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You need ads data to serve Al models and historical data tor analytics longtail and outlier data points need to be identified You want to cleanse the data n near-reel time before running it through Al models What should you do?
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?
You are migrating your on-premises data warehouse to BigQuery. One of the upstream data sources resides on a MySQL database that runs in your on-premises data center with no public IP addresses. You want to ensure that the data ingestion into BigQuery is done securely and does not go through the public internet. What should you do?
To securely ingest data from an on-premises MySQL database into BigQuery without routing through the public internet, using Datastream with Private connectivity over Cloud Interconnect is the best approach. Here's why:
Datastream for Data Replication:
Datastream provides a managed service for data replication from various sources, including on-premises databases, to Google Cloud services like BigQuery.
Cloud Interconnect:
Cloud Interconnect establishes a private connection between your on-premises data center and Google Cloud, ensuring that data transfer occurs over a secure, private network rather than the public internet.
Private Connectivity:
Using Private connectivity with Datastream leverages the established Cloud Interconnect to securely connect your on-premises MySQL database with Google Cloud. This method ensures that the data does not traverse the public internet.
Encryption:
Using Server-only encryption ensures that data is encrypted in transit between Datastream and BigQuery, adding an extra layer of security.
Steps to Implement:
Set Up Cloud Interconnect:
Establish a Cloud Interconnect between your on-premises data center and Google Cloud to create a private connection.
Configure Datastream:
Set up Datastream to use Private connectivity as the connection method and allocate an IP address range within your VPC network.
Use Server-only encryption to ensure secure data transfer.
Create Connection Profile:
Create a connection profile in Datastream to define the connection parameters, including the use of Cloud Interconnect and Private connectivity.
Datastream Documentation
Cloud Interconnect Documentation
Setting Up Private Connectivity in Datastream
You have several Spark jobs that run on a Cloud Dataproc cluster on a schedule. Some of the jobs run in sequence, and some of the jobs run concurrently. You need to automate this process. What should you do?
Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow. Numerous data logs are being are being generated during this step, and the team wants to analyze them. Due to the dynamic nature of the campaign, the data is growing exponentially every hour.
The data scientists have written the following code to read the data for a new key features in the logs.
BigQueryIO.Read
.named(''ReadLogData'')
.from(''clouddataflow-readonly:samples.log_data'')
You want to improve the performance of this data read. What should you do?
