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| Certification Vendor: | Databricks |
|---|---|
| Exam Name: | Databricks Certified Data Analyst Associate Exam |
| Exam Number: | Databricks-Certified-Data-Analyst-Associate |
| Exam Format: | Multiple Choice, Multiple Select |
| Available Languages: | English |
| Certificate Validity Period: | 2 years |
| Passing Score: | 70% |
| Related Certifications: | Databricks Certified Machine Learning Associate Databricks Certified Data Engineer Associate |
| Exam Price: | $200 USD |
| Real Exam Qty: | 45–60 |
| Exam Duration: | 90 minutes |
| Recommended Training: | Databricks Academy - Data Analyst Learning Path Databricks SQL Training Courses |
| Exam Registration: | Databricks Certification Portal Kryterion Webassessor Registration |
| Sample Questions: | Databricks Databricks-Certified-Data-Analyst-Associate Sample Questions |
| Exam Way: | Online proctored exam via remote monitoring (Kryterion Webassessor platform) |
| Pre Condition: | No formal prerequisites required, but familiarity with SQL and basic data analysis concepts is recommended. |
| Official Syllabus URL: | https://www.databricks.com/learn/certification |
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NEW QUESTION # 68
Which of the following describes the relationship between Gold tables and Silver tables?
Answer: B
Explanation:
Option A is correct. Silver tables are cleaned, validated, and enriched versions of data, often still retaining detailed records. Gold tables are typically business-ready, analytics-focused, and more likely to contain aggregations, dimensional models, and reporting-ready metrics. Official Databricks extract: Silver is associated with "Data cleaning and validation," while Gold is associated with "Dimensional modeling and aggregation." Databricks also states that Gold data is often highly aggregated and tailored for analytics and reporting.
NEW QUESTION # 69
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?
Answer: D
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 # 70
A data scientist has asked a data analyst to create histograms for every continuous variable in a data set. The data analyst needs to identify which columns are continuous in the data set.
What describes a continuous variable?
Answer: D
Explanation:
A continuous variable is a type of quantitative variable that can assume an infinite number of values within a given range. This means that between any two possible values, there can be an infinite number of other values. For example, variables such as height, weight, and temperature are continuous because they can be measured to any level of precision, and there are no gaps between possible values. This is in contrast to discrete variables, which can only take on specific, distinct values (e.g., the number of children in a family).
Understanding the nature of continuous variables is crucial for data analysts, especially when selecting appropriate statistical methods and visualizations, such as histograms, to accurately represent and analyze the data.
NEW QUESTION # 71
Which of the following is an advantage of using a Delta Lake-based data lakehouse over common data lake solutions?
Answer: E
Explanation:
A Delta Lake-based data lakehouse is a data platform architecture that combines the scalability and flexibility of a data lake with the reliability and performance of a data warehouse. One of the key advantages of using a Delta Lake-based data lakehouse over common data lake solutions is that it supports ACID transactions, which ensure data integrity and consistency. ACID transactions enable concurrent reads and writes, schema enforcement and evolution, data versioning and rollback, and data quality checks. These features are not available in traditional data lakes, which rely on file-based storage systems that do not support transactions. References:
* Delta Lake: Lakehouse, warehouse, advantages | Definition
* Synapse - Data Lake vs. Delta Lake vs. Data Lakehouse
* Data Lake vs. Delta Lake - A Detailed Comparison
* Building a Data Lakehouse with Delta Lake Architecture: A Comprehensive Guide
NEW QUESTION # 72
A data analyst is troubleshooting a query in Databricks SQL that fails when processing large datasets and complex join operations. Logs indicate that the job consistently aborts due to resource constraint errors on the cluster.
Which Query Profile metric should the analyst use to identify the operator that is causing resource overuse?
Answer: B
Explanation:
The correct answer is C because the issue is a resource constraint failure, and the analyst needs to identify which operator is consuming excessive memory. In Query Profile, Memory peak shows memory usage at the operator level and helps identify the operator causing resource overuse. Time spent helps identify slow operators, shuffle read size helps analyze data movement, and bytes spilled to disk indicates spill behavior, but the most direct metric for resource overuse due to memory pressure is memory peak.
Official documentation extract used: Databricks Query Profile graph view shows metrics such as "Time spent, Memory peak, and Rows."
NEW QUESTION # 73
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