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

SectionObjectives
Topic 1: Data Visualization and Dashboards- Creating dashboards in Databricks SQL
  • 1. Visualizing query results
    • 2. Dashboard configuration and sharing
      Topic 2: Data Governance and Security- Access control and permissions
      • 1. Unity Catalog basics
        • 2. Row-level and column-level security concepts
          Topic 3: Data Management in Lakehouse- Delta Lake fundamentals
          • 1. ACID transactions and versioning
            • 2. Table optimization concepts
              - Data ingestion and preparation
              • 1. Batch and streaming ingestion concepts
                Topic 4: Databricks SQL and SQL Analytics- Data transformation and analysis
                • 1. Common table expressions (CTEs)
                  • 2. Window functions
                    - Querying data using SQL in Databricks
                    • 1. Joins and aggregations
                      • 2. SELECT statements and filtering data

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                        Databricks Certified Data Analyst Associate Exam Sample Questions (Q39-Q44):

                        NEW QUESTION # 39
                        Which of the following benefits of using Databricks SQL is provided by Data Explorer?

                        Answer: A

                        Explanation:
                        Data Explorer is a user interface that allows you to discover and manage data, schemas, tables, models, and permissions in Databricks SQL. You can use Data Explorer to view schema details, preview sample data, and see table and model details and properties. Administrators can view and change owners, and admins and data object owners can grant and revoke permissions1. References: Discover and manage data using Data Explorer


                        NEW QUESTION # 40
                        Which data lakehouse feature results in improved data quality over a traditional data lake?

                        Answer: D

                        Explanation:
                        Option D is correct. ACID-compliant transactions improve reliability and data quality because writes are consistent and atomic rather than leaving partially written or corrupted states. Open formats and SQL access are important lakehouse capabilities, but the feature most directly tied to improved data quality over a traditional data lake is ACID transactions. Official Databricks extract: Delta Lake extends Parquet with a transaction log for "ACID transactions," and Databricks states that Delta Lake adds ACID transactions and schema evolution for reliable, high-quality data.


                        NEW QUESTION # 41
                        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: 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 # 42
                        What describes the variance of a set of values?

                        Answer: B

                        Explanation:
                        Variance is a statistical measure that quantifies the dispersion or spread of a set of values around their mean (central value). It is calculated by taking the average of the squared differences between each value and the mean of the dataset. A higher variance indicates that the data points are more spread out from the mean, while a lower variance suggests that they are closer to the mean. This measure is fundamental in statistics to understand the degree of variability within a dataset.WikipediaWikipedia+1Investopedia+1 Reference: Variance - Wikipedia


                        NEW QUESTION # 43
                        How can a data analyst determine if query results were pulled from the cache?

                        Answer: A

                        Explanation:
                        Databricks SQL uses a query cache to store the results of queries that have been executed previously. This improves the performance and efficiency of repeated queries. To determine if a query result was pulled from the cache, you can go to the Query History tab in the Databricks SQL UI and click on the text of the query. A slideout will appear on the right side of the screen, showing the query details, including the cache status. If the result came from the cache, the cache status will show "Cached". If the result did not come from the cache, the cache status will show "Not cached". You can also see the cache hit ratio, which is the percentage of queries that were served from the cache. Reference: The answer can be verified from Databricks SQL documentation which provides information on how to use the query cache and how to check the cache status. Reference link: Databricks SQL - Query Cache


                        NEW QUESTION # 44
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