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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Importing Data | 5% | - UI-based data ingestion - S3 and cloud storage integration - Delta Sharing - Databricks Marketplace - API and Auto Loader |
| Topic 2: Understanding of Databricks Data Intelligence Platform | 11% | - Lakehouse platform fundamentals - Workspace navigation and interface - Core architecture and components |
| Topic 3: Managing Data | 8% | - Dataset versioning and management - Unity Catalog usage - Discovering and registering datasets - Data cleaning and preparation |
| Topic 4: Creating Dashboards and Visualizations in Databricks | 16% | - Scheduling and sharing dashboards - Filtering and interactivity - Dashboard creation and layout - Visualization types and best practices |
| Topic 5: Data Modeling with Databricks SQL | 5% | - Schema design principles - Delta table structure - Performance-oriented modeling |
| Topic 6: Securing Data | 8% | - Data governance policies - Secure storage and compliance - Access control and permissions |
| Topic 7: Executing Queries using Databricks SQL and Databricks SQL Warehouses | 20% | - ANSI SQL syntax and functions - Warehouse configuration and performance - Creating and managing views - Aggregations and grouping - Joining and combining datasets |
| Topic 8: Analyzing Queries | 15% | - Query history and auditing - Execution plans and analysis - Liquid clustering and indexing - Performance optimization |
| Topic 9: Developing, Sharing, and Maintaining AI/BI Genie Spaces | 12% | - Maintenance and improvement - Natural language query setup - Access control and sharing - Genie space setup and configuration |
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NEW QUESTION # 68
A data analyst is working on a DataFrame named dates_df and needs to add a new column, date, derived from the timestamp field.
Which code fragment should be used to extract the date from a timestamp?
Answer: D
Explanation:
Option B is correct. The function to_date converts a timestamp or date-like expression to a date value, which matches the requirement to extract the date from the timestamp field. unix_timestamp converts to a Unix timestamp value, date_format formats a date or timestamp as a string, and from_unixtime converts Unix time into a timestamp/string representation. Official Databricks documentation states that to_date(expr [, fmt]) returns the expression cast to a date.
NEW QUESTION # 69
A data analyst has been asked to produce a visualization that shows the flow of users through a website.
Which of the following is used for visualizing this type of flow?
Answer: E
Explanation:
A Sankey diagram is a type of visualization that shows the flow of data between different nodes or categories.
It is often used to represent the movement of users through a website, as it can show the paths they take, the sources they come from, the pages they visit, and the outcomes they achieve. A Sankey diagram consists of links and nodes, where the links represent the volume or weight of the flow, and the nodes represent the stages or steps of the flow. The width of the links is proportional to the amount of flow, and the color of the links can indicate different attributes or segments of the flow. A Sankey diagram can help identify the most common or popular user journeys, the bottlenecks or drop-offs in the flow, and the opportunities for improvement or optimization. References: The answer can be verified from Databricks documentation which provides examples and instructions on how to create Sankey diagrams using Databricks SQL Analytics and Databricks Visualizations. Reference links: Databricks SQL Analytics - Sankey Diagram, Databricks Visualizations - Sankey Diagram
NEW QUESTION # 70
In which of the following situations should a data analyst use higher-order functions?
Answer: C
Explanation:
Higher-order functions are a simple extension to SQL to manipulate nested data such as arrays. A higher- order function takes an array, implements how the array is processed, and what the result of the computation will be. It delegates to a lambda function how to process each item in the array. This allows you to define functions that manipulate arrays in SQL, without having to unpack and repack them, use UDFs, or rely on limited built-in functions. Higher-order functions provide a performance benefit over user defined functions. References: Higher-order functions | Databricks on AWS, Working with Nested Data Using Higher Order Functions in SQL on Databricks | Databricks Blog, Higher-order functions - Azure Databricks | Microsoft Learn, Optimization recommendations on Databricks | Databricks on AWS
NEW QUESTION # 71
Where can an admin or data owner grant database, table, and view permissions to a group?
Answer: C
Explanation:
Option B is correct. In the older Databricks SQL UI terminology used by this question, permissions for databases, tables, and views are managed from the Data area. In the current Databricks UI, this is handled through Catalog Explorer, where an admin or data owner opens the object, goes to the Permissions tab, clicks Grant, selects users or groups, and grants the required privileges. Dashboards are for reporting, SQL Warehouses provide compute, and Settings is not the object-level permission management area. Official Databricks documentation says privileges can be managed using SQL commands, CLI, Terraform, or Catalog Explorer, and the UI flow is: open the table details page, go to Permissions, click Grant, select users or groups, and assign privileges.
NEW QUESTION # 72
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?
Answer: C
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. Reference: Databricks - DROP TABLE
NEW QUESTION # 73
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