INTERACTIVE DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE QUESTIONS - DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE NEW BRAINDUMPS FREE

Interactive Databricks-Certified-Data-Engineer-Associate Questions - Databricks-Certified-Data-Engineer-Associate New Braindumps Free

Interactive Databricks-Certified-Data-Engineer-Associate Questions - Databricks-Certified-Data-Engineer-Associate New Braindumps Free

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q27-Q32):

NEW QUESTION # 27
Which of the following data workloads will utilize a Gold table as its source?

  • A. A job that cleans data by removing malformatted records
  • B. A job that ingests raw data from a streaming source into the Lakehouse
  • C. A job that queries aggregated data designed to feed into a dashboard
  • D. A job that aggregates uncleaned data to create standard summary statistics
  • E. A job that enriches data by parsing its timestamps into a human-readable format

Answer: C


NEW QUESTION # 28
In which of the following file formats is data from Delta Lake tables primarily stored?

  • A. Delta
  • B. A proprietary, optimized format specific to Databricks
  • C. Parquet
  • D. JSON
  • E. CSV

Answer: C

Explanation:
Delta Lake is an open source project that provides ACID transactions, time travel, and other features on top of Apache Parquet, a columnar file format that is widely used for big data analytics. Delta Lake uses versioned Parquet files to store your data in your cloud storage, along with JSON files as transaction logs and checkpoint files to track the changes and ensure data integrity. Delta Lake is compatible with any Apache Hive compatible file format, such as CSV, JSON, or AVRO, but it primarily stores data as Parquet files for better performance and compression. Reference: How to Create Delta Lake tables, 5 reasons to choose Delta Lake format (on Databricks), Parquet vs Delta format in Azure Data Lake Gen 2 store, What is Delta Lake? - Azure Databricks, Lakehouse and Delta tables - Microsoft Fabric


NEW QUESTION # 29
Which of the following describes the relationship between Bronze tables and raw data?

  • A. Bronze tables contain aggregates while raw data is unaggregated.
  • B. Bronze tables contain raw data with a schema applied.
  • C. Bronze tables contain less data than raw data files.
  • D. Bronze tables contain a less refined view of data than raw data.
  • E. Bronze tables contain more truthful data than raw data.

Answer: B

Explanation:
Explanation
The Bronze layer is where we land all the data from external source systems. The table structures in this layer correspond to the source system table structures "as-is," along with any additional metadata columns that capture the load date/time, process ID, etc. The focus in this layer is quick Change Data Capture and the ability to provide an historical archive of source (cold storage), data lineage, auditability, reprocessing if needed without rereading the data from the source system.https://www.databricks.com/glossary/medallion-architecture#:~:text=Bronze%20layer%20%28raw%20d


NEW QUESTION # 30
A data engineer is maintaining a data pipeline. Upon data ingestion, the data engineer notices that the source data is starting to have a lower level of quality. The data engineer would like to automate the process of monitoring the quality level.
Which of the following tools can the data engineer use to solve this problem?

  • A. Delta Live Tables
  • B. Auto Loader
  • C. Data Explorer
  • D. Unity Catalog
  • E. Delta Lake

Answer: A

Explanation:
Delta Live Tables is a tool that enables data engineers to build and manage reliable data pipelines with minimal code. One of the features of Delta Live Tables is data quality monitoring, which allows data engineers to define quality expectations for their data and automatically check them at every step of the pipeline. Data quality monitoring can help detect and resolve data quality issues, such as missing values, duplicates, outliers, or schema changes. Data quality monitoring can also generate alerts and reports on the quality level of the data, and enable data engineers to troubleshoot and fix problems quickly. Reference: Delta Live Tables Overview, Data Quality Monitoring


NEW QUESTION # 31
Which of the following tools is used by Auto Loader process data incrementally?

  • A. Spark Structured Streaming
  • B. Data Explorer
  • C. Unity Catalog
  • D. Databricks SQL
  • E. Checkpointing

Answer: A


NEW QUESTION # 32
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