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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing Data | 8% | - Discovering and registering datasets - Dataset versioning and management - Unity Catalog usage - Data cleaning and preparation |
| Topic 2: Creating Dashboards and Visualizations in Databricks | 16% | - Visualization types and best practices - Scheduling and sharing dashboards - Dashboard creation and layout - Filtering and interactivity |
| Topic 3: Understanding of Databricks Data Intelligence Platform | 11% | - Core architecture and components - Workspace navigation and interface - Lakehouse platform fundamentals |
| Topic 4: Securing Data | 8% | - Data governance policies - Secure storage and compliance - Access control and permissions |
| Topic 5: Data Modeling with Databricks SQL | 5% | - Schema design principles - Delta table structure - Performance-oriented modeling |
| Topic 6: Analyzing Queries | 15% | - Liquid clustering and indexing - Query history and auditing - Performance optimization - Execution plans and analysis |
| Topic 7: Importing Data | 5% | - Databricks Marketplace - UI-based data ingestion - Delta Sharing - S3 and cloud storage integration - API and Auto Loader |
| Topic 8: Developing, Sharing, and Maintaining AI/BI Genie Spaces | 12% | - Natural language query setup - Maintenance and improvement - Genie space setup and configuration - Access control and sharing |
| Topic 9: Executing Queries using Databricks SQL and Databricks SQL Warehouses | 20% | - Creating and managing views - Aggregations and grouping - Warehouse configuration and performance - Joining and combining datasets - ANSI SQL syntax and functions |
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NEW QUESTION # 38
A data analyst has created a Query in Databricks SQL, and now they want to create two data visualizations from that Query and add both of those data visualizations to the same Databricks SQL Dashboard.
Which of the following steps will they need to take when creating and adding both data visualizations to the Databricks SQL Dashboard?
Answer: D
Explanation:
A data analyst can create multiple visualizations from the same query in Databricks SQL by clicking the + button next to the Results tab and selecting Visualization. Each visualization can have a different type, name, and configuration. To add a visualization to a dashboard, the data analyst can click the vertical ellipsis button beneath the visualization, select + Add to Dashboard, and choose an existing or new dashboard. The data analyst can repeat this process for each visualization they want to add to the same dashboard. Reference: Visualization in Databricks SQL, Visualize queries and create a dashboard in Databricks SQL
NEW QUESTION # 39
Where in the Databricks SQL workspace can a data analyst configure a refresh schedule for a query when the query is not attached to a dashboard or alert?
Answer: D
Explanation:
In Databricks SQL, to configure a refresh schedule for a query that is not attached to a dashboard or alert, a data analyst should use the Query Editor. Within the Query Editor, there is an option to set up scheduled executions for queries. This feature enables the query to run at specified intervals, ensuring that the results are updated regularly. By scheduling queries in this manner, analysts can automate data refreshes and maintain up- to-date query results without manual intervention.
Reference: Schedule a query - Databricks Documentation
NEW QUESTION # 40
Where can an admin or data owner grant database, table, and view permissions to a group?
Answer: B
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 # 41
A data analyst has been asked to configure an alert for a query that returns the income in the accounts_receivable table for a date range. The date range is configurable using a Date query parameter.
The Alert does not work.
Which of the following describes why the Alert does not work?
Answer: C
Explanation:
According to the Databricks documentation1, queries that use query parameters cannot be used with Alerts. This is because Alerts do not support user input or dynamic values. Alerts leverage queries with parameters using the default value specified in the SQL editor for each parameter. Therefore, if the query uses a Date query parameter, the alert will always use the same date range as the default value, regardless of the actual date. This may cause the alert to not work as expected, or to not trigger at all. Reference:
Databricks SQL alerts: This is the official documentation for Databricks SQL alerts, where you can find information about how to create, configure, and monitor alerts, as well as the limitations and best practices for using alerts.
NEW QUESTION # 42
Which of the following statements describes descriptive statistics?
Answer: A
Explanation:
Descriptive statistics is a branch of statistics that uses summary statistics, such as mean, median, mode, standard deviation, range, frequency, or correlation, to quantitatively describe and summarize data.
Descriptive statistics can help data analysts understand the main features of a data set, such as its central tendency, variability, or distribution. Descriptive statistics can also help data analysts visualize data using charts, graphs, or tables. Descriptive statistics do not make any inferences or predictions about the data, unlike inferential statistics, which use data analysis techniques to infer properties of an underlying population or probability distribution from a sample of data. References: Databricks - Descriptive Statistics, Databricks - Data Analysis with Databricks SQL
NEW QUESTION # 43
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