Most Recent Databricks-Certified-Data-Analyst-Associate Exam Dumps

Prepare for the Databricks Certified Data Analyst Associate Exam exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Databricks-Certified-Data-Analyst-Associate exam and achieve success.

The questions for Databricks-Certified-Data-Analyst-Associate were last updated on May 1, 2025.

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Question No. 1

Which of the following approaches can be used to connect Databricks to Fivetran for data ingestion?

AUse Workflows to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with

BUse Delta Live Tables to establish a cluster for Fivetran to interact with

CUse Partner Connect's automated workflow to establish a cluster for Fivetran to interact with

DUse Partner Connect's automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with

EUse Workflows to establish a cluster for Fivetran to interact with
Partner Connect is a feature that allows you to easily connect your Databricks workspace to Fivetran and other ingestion partners using an automated workflow. You can select a SQL warehouse or a cluster as the destination for your data replication, and the connection details are sent to Fivetran. You can then choose from over 200 data sources that Fivetran supports and start ingesting data into Delta Lake.Reference:Connect to Fivetran using Partner Connect,Use Databricks with Fivetran

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Correct Answer: C

Question No. 2

A data analyst needs to share a Databricks SQL dashboard with stakeholders that are not permitted to have accounts in the Databricks deployment. The stakeholders need to be notified every time the dashboard is refreshed.

Which approach can the data analyst use to accomplish this task with minimal effort/

ABy granting the stakeholders' email addresses permissions to the dashboard

BBy adding the stakeholders' email addresses to the refresh schedule subscribers list

CBy granting the stakeholders' email addresses to the SQL Warehouse (formerly known as endpoint) subscribers list

DBy downloading the dashboard as a PDF and emailing it to the stakeholders each time it is refreshed
To share a Databricks SQL dashboard with stakeholders who do not have accounts in the Databricks deployment and ensure they are notified upon each refresh, the data analyst can add the stakeholders' email addresses to the dashboard's refresh schedule subscribers list. This approach allows the stakeholders to receive email notifications containing the latest dashboard updates without requiring them to have direct access to the Databricks workspace. This method is efficient and minimizes effort, as it automates the notification process and ensures stakeholders remain informed of the most recent data insights.

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Correct Answer: B

Question No. 3

A data analyst is working with gold-layer tables to complete an ad-hoc project. A stakeholder has provided the analyst with an additional dataset that can be used to augment the gold-layer tables already in use.

Which of the following terms is used to describe this data augmentation?

AData testing

BAd-hoc improvements

CLast-mile

DLast-mile ETL

EData enhancement
Data enhancement is the process of adding or enriching data with additional information to improve its quality, accuracy, and usefulness. Data enhancement can be used to augment existing data sources with new data sources, such as external datasets, synthetic data, or machine learning models. Data enhancement can help data analysts to gain deeper insights, discover new patterns, and solve complex problems.Data enhancement is one of the applications of generative AI, which can leverage machine learning to generate synthetic data for better models or safer data sharing1.
In the context of the question, the data analyst is working with gold-layer tables, which are curated business-level tables that are typically organized in consumption-ready project-specific databases234.The gold-layer tables are the final layer of data transformations and data quality rules in the medallion lakehouse architecture, which is a data design pattern used to logically organize data in a lakehouse2. The stakeholder has provided the analyst with an additional dataset that can be used to augment the gold-layer tables already in use. This means that the analyst can use the additional dataset to enhance the existing gold-layer tables with more information, such as new features, attributes, or metrics. This data augmentation can help the analyst to complete the ad-hoc project more effectively and efficiently.

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Correct Answer: E

What is the medallion lakehouse architecture? - Databricks

Data Warehousing Modeling Techniques and Their Implementation on the Databricks Lakehouse Platform | Databricks Blog

What is the medallion lakehouse architecture? - Azure Databricks

What is a Medallion Architecture? - Databricks

Synthetic Data for Better Machine Learning | Databricks Blog

Question No. 4

Which of the following benefits of using Databricks SQL is provided by Data Explorer?

AIt can be used to run UPDATE queries to update any tables in a database.

BIt can be used to view metadata and data, as well as view/change permissions.

CIt can be used to produce dashboards that allow data exploration.

DIt can be used to make visualizations that can be shared with stakeholders.

EIt can be used to connect to third party Bl cools.
Data Explorer is a user interface that allows you to discover and manage data, schemas, tables, models, and permissions in Databricks SQL. You can use Data Explorer to view schema details, preview sample data, and see table and model details and properties.Administrators can view and change owners, and admins and data object owners can grant and revoke permissions1.Reference:Discover and manage data using Data Explorer

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Correct Answer: B

Question No. 5

A data engineering team has created a Structured Streaming pipeline that processes data in micro-batches and populates gold-level tables. The microbatches are triggered every minute.

A data analyst has created a dashboard based on this gold-level dat

a. The project stakeholders want to see the results in the dashboard updated within one minute or less of new data becoming available within the gold-level tables.

Which of the following cautions should the data analyst share prior to setting up the dashboard to complete this task?

AThe required compute resources could be costly

BThe gold-level tables are not appropriately clean for business reporting

CThe streaming data is not an appropriate data source for a dashboard

DThe streaming cluster is not fault tolerant

EThe dashboard cannot be refreshed that quickly
A Structured Streaming pipeline that processes data in micro-batches and populates gold-level tables every minute requires a high level of compute resources to handle the frequent data ingestion, processing, and writing. This could result in a significant cost for the organization, especially if the data volume and velocity are large. Therefore, the data analyst should share this caution with the project stakeholders before setting up the dashboard and evaluate the trade-offs between the desired refresh rate and the available budget. The other options are not valid cautions because:
B . The gold-level tables are assumed to be appropriately clean for business reporting, as they are the final output of the data engineering pipeline. If the data quality is not satisfactory, the issue should be addressed at the source or silver level, not at the gold level.
C . The streaming data is an appropriate data source for a dashboard, as it can provide near real-time insights and analytics for the business users. Structured Streaming supports various sources and sinks for streaming data, including Delta Lake, which can enable both batch and streaming queries on the same data.
D . The streaming cluster is fault tolerant, as Structured Streaming provides end-to-end exactly-once fault-tolerance guarantees through checkpointing and write-ahead logs. If a query fails, it can be restarted from the last checkpoint and resume processing.
E . The dashboard can be refreshed within one minute or less of new data becoming available in the gold-level tables, as Structured Streaming can trigger micro-batches as fast as possible (every few seconds) and update the results incrementally. However, this may not be necessary or optimal for the business use case, as it could cause frequent changes in the dashboard and consume more resources.Reference:Streaming on Databricks,Monitoring Structured Streaming queries on Databricks,A look at the new Structured Streaming UI in Apache Spark 3.0,Run your first Structured Streaming workload

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Correct Answer: A

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