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?
A.
Use Analytics Hub to control data access, and provide third party companies with access to the dataset.
B.
Use Cloud Scheduler to export the data on a regular basis to Cloud Storage, and provide third-party companies with access to the bucket.
C.
Create a separate dataset in BigQuery that contains the relevant data to share, and provide third-party companies with access to the new dataset.
D.
Create a Dataflow job that reads the data in frequent time intervals, and writes it to the relevant BigQuery dataset or Cloud Storage bucket for third-party companies to use.
I feel the answer really should be Create an authorized view on the BigQuery table to control data access, and provide third-party companies with access to that view.
A is the answer.
https://cloud.google.com/bigquery/docs/analytics-hub-introduction
nalytics Hub is a data exchange platform that enables you to share data and insights at scale across organizational boundaries with a robust security and privacy framework.
As an Analytics Hub publisher, you can monetize data by sharing it with your partner network or within your own organization in real time. Listings let you share data without replicating the shared data. You can build a catalog of analytics-ready data sources with granular permissions that let you deliver data to the right audiences. You can also manage subscriptions to your listings.
Option A: This option is correct because Analytics Hub is a managed service that provides a centralized repository for data assets. You can use Analytics Hub to share data with other Google Cloud Platform services, as well as with third-party companies
You are preparing for exam:
Creating a view and share with 3rd party is best and cheapest.
Then create a separate dataset to share it cost less than using paid service for data access i.e analytics hub where you create data access policies
you choose, its just making me craazy
One main reason you should use analytics hub, when you want control over 3 party activites and you want to monetize ( to make money ) by sharing BQ dataset.
Shared datasets are collections of tables and views in BigQuery defined by a data publisher and make up the unit of cross-project / cross-organizational sharing. Data subscribers get an opaque, read-only, linked dataset inside their project and VPC perimeter that they can combine with their own datasets and connect to solutions from Google Cloud or our partners. For example, a retailer might create a single exchange to share demand forecasts to the 1,000’s of vendors in their supply chain–having joined historical sales data with weather, web clickstream, and Google Trends data in their own BigQuery project, then sharing real-time outputs via Analytics Hub. The publisher can add metadata, track subscribers, and see aggregated usage metrics.
A
Multiple choose listed wrongly
Correct one
A.
Create an authorized view on the BigQuery table to control data access, and provide third-party companies with access to that view.
B.
Use Cloud Scheduler to export the data on a regular basis to Cloud Storage, and provide third-party companies with access to the bucket.
c.
Create a separate dataset in BigQuery that contains the relevant data to share, and provide third-party companies with access to the new dataset.
D.
Create a Cloud Dataflow job that reads the data in frequent time intervals, and writes it to the relevant BigQuery dataset or Cloud Storage bucket for third-party companies to use.
no option is correct
this is correct answer -Create an authorised view on the BigQuery table to control data access, and provide third-party companies with access to that view.
Answer A.
As an Analytics Hub user, you can perform the following tasks:
As an Analytics Hub publisher, you can monetize data by sharing it with your partner network or within your own organization in real time. Listings let you share data without replicating the shared data. You can build a catalog of analytics-ready data sources with granular permissions that let you deliver data to the right audiences.
As an Analytics Hub subscriber, you can discover the data that you are looking for, combine shared data with your existing data, and leverage the built-in features of BigQuery. When you subscribe to a listing, a linked dataset is created in your project.
As an Analytics Hub viewer, you can browse through the datasets that you have access to in Analytics Hub and request the publisher to access the shared data.
As an Analytics Hub administrator, you can create data exchanges that enable data sharing, and then give permissions to data publishers and subscribers to access these data exchanges.
https://cloud.google.com/bigquery/docs/analytics-hub-introduction
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