Databricks-DE-Pro Data Sharing and Federation Practice Question
A data engineer wants to share a Delta table with an external partner who does not have a Databricks account. The partner needs to access the data using Python. Which method should the engineer recommend to the partner for accessing the shared data?
⚠ Common exam trap
The trap here is assuming that the partner needs Databricks-specific tools like the SQL Connector, when the open Delta Sharing protocol provides a dedicated Python library for non-Databricks users.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Install the delta-sharing Python library and use the provided credential file to read the shared table.
For recipients without a Databricks account, the delta-sharing Python library is the standard way to access shared data. It uses the credential file to authenticate and allows reading the shared table into Python. This method is secure, supports live data, and does not require Databricks infrastructure on the recipient side. Other methods either require Databricks access or are not part of the Delta Sharing protocol.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Mount the shared table as an external table in their local Spark cluster using the Delta Sharing connector.
Why it's wrong here
While the Delta Sharing connector for Apache Spark allows reading shared data in Spark, it still requires the delta-sharing library and credential file. However, the option as stated implies mounting as an external table, which is not a standard feature of Delta Sharing. The typical approach is to use the connector to read the data, not to mount it. Additionally, the partner may not have a Spark cluster. This option is less direct and potentially misleading.
- ✗
Use the Databricks SQL Connector for Python with the partner's Databricks personal access token.
Why it's wrong here
The Databricks SQL Connector for Python is designed to connect to Databricks SQL warehouses and requires a Databricks account and personal access token. Since the partner does not have a Databricks account, this method is not feasible. The partner would need to be a Databricks user, which contradicts the scenario. Therefore, this option is incorrect for an external partner without Databricks access.
- ✓
Install the delta-sharing Python library and use the provided credential file to read the shared table.
Why this is correct
The delta-sharing Python library is specifically designed for recipients to access Delta Shares without needing a Databricks account. The partner can install the library via pip, use the credential file provided by the data engineer, and read the shared table as a pandas DataFrame or Apache Spark DataFrame. This method is secure, supports the Delta Sharing protocol, and is the recommended approach for non-Databricks recipients.
- ✗
Download the shared table as a Parquet file from the Databricks workspace and load it into their Python environment.
Why it's wrong here
Downloading the table as a Parquet file would require the partner to have access to the Databricks workspace, which they do not. Delta Sharing does not provide a direct download of the entire table as a single file; it provides access via the protocol. This method would also be a static snapshot and not reflect updates. It bypasses the secure sharing mechanism and is not a supported method for external recipients.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DE-Pro practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DE-Pro exam.