topics and sentiment from the posts.
- You must store the raw posts for archiving and reprocessing.
- You will create dashboards to be shared with people both inside and
outside your organization.
You need to store both the data extracted from the API to perform analysis as well as the raw social media posts for historical archiving. What should you do?
You have the following requirements:
- You will batch-load the posts once per day and run them through the
Cloud Natural Language API.
- You will extract topics and sentiment from the posts.
- You must store the raw posts for archiving and reprocessing.
- You will create dashboards to be shared with people both inside and
outside your organization.
You need to store both the data extracted from the API to perform analysis as well as the raw social media posts for historical archiving. What should you do?
Professional-Data-Engineer Exam Question 169
You created an analytics environment on Google Cloud so that your data scientist team can explore data without impacting the on-premises Apache Hadoop solution. The data in the on- premises Hadoop Distributed File System (HDFS) cluster is in Optimized Row Columnar (ORC) formatted files with multiple columns of Hive partitioning. The data scientist team needs to be able to explore the data in a similar way as they used the on-premises HDFS cluster with SQL on the Hive query engine. You need to choose the most cost-effective storage and processing solution.
What should you do?
What should you do?
Professional-Data-Engineer Exam Question 170
You work for a global shipping company. You want to train a model on 40 TB of data to predict which ships in each geographic region are likely to cause delivery delays on any given day. The model will be based on multiple attributes collected from multiple sources. Telemetry data, including location in GeoJSON format, will be pulled from each ship and loaded every hour. You want to have a dashboard that shows how many and which ships are likely to cause delays within a region. You want to use a storage solution that has native functionality for prediction and geospatial processing. Which storage solution should you use?
