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Databricks Databricks-Certified-Data-Analyst-Associate Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Executing Queries Using Databricks SQL and SQL Warehouses	20%	- SQL Querying 1. Writing SQL Queries 2. Filtering and Aggregation 3. Query Optimization 4. SQL Warehouses 5. Joins and Subqueries
Topic 2: Creating Dashboards and Visualizations	16%	- Visualization 1. Alerts and Filters 2. Dashboards 3. Charts and Graphs 4. Sharing and Publishing
Topic 3: Developing AI/BI Genie Spaces	12%	- AI and BI Features 1. AI/BI Genie 2. Natural Language Queries 3. Workspace Configuration
Topic 4: Securing Data	8%	- Security and Access Control 1. Data Access Policies 2. Permissions and Roles 3. Unity Catalog Security
Topic 5: Importing Data	5%	- Data Import 1. Loading CSV and JSON Data 2. Uploading Files 3. Creating Tables from Imported Data
Topic 6: Analyzing Queries	15%	- Query Analysis 1. Reading Query Plans 2. Performance Tuning 3. Monitoring Query Execution
Topic 7: Managing Data	8%	- Data Management 1. Handling Missing and Invalid Data 2. Discovering Data Assets 3. Cleaning Data with SQL 4. Tagging and Lineage
Topic 8: Data Modeling with Databricks SQL	5%	- Modeling Concepts 1. Fact and Dimension Tables 2. Data Organization 3. Views and Relationships
Topic 9: Understanding of Databricks Data Intelligence Platform	11%	- Catalog and Governance 1. Views and Certified Tables 2. Managed and External Tables 3. Catalogs and Schemas 4. Data Lineage - Platform Components 1. Lakeflow Jobs 2. Mosaic AI 3. Unity Catalog 4. Databricks SQL 5. Delta Lake

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Databricks Certified Data Analyst Associate Exam Sample Questions (Q90-Q95):

NEW QUESTION # 90
Data professionals with varying responsibilities use the Databricks Lakehouse Platform Which role in the Databricks Lakehouse Platform use Databricks SQL as their primary service?

A. Platform architect
B. Data scientist
C. Data engineer
D. Business analyst

Answer: D

Explanation:
In the Databricks Lakehouse Platform, business analysts primarily utilize Databricks SQL as their main service. Databricks SQL provides an environment tailored for executing SQL queries, creating visualizations, and developing dashboards, which aligns with the typical responsibilities of business analysts who focus on interpreting data to inform business decisions. While data scientists and data engineers also interact with the Databricks platform, their primary tools and services differ; data scientists often engage with machine learning frameworks and notebooks, whereas data engineers focus on data pipelines and ETL processes.
Platform architects are involved in designing and overseeing the infrastructure and architecture of the platform. Therefore, among the roles listed, business analysts are the primary users of Databricks SQL.
Reference: The scope of the lakehouse platform

NEW QUESTION # 91
Which of the following approaches can be used to connect Databricks to Fivetran for data ingestion?

A. Use Workflows to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
B. Use Partner Connect ' s automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
C. Use Partner Connect ' s automated workflow to establish a cluster for Fivetran to interact with
D. Use Workflows to establish a cluster for Fivetran to interact with
E. Use Delta Live Tables to establish a cluster for Fivetran to interact with

Answer: C

Explanation:
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. References: Connect to Fivetran using Partner Connect, Use Databricks with Fivetran

NEW QUESTION # 92
Which of the following data workloads will utilize a Gold table as its source?

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

Answer: A

Explanation:
Option D is correct. Gold tables are refined, business-ready datasets used for analytics, dashboards, reporting, and other downstream consumption. A workload that queries aggregated data designed to feed a dashboard is therefore using Gold-layer data. Raw streaming ingestion belongs to Bronze, cleaning malformed records belongs to Silver, and aggregating uncleaned data is not the recommended Gold pattern. Official Databricks extract: the Gold layer "consists of aggregated data tailored for analytics and reporting" and is optimized for
"queries and dashboards."

NEW QUESTION # 93
A data analyst created and is the owner of the managed table my_ table. They now want to change ownership of the table to a single other user using Data Explorer.
Which of the following approaches can the analyst use to complete the task?

A. Edit the Owner field in the table page by selecting All Users
B. Edit the Owner field in the table page by selecting the new owner's account
C. Edit the Owner field in the table page by removing their own account
D. Edit the Owner field in the table page by selecting the Admins group
E. Edit the Owner field in the table page by removing all access

Answer: B

Explanation:
The Owner field in the table page shows the current owner of the table and allows the owner to change it to another user or group. To change the ownership of the table, the owner can click on the Owner field and select the new owner from the drop-down list. This will transfer the ownership of the table to the selected user or group and remove the previous owner from the list of table access control entries1. The other options are incorrect because:
A . Removing the owner's account from the Owner field will not change the ownership of the table, but will make the table ownerless2.
B . Selecting All Users from the Owner field will not change the ownership of the table, but will grant all users access to the table3.
D . Selecting the Admins group from the Owner field will not change the ownership of the table, but will grant the Admins group access to the table3.
E . Removing all access from the Owner field will not change the ownership of the table, but will revoke all access to the table4. Reference:
1: Change table ownership
2: Ownerless tables
3: Table access control
4: Revoke access to a table

NEW QUESTION # 94
Which of the following is a benefit of Databricks SQL using ANSI SQL as its standard SQL dialect?

A. It is more compatible with Spark's interpreters
B. It is easy to migrate existing SQL queries to Databricks SQL
C. It allows for the use of Photon's computation optimizations
D. It has increased customization capabilities
E. It is more performant than other SQL dialects

Answer: B

Explanation:
Databricks SQL uses ANSI SQL as its standard SQL dialect, which means it follows the SQL specifications defined by the American National Standards Institute (ANSI). This makes it easier to migrate existing SQL queries from other data warehouses or platforms that also use ANSI SQL or a similar dialect, such as PostgreSQL, Oracle, or Teradata. By using ANSI SQL, Databricks SQL avoids surprises in behavior or unfamiliar syntax that may arise from using a non-standard SQL dialect, such as Spark SQL or Hive SQL12. Moreover, Databricks SQL also adds compatibility features to support common SQL constructs that are widely used in other data warehouses, such as QUALIFY, FILTER, and user-defined functions2. Reference: ANSI compliance in Databricks Runtime, Evolution of the SQL language at Databricks: ANSI standard by default and easier migrations from data warehouses

NEW QUESTION # 95
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