A data engineer has created a Delta Share and added several tables. Now they need to grant access to an external data science team. The team will use a Spark client to read the shared data. What should the engineer do to provide the team with the necessary access?

Add the data science team's IP addresses to the workspace firewall.

Create a new cluster and share its connection string with the team.

Create a recipient, generate a share credential, and send the credential to the data science team.

Provide the team with the workspace admin credentials.

A retail analytics company wants to share daily sales aggregates with a partner's Tableau dashboards. The partner needs to see the latest committed data as soon as it lands, without any manual refresh or data duplication. The partner's team is not using Databricks. Which approach best meets the requirement?

Create a Delta Share and have the partner connect via the open-source Delta Sharing connector for Tableau.

Set up a recurring job to email a CSV attachment of the aggregates to the partner.

Grant the partner direct SQL access to the Databricks SQL warehouse to run their own queries.

Export the sales aggregates to Parquet files daily and share the files via a shared cloud storage bucket.

In Delta Sharing architecture, what is the role of the 'recipient'?

The organization or user that receives access to the shared data

The protocol used to authenticate and authorize data access

The computing platform that hosts the Delta Sharing server

The organization that owns and manages the shared data

In Databricks, what is the first step to share a table using Delta Sharing?

Create a Delta Share and add tables to it

Enable Delta Sharing on the cluster

Create a recipient and generate credentials

Grant the recipient access to the underlying cloud storage

What is the primary purpose of Delta Sharing?

To migrate data from on-premises systems to the cloud

To enable secure, live data sharing from a Lakehouse to any computing platform

To transform data into a format optimized for machine learning

To replicate data to a central data warehouse for reporting

DatabricksCertified Data Engineer Professional

Domain 4Objective 3

Use Delta Share to Share Live Data from Lakehouse to Any Computing Platform. DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 3)

Part of the Data Sharing and Federation domain, which accounts for 5% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~3–4 in this domain), expect 1–1 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)

29questions here

6free pages

7concepts

5%of the exam

Questions 11–15

11application · medium
A data engineer has created a Delta Share and added several tables. Now they need to grant access to an external data science team. The team will use a Spark client to read the shared data. What should the engineer do to provide the team with the necessary access?
Select an answer first
12application · medium
A retail analytics company wants to share daily sales aggregates with a partner's Tableau dashboards. The partner needs to see the latest committed data as soon as it lands, without any manual refresh or data duplication. The partner's team is not using Databricks. Which approach best meets the requirement?
Select an answer first
13foundation · easy
In Delta Sharing architecture, what is the role of the 'recipient'?
Select an answer first
14foundation · easy
In Databricks, what is the first step to share a table using Delta Sharing?
Select an answer first
15foundation · easy
What is the primary purpose of Delta Sharing?
Select an answer first

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