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A data engineer wants to ingest a large collection of image files (JPEG and PNG) from cloud object storage into Unity Catalog-managed table for further analysis and visualization. Which two configurations and practices are recommended to incrementally ingest these images into the table?

A data engineer is configuring Delta Sharing for a Databricks-to-Databricks scenario to optimize read
performance. The recipient needs to perform time travel queries and streaming reads on shared sales
data. Which configuration will provide the optimal performance while enabling these capabilities?

A data organization has adopted Delta Sharing to securely distribute curated datasets from a Unity Catalog-enabled workspace. The data engineering team is sharing large Delta tables with an internal
partner via Databricks-to-Databricks and aggregated reports with an external client

via Open Sharing. While testing new sharing workflows, the data engineering team encounters challenges related to access control, data update visibility, and shareable object types.

What is a limitation of the Delta Sharing protocol or implementation when used with Databricks-to- Databricks or Open Sharing?

A data engineer is creating a daily reporting Job. There are two reporting notebooks one for weekdays and
the other for weekends. An "If/else condition" task is configured as
"{{job.start_time.is_weekday}} == true" to route the job to either weekday or weekend
notebook tasks. The same job would be used in multiple time zones.
Which action should a senior data engineer take upon reviewing the job to merge or reject the pull
request?

How are the operational aspects of Lakeflow Spark Declarative Pipelines from Spark Structured Streaming different?

A workspace admin has created a new catalog called ‘finance_data’ and wants to delegate permission management to a finance team lead without giving them full admin rights. Which privilege should be granted to the finance team lead?

A data engineer is configuring a Lakeflow Spark Declarative Pipelines to process CDC data from a source.
The source events sometimes arrive out of order, and multiple updates may occur with the same update_timestamp but with different update_sequence_id.

What should the data engineer do to ensure events are sequenced correctly?

A streaming video analytics team ingests billions of events daily into a Unity Catalog-managed Delta table video_events. Analysts run ad-hoc point-lookup queries on columns like user_id, campaign_id, and region. The team manually runs OPTIMIZE video_events Z-ORDER user_id, campaign_id,
region, but still sees poor performance on recent data, and dislikes the operational overhead. The team
wants a hands-off way to keep hot columns co-located as query patterns evolve.

Which Delta capability should the team leverage on video_events?

A data engineer is designing a data pipeline in Databricks that needs to process records from a Kafka
stream where late-arriving data common. Which approach should the data engineer use?

A data engineering team is configuring access controls in Databricks Unity Catalog. They grant the
SELECT privilege on the sales catalog to the analyst_group, expecting that members of this group will automatically have SELECT access to all current and future schemas, tables, and views within the sales
catalog.
What describes the privilege inheritance behavior in Unity Catalog?

QUESTION 308
An organization processes customer data from web and mobile applications. Data includes names, emails phone numbers, and location history. Data arrives both as Batch files from an SFTP drop (daily) and Streaming JSON events from Kafka (real-time).

To comply with internal data privacy policies, the following requirements must be met:
* Personally identifiable information (PII) like email, phone_number, and ip_address must be masked or anonymized before storage
* Both batch and streaming pipelines must apply consistent PII handling
* Masking logic must be auditable and reproducible
* The masked data must still be usable for downstream analytics
How should the data engineer design a compliant data pipeline on Databricks that supports both batch and streaming modes, applies data masking to PII, and maintains traceability of transformations for audits?

Which method can be used to determine the total wall-clock time it took to execute a query?

A data architect is designing a Databricks solution to efficiently process data for different business requirements.
In which scenario should a data engineer use a materialized view compared to a streaming table?

A query is taking too long to run. After investigating the Spark UI, the data engineer discovered a
significant amount of disk spill. The type of compute instance the data engineer used only provides a core- to-memory ratio of 1:2.

What are the two steps the data engineer should take to minimize spillage? (Choose two.)

A data engineering team has a time-consuming data ingestion job. It has three data sources, and each
data ingestion notebook takes about one hour to load new data. The job had been working fine, loading
data every midnight. However, one day they received an alert message stating the job had failed. By

investigating the cause, they figured out that the failed notebook code was updated, and a new required configuration was introduced to parameterize a hardcoded value without notice. Now, the team has to fix the issue as quickly as possible to load the latest data from the failing data source.

Which action should the team take in this scenario?

A data engineer is masking the provided data column containing the email address. The goal is to have an
output of the same length for all rows, while keeping different outputs for different values.
Which SQL function should be used to achieve this?

A company wants to implement Lakehouse Federation across multiple data sources, but is worried about data consistency and ensuring all teams access the same authoritative version of their data.

Which statement is applicable for Lakehouse Federations to maintain data consistency?

A data engineer needs to implement column masking for a sensitive column in a Unity Catalog-managed table. The masking logic must dynamically check if users belong to specific groups defined in a separate table (group_access) that maps groups to allowed departments. Which approach should the engineer use to efficiently enforce this requirement?

A data engineer wants to automate job monitoring and recovery in Databricks using the Jobs API. They
need to list all jobs, identify a failed job, and rerun it. Which sequence of API actions should the data engineer perform?

A data engineering team is setting up deployment automation. To deploy workspace assets remotely using the Databricks CLI command, they must configure it with proper authentication. Which authentication approach will provide the highest level of security?

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