Title: Get Certified on the First Attempt with Databricks Databricks-Certified-Professi [Print This Page] Author: rickada186 Time: 14 hour before Title: Get Certified on the First Attempt with Databricks Databricks-Certified-Professi When you are studying for the Databricks-Certified-Professional-Data-Engineer exam, maybe you are busy to go to work, for your family and so on. Time is precious for everyone to do the efficient job. If you want to get good Databricks-Certified-Professional-Data-Engineer prep guide, it must be spending less time to pass it. We are choosing the key point and the latest information to finish our Databricks-Certified-Professional-Data-Engineer Guide Torrent. It only takes you 20 hours to 30 hours to do the practice. After your effective practice, you can master the examination point from the Databricks-Certified-Professional-Data-Engineer exam torrent. Then, you will have enough confidence to pass the Databricks-Certified-Professional-Data-Engineer exam.
The Databricks Databricks-Certified-Professional-Data-Engineer Exam is designed to test the candidate's ability to work with Databricks in a real-world setting. Candidates are required to demonstrate their ability to design and implement data pipelines that are scalable, efficient, and reliable. They must also be able to troubleshoot issues that arise during the data engineering process and optimize performance to ensure that pipelines run smoothly.
Databricks Certified Professional Data Engineer certification is a valuable credential for data engineers who work with the Databricks platform. It validates their skills and expertise and demonstrates to employers that they have the knowledge and experience needed to work with Databricks effectively. By passing the exam and earning the certification, data engineers can enhance their career prospects and gain a competitive advantage in the job market.
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Databricks Certified Professional Data Engineer exam measures a candidate's ability to design, build, and manage data pipelines using Databricks. It covers a wide range of topics, including data ingestion, transformation, storage, and analysis. Candidates must demonstrate their proficiency in using Databricks tools and techniques to solve real-world data engineering problems. Databricks Certified Professional Data Engineer Exam certification exam is ideal for data engineers who want to validate their skills and expertise in using Databricks to build and manage data pipelines. Databricks Certified Professional Data Engineer Exam Sample Questions (Q193-Q198):NEW QUESTION # 193
In order to use Unity catalog features, which of the following steps needs to be taken on man-aged/external tables in the Databricks workspace?
A. Upgrade to DBR version 15.0
B. Migrate/upgrade objects in workspace managed/external tables/view to unity catalog
C. Copy data from workspace to unity catalog
D. Enable unity catalog feature in workspace settings
E. Upgrade workspace to Unity catalog
Answer: B
Explanation:
Explanation
Upgrade tables and views to Unity Catalog - Azure Databricks | Microsoft Docs Managed table: Upgrade a managed to Unity Catalog External table: Upgrade an external table to Unity Catalog
NEW QUESTION # 194
The business reporting team requires that data for their dashboards be updated every hour. The total processing time for the pipeline that extracts, transforms, and loads the data for their pipeline runs in 10 minutes. Assuming normal operating conditions, which configuration will meet their service-level agreement requirements with the lowest cost?
A. Configure a job that executes every time new data lands in a given directory.
B. Schedule a job to execute the pipeline once an hour on a new job cluster.
C. Schedule a Structured Streaming job with a trigger interval of 60 minutes.
D. Schedule a job to execute the pipeline once an hour on a dedicated interactive cluster.
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Exact extract: "Job clusters are created for a job run and terminate when the job completes." Exact extract: "All-purpose (interactive) clusters are intended for interactive development and collaboration."
NEW QUESTION # 195
Which of the following describes how Databricks Repos can help facilitate CI/CD workflows on the
Databricks Lakehouse Platform?
A. Databricks Repos can be used to design, develop, and trigger Git automation pipelines
B. Databricks Repos can merge changes from a secondary Git branch into a main Git branch
C. Databricks Repos can facilitate the pull request, review, and approval process before merging branches
D. Databricks Repos can commit or push code changes to trigger a CI/CD process
E. Databricks Repos can store the single-source-of-truth Git repository
Answer: D
NEW QUESTION # 196
A Delta Lake table with Change Data Feed (CDF) enabled in the Lakehouse named customer_churn_params is used in churn prediction by the machine learning team. The table contains information about customers derived from a number of upstream sources. Currently, the data engineering team populates this table nightly by overwriting the table with the current valid values derived from upstream data sources. The churn prediction model used by the ML team is fairly stable in production. The team is only interested in making predictions on records that have changed in the past 24 hours. Which approach would simplify the identification of these changed records?
A. Apply the churn model to all rows in the customer_churn_params table, but implement logic to perform an upsert into the predictions table that ignores rows where predictions have not changed.
B. Replace the current overwrite logic with a MERGE statement to modify only those records that have changed; write logic to make predictions on the changed records identified by the Change Data Feed.
C. Convert the batch job to a Structured Streaming job using the complete output mode; configure a Structured Streaming job to read from the customer_churn_params table and incrementally predict against the churn model.
D. Modify the overwrite logic to include a field populated by calling current_timestamp() as data are being written; use this field to identify records written on a particular date.
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
* Exact extract: "Change data feed (CDF) provides row-level change information for Delta tables."
* Exact extract: "Use table_changes to query the set of rows that were inserted, updated, or deleted between two versions (or timestamps)." References: Delta Lake Change Data Feed; Delta Lake MERGE INTO.
NEW QUESTION # 197
A data architect is designing a data model that works for both video-based machine learning work-loads and
highly audited batch ETL/ELT workloads.
Which of the following describes how using a data lakehouse can help the data architect meet the needs of
both workloads?
A. A data lakehouse requires very little data modeling
B. A data lakehouse provides autoscaling for compute clusters
C. A data lakehouse fully exists in the cloud
D. A data lakehouse combines compute and storage for simple governance
E. A data lakehouse stores unstructured data and is ACID-compliant
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