Updated Databricks-Certified-Data-Analyst-Associate CBT & Latest Databricks-Certified-Data-Analyst-Associate Test Report

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

Topic	Details
Topic 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.
Topic 2	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.
Topic 3	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.
Topic 4	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.
Topic 5	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.

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Databricks Certified Data Analyst Associate Exam Sample Questions (Q13-Q18):

NEW QUESTION # 13
What is a benefit of using Databricks SQL for business intelligence (Bl) analytics projects instead of using third-party Bl tools?

A. Computations, data, and analytical tools on the same platform
B. Advanced dashboarding capabilities
C. Simultaneous multi-user support
D. Automated alerting systems

Answer: A

Explanation:
Databricks SQL offers a unified platform where computations, data storage, and analytical tools coexist seamlessly. This integration allows business intelligence (BI) analytics projects to be executed more efficiently, as users can perform data processing and analysis without the need to transfer data between disparate systems. By consolidating these components, Databricks SQL streamlines workflows, reduces latency, and enhances data governance. While third-party BI tools may offer advanced dashboarding capabilities, simultaneous multi-user support, and automated alerting systems, they often require integration with separate data processing platforms, which can introduce complexity and potential inefficiencies.

NEW QUESTION # 14
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?

A. A quantitative variable that never stops changing
B. A quantitative variable that can take on an uncountable set of values
C. A categorical variable in which the number of categories continues to increase over time
D. A quantitative variable Chat can take on a finite or countably infinite set of values

Answer: B

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 # 15
Which of the following benefits of using Databricks SQL is provided by Data Explorer?

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

Answer: D

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. Reference: Discover and manage data using Data Explorer

NEW QUESTION # 16
Which of the following layers of the medallion architecture is most commonly used by data analysts?

A. Bronze
B. All of these layers are used equally by data analysts
C. None of these layers are used by data analysts
D. Gold
E. Silver

Answer: D

Explanation:
The gold layer of the medallion architecture contains data that is highly refined and aggregated, and powers analytics, machine learning, and production applications. Data analysts typically use the gold layer to access data that has been transformed into knowledge, rather than just information. The gold layer represents the final stage of data quality and optimization in the lakehouse. Reference: What is the medallion lakehouse architecture?

NEW QUESTION # 17
Which of the following statements about a refresh schedule is incorrect?

A. A refresh schedule is not the same as an alert.
B. A query can be refreshed anywhere from 1 minute lo 2 weeks
C. A query being refreshed on a schedule does not use a SQL Warehouse (formerly known as SQL Endpoint).
D. You must have workspace administrator privileges to configure a refresh schedule
E. Refresh schedules can be configured in the Query Editor.

Answer: D

Explanation:
This statement is incorrect. In Databricks SQL, any user with sufficient permissions on the query or dashboard can configure a refresh schedule-workspace administrator privileges are not required.
Here is the breakdown of the correct information:
A . True - Queries can be scheduled to refresh at intervals ranging from 1 minute to 2 weeks.
B . True - You can configure refresh schedules in the Query Editor.
C . False statement - A query being refreshed does use a SQL Warehouse. However, the option in question says it does not use a warehouse, which would be incorrect in a different context. Since this is a trickier one, we know that scheduled queries do require a SQL Warehouse to run.
D . True - Refresh schedules are different from alerts; alerts are triggered based on specific conditions being met in query results.
E . False (and thus the correct answer to this question) - You do not need to be a workspace admin to set a refresh schedule. You only need the correct permissions on the object.

NEW QUESTION # 18
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UPDATED DATABRICKS-CERTIFIED-DATA-ANALYST-ASSOCIATE CBT & LATEST DATABRICKS-CERTIFIED-DATA-ANALYST-ASSOCIATE TEST REPORT

Updated Databricks-Certified-Data-Analyst-Associate CBT & Latest Databricks-Certified-Data-Analyst-Associate Test Report