Google Cloud-Digital-Leader Dumps Questions Answers

Many organizations have separate development and production environments so they can build and test new features without disturbing production traffic. In Optimizely, you can create separate projects for each environment to help with governance.

With separate development and production projects, your organization can safely build and QA experiments and Personalization campaigns in a development environment before deploying to production. This approach allows multiple stakeholders in your organization to act as gatekeepers for running new experiments in production.

Reference link- https://support.optimizely.com/hc/en-us/articles/4410284353805-Set-up-projects-for-development-and-production-environments

Explanation

=> Cloud Pub/Sub- Cloud Pub/Sub is the best to be the end-point for ingesting large amounts of data. It will grow as required, can stream data to downstream systems, and can also work with intermittently available backends.

=> Cloud Dataflow- supports streaming data and therefore is an appropriate option for processing the data that is ingested.

=> BigQuery- BigQuery also supports streaming data and its possible to do real time ana-lytics on it.

=> DataStudio- DataStudio and Looker are for visualization. They don't have any in-built analysis.

=> Cloud Functions- Cloud Functions is a useful serverless endpoint. However, Pub/Sub is better in this case because it can also retain messages for a set period if it was not possi-ble to deliver it first time.

=>Cloud Dataproc- Cloud Dataproc is used for Hadoop/Spark workloads and won't be a good fit here.

Explanation

By storing their application data in the cloud the organization will be able to gather and analyze user behavior data in real-time. This will enable them to dynamically adjust their application for different user needs.