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Databricks Databricks-Certified-Data-Analyst-Associate Prüfungsplan:

Thema	Einzelheiten
Thema 1	Data Management: The topic describes Delta Lake as a tool for managing data files, Delta Lake manages table metadata, benefits of Delta Lake within the Lakehouse, tables on Databricks, a table owner’s responsibilities, and the persistence of data. It also identifies management of a table, usage of Data Explorer by a table owner, and organization-specific considerations of PII data. Lastly, the topic it explains how the LOCATION keyword changes, usage of Data Explorer to secure data.
Thema 2	Databricks SQL: This topic discusses key and side audiences, users, Databricks SQL benefits, complementing a basic Databricks SQL query, schema browser, Databricks SQL dashboards, and the purpose of Databricks SQL endpoints warehouses. Furthermore, the delves into Serverless Databricks SQL endpoint warehouses, trade-off between cluster size and cost for Databricks SQL endpoints warehouses, and Partner Connect. Lastly it discusses small-file upload, connecting Databricks SQL to visualization tools, the medallion architecture, the gold layer, and the benefits of working with streaming data.
Thema 3	Data Visualization and Dashboarding: Sub-topics of this topic are about of describing how notifications are sent, how to configure and troubleshoot a basic alert, how to configure a refresh schedule, the pros and cons of sharing dashboards, how query parameters change the output, and how to change the colors of all of the visualizations. It also discusses customized data visualizations, visualization formatting, Query Based Dropdown List, and the method for sharing a dashboard.
Thema 4	Analytics applications: It describes key moments of statistical distributions, data enhancement, and the blending of data between two source applications. Moroever, the topic also explains last-mile ETL, a scenario in which data blending would be beneficial, key statistical measures, descriptive statistics, and discrete and continuous statistics.
Thema 5	SQL in the Lakehouse: It identifies a query that retrieves data from the database, the output of a SELECT query, a benefit of having ANSI SQL, access, and clean silver-level data. It also compares and contrasts MERGE INTO, INSERT TABLE, and COPY INTO. Lastly, this topic focuses on creating and applying UDFs in common scaling scenarios.

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Databricks Certified Data Analyst Associate Exam Databricks-Certified-Data-Analyst-Associate Prüfungsfragen mit Lösungen (Q53-Q58):

53. Frage
Which of the following benefits of using Databricks SQL is provided by Data Explorer?

A. It can be used to view metadata and data, as well as view/change permissions.
B. It can be used to produce dashboards that allow data exploration.
C. It can be used to make visualizations that can be shared with stakeholders.
D. It can be used to connect to third party Bl cools.
E. It can be used to run UPDATE queries to update any tables in a database.

Antwort: A

Begründung:
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

54. Frage
After running DESCRIBE EXTENDED accounts.customers;, the following was returned:

Now, a data analyst runs the following command:
DROP accounts.customers;
Which of the following describes the result of running this command?

A. All files with the .customers extension are deleted.
B. The accounts.customers table is removed from the metastore, but the underlying data files are untouched.
C. Running SELECT * FROM accounts.customers will return all rows in the table.
D. The accounts.customers table is removed from the metastore, and the underlying data files are deleted.
E. Running SELECT * FROM delta. `dbfs:/stakeholders/customers` results in an error.

Antwort: B

Begründung:
the accounts.customers table is an EXTERNAL table, which means that it is stored outside the default warehouse directory and is not managed by Databricks. Therefore, when you run the DROP command on this table, it only removes the metadata information from the metastore, but does not delete the actual data files from the file system. This means that you can still access the data using the location path (dbfs:/stakeholders
/customers) or create another table pointing to the same location. However, if you try to query the table using its name (accounts.customers), you will get an error because the table no longer exists in the metastore. References: DROP TABLE | Databricks on AWS, Best practices for dropping a managed Delta Lake table - Databricks

55. Frage
A data analyst has been asked to provide a list of options on how to share a dashboard with a client. It is a security requirement that the client does not gain access to any other information, resources, or artifacts in the database.
Which of the following approaches cannot be used to share the dashboard and meet the security requirement?

A. Take a screenshot of the dashboard and share it with the client.
B. Download the Dashboard as a PDF and share it with the client.
C. Set a refresh schedule for the dashboard and enter the client ' s email address in the " Subscribers " box.
D. Download a PNG file of the visualizations in the dashboard and share them with the client.
E. Generate a Personal Access Token that is good for 1 day and share it with the client.

Antwort: E

Begründung:
The approach that cannot be used to share the dashboard and meet the security requirement is D. Generating a Personal Access Token that is good for 1 day and sharing it with the client. This approach would give the client access to the Databricks workspace using the token owner's identity and permissions, which could expose other information, resources, or artifacts in the database1. The other approaches can be used to share the dashboard and meet the security requirement because:
* A. Downloading the Dashboard as a PDF and sharing it with the client would only provide a static snapshot of the dashboard without any interactive features or access to the underlying data2.
* B. Setting a refresh schedule for the dashboard and entering the client's email address in the
"Subscribers" box would send the client an email with the latest dashboard results as an attachment or a link to a secure web page3. The client would not be able to access the Databricks workspace or the dashboard itself.
* C. Taking a screenshot of the dashboard and sharing it with the client would also only provide a static snapshot of the dashboard without any interactive features or access to the underlying data4.
* E. Downloading a PNG file of the visualizations in the dashboard and sharing them with the client would also only provide a static snapshot of the visualizations without any interactive features or access to the underlying data5. References:
* 1: Personal access tokens
* 2: Download as PDF
* 3: Automatically refresh a dashboard
* 4: Take a screenshot
* 5: Download a PNG file

56. Frage
A data analyst is using Databricks Unity Catalog. The datasets are tagged by sensitivity, and confidential data is marked with the tag key confidential. The data analyst needs to quickly find all tables tagged as confidential to review their access permissions in the Databricks workspace search bar.
Which search key text should the data analyst use to find these tables?

A. tag:confidential
B. confidential:true
C. tag=confidential
D. search tag = ' confidential '

Antwort: A

Begründung:
The correct answer is C because the tag key is confidential, and Databricks workspace search uses the syntax tag: < tag_key > to search by tag key. Therefore, the correct search text is tag:confidential. Option A uses a Boolean-style syntax that is not the documented Databricks tag search syntax. Option B uses an equals sign, and Option D is not valid workspace search syntax.
Official documentation extract used: Databricks states that to search by tag key alone, use the syntax tag: < tag_key > .

57. Frage
What describes the variance of a set of values?

A. Variance is a measure of how far a set of values is spread out from the sets central value.
B. Variance is a measure of how far an observed value is from the variable's maximum or minimum value.
C. Variance is a measure of central tendency of a set of values.
D. Variance is a measure of how far a single observed value is from a set ot va IN

Antwort: A

Begründung:
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

58. Frage
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