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

Section	Weight	Objectives
Analyzing Queries	15%	- Liquid clustering and indexing - Performance optimization - Execution plans and analysis - Query history and auditing
Managing Data	8%	- Dataset versioning and management - Discovering and registering datasets - Unity Catalog usage - Data cleaning and preparation
Securing Data	8%	- Secure storage and compliance - Data governance policies - Access control and permissions
Executing Queries using Databricks SQL and Databricks SQL Warehouses	20%	- Warehouse configuration and performance - Creating and managing views - Aggregations and grouping - ANSI SQL syntax and functions - Joining and combining datasets
Understanding of Databricks Data Intelligence Platform	11%	- Core architecture and components - Lakehouse platform fundamentals - Workspace navigation and interface
Importing Data	5%	- Delta Sharing - UI-based data ingestion - API and Auto Loader - S3 and cloud storage integration - Databricks Marketplace
Creating Dashboards and Visualizations in Databricks	16%	- Visualization types and best practices - Scheduling and sharing dashboards - Filtering and interactivity - Dashboard creation and layout
Data Modeling with Databricks SQL	5%	- Performance-oriented modeling - Delta table structure - Schema design principles
Developing, Sharing, and Maintaining AI/BI Genie Spaces	12%	- Genie space setup and configuration - Access control and sharing - Natural language query setup - Maintenance and improvement

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Databricks Certified Data Analyst Associate Exam Sample Questions (Q53-Q58):

NEW QUESTION # 53
A data analyst has a managed table table_name in database database_name. They would now like to remove the table from the database and all of the data files associated with the table. The rest of the tables in the database must continue to exist.
Which of the following commands can the analyst use to complete the task without producing an error?

A. DROP TABLE database_name.table_name;
B. DROP TABLE table_name FROM database_name;
C. DELETE TABLE table_name FROM database_name;
D. DROP DATABASE database_name;
E. DELETE TABLE database_name.table_name;

Answer: A

Explanation:
The DROP TABLE command removes a table from the metastore and deletes the associated data files. The syntax for this command is DROP TABLE [IF EXISTS] [database_name.] table_name;. The optional IF EXISTS clause prevents an error if the table does not exist. The optional database_name. prefix specifies the database where the table resides. If not specified, the current database is used. Therefore, the correct command to remove the table table_name from the database database_name and all of the data files associated with it is DROP TABLE database_name.table_name;. The other commands are either invalid syntax or would produce undesired results. References: Databricks - DROP TABLE

NEW QUESTION # 54
A data analyst has recently joined a new team that uses Databricks SQL, but the analyst has never used Databricks before. The analyst wants to know where in Databricks SQL they can write and execute SQL queries.
On which of the following pages can the analyst write and execute SQL queries?

A. SQL Editor page
B. Dashboards page
C. Data page
D. Alerts page
E. Queries page

Answer: A

Explanation:
The SQL Editor page is where the analyst can write and execute SQL queries in Databricks SQL. The SQL Editor page has a query pane where the analyst can type or paste SQL statements, and a results pane where the analyst can view the query results in a table or a chart. The analyst can also browse data objects, edit multiple queries, execute a single query or multiple queries, terminate a query, save a query, download a query result, and more from the SQL Editor page. Reference: Create a query in SQL editor

NEW QUESTION # 55
Delta Lake stores table data as a series of data files, but it also stores a lot of other information.
Which of the following is stored alongside data files when using Delta Lake?

A. Owner account information
B. Table metadata
C. Table metadata, data summary visualizations, and owner account information
D. None of these
E. Data summary visualizations

Answer: B

Explanation:
Delta Lake stores table data as a series of data files in a specified location, but it also stores table metadata in a transaction log. The table metadata includes the schema, partitioning information, table properties, and other configuration details. The table metadata is stored alongside the data files and is updated atomically with every write operation. The table metadata can be accessed using the DESCRIBE DETAIL command or the DeltaTable class in Scala, Python, or Java. The table metadata can also be enriched with custom tags or user-defined commit messages using the TBLPROPERTIES or userMetadata options. Reference:
Enrich Delta Lake tables with custom metadata
Delta Lake Table metadata - Stack Overflow
Metadata - The Internals of Delta Lake

NEW QUESTION # 56
A data analyst has a managed table table_name in database database_name. They would now like to remove the table from the database and all of the data files associated with the table. The rest of the tables in the database must continue to exist.
Which of the following commands can the analyst use to complete the task without producing an error?

A. DROP TABLE database_name.table_name;
B. DROP TABLE table_name FROM database_name;
C. DELETE TABLE table_name FROM database_name;
D. DROP DATABASE database_name;
E. DELETE TABLE database_name.table_name;

Answer: A

NEW QUESTION # 57
A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

A. They can set up the dashboard's SQL endpoint to be serverless.
B. They can turn on the Auto Stop feature for the SQL endpoint.
C. They can reduce the cluster size of the SQL endpoint.
D. They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.
E. They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.

Answer: B

Explanation:
Option C is correct because Auto Stop is specifically designed to stop a SQL warehouse when it has been idle for a configured number of minutes. This minimizes total warehouse running time after the scheduled dashboard refresh completes. Reducing cluster size may reduce hourly cost but does not stop the warehouse.
Serverless can help with management, but the feature directly matching "only running when necessary" is Auto Stop. Official Databricks extract: "Auto Stop determines whether the warehouse stops if it's idle for the specified number of minutes." Databricks also notes that idle SQL warehouses continue to accumulate charges until stopped.

NEW QUESTION # 58
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