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

Section	Weight	Objectives
Topic 1: Analyzing Queries	15%	- Query Analysis 1. Monitoring Query Execution 2. Performance Tuning 3. Reading Query Plans
Topic 2: Understanding of Databricks Data Intelligence Platform	11%	- Platform Components 1. Unity Catalog 2. Lakeflow Jobs 3. Databricks SQL 4. Delta Lake 5. Mosaic AI - Catalog and Governance 1. Managed and External Tables 2. Data Lineage 3. Views and Certified Tables 4. Catalogs and Schemas
Topic 3: Managing Data	8%	- Data Management 1. Cleaning Data with SQL 2. Handling Missing and Invalid Data 3. Discovering Data Assets 4. Tagging and Lineage
Topic 4: Importing Data	5%	- Data Import 1. Creating Tables from Imported Data 2. Uploading Files 3. Loading CSV and JSON Data
Topic 5: Creating Dashboards and Visualizations	16%	- Visualization 1. Charts and Graphs 2. Dashboards 3. Sharing and Publishing 4. Alerts and Filters
Topic 6: Executing Queries Using Databricks SQL and SQL Warehouses	20%	- SQL Querying 1. SQL Warehouses 2. Writing SQL Queries 3. Filtering and Aggregation 4. Joins and Subqueries 5. Query Optimization
Topic 7: Securing Data	8%	- Security and Access Control 1. Data Access Policies 2. Permissions and Roles 3. Unity Catalog Security
Topic 8: Developing AI/BI Genie Spaces	12%	- AI and BI Features 1. AI/BI Genie 2. Natural Language Queries 3. Workspace Configuration
Topic 9: Data Modeling with Databricks SQL	5%	- Modeling Concepts 1. Data Organization 2. Fact and Dimension Tables 3. Views and Relationships

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Databricks Certified Data Analyst Associate Exam Sample Questions (Q53-Q58):

NEW QUESTION # 53
Which of the following statements describes descriptive statistics?

A. A branch of statistics that uses summary statistics to quantitatively describe and summarize data.
B. A branch of statistics that uses summary statistics to categorically describe and summarize data.
C. A branch of statistics that uses quantitative variables that must take on a finite or countably infinite set of values.
D. A branch of statistics that uses a variety of data analysis techniques to infer properties of an underlying distribution of probability.
E. A branch of statistics that uses quantitative variables that must take on an uncountable set of values.

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. Reference: Databricks - Descriptive Statistics, Databricks - Data Analysis with Databricks SQL

NEW QUESTION # 54
What does Partner Connect do when connecting Power Bl and Tableau?

A. Downloads a configuration file for connection by Power Bl or Tableau to a SQL Warehouse (formerly known as a SQL Endpoint).
B. Creates a Personal Access Token for authentication into Databricks SQL and emails it to you.
C. Creates a Personal Access Token. downloads and installs an ODBC driver, and downloads a configuration file for connection by Power Bl or Tableau to a SQL Warehouse (formerly known as a SQL Endpoint).
D. Downloads and installs an ODBC driver.

Answer: C

Explanation:
When connecting Power BI and Tableau through Databricks Partner Connect, the system automates several steps to streamline the integration process:
Personal Access Token Creation: Partner Connect generates a Databricks personal access token, which is essential for authenticating and establishing a secure connection between Databricks and the BI tools.
ODBC Driver Installation: The appropriate ODBC driver is downloaded and installed. This driver facilitates communication between the BI tools and Databricks, ensuring compatibility and optimal performance.
Configuration File Download: A configuration file tailored for the selected BI tool (Power BI or Tableau) is provided. This file contains the necessary connection details, simplifying the setup process within the BI tool.
By automating these steps, Partner Connect ensures a seamless and efficient integration, reducing manual configuration efforts and potential errors.

NEW QUESTION # 55
A data team has been given a series of projects by a consultant that need to be implemented in the Databricks Lakehouse Platform.
Which of the following projects should be completed in Databricks SQL?

A. Automating complex notebook-based workflows with multiple tasks
B. Segmenting customers into like groups using a clustering algorithm
C. Combining two data sources into a single, comprehensive dataset
D. Testing the quality of data as it is imported from a source
E. Tracking usage of feature variables for machine learning projects

Answer: C

Explanation:
Databricks SQL is a service that allows users to query data in the lakehouse using SQL and create visualizations and dashboards1. One of the common use cases for Databricks SQL is to combine data from different sources and formats into a single, comprehensive dataset that can be used for further analysis or reporting2. For example, a data analyst can use Databricks SQL to join data from a CSV file and a Parquet file, or from a Delta table and a JDBC table, and create a new table or view that contains the combined data3.
This can help simplify the data management and governance, as well as improve the data quality and consistency. References:
* Databricks SQL overview
* Databricks SQL use cases
* Joining data sources

NEW QUESTION # 56
A data analyst at an e-commerce company needs to process daily sales data. The data consists of approximately 50,000 records stored in a single CSV file, totaling about 20 MB. The analyst needs to perform aggregations and generate a summary report.
Which approach could the data analyst use in this situation?

A. Implement Apache Spark with a distributed cluster to process the data in parallel.
B. Set up a Hadoop ecosystem with HDFS and MapReduce for distributed processing.
C. Use a local Python script with the pandas library to read and analyze the CSV file.
D. Deploy a real-time streaming solution using Spark Streaming to process incoming data.

Answer: C

Explanation:
Option B is correct. A 20 MB CSV file with about 50,000 records is small enough for a local pandas workflow. A real-time streaming solution, a distributed Spark cluster, or Hadoop MapReduce would add unnecessary complexity for a small single-file batch analysis. Databricks documentation explains that pandas is available in Databricks Runtime and can be used for data analysis, while pandas API on Spark is useful when pandas-style workloads need to scale beyond smaller datasets. Databricks also notes that pandas does not scale out to big data, which is exactly why Spark or pandas API on Spark is used for larger workloads, not for a small 20 MB file.

NEW QUESTION # 57
A data analyst has produced a visualization. A stakeholder has viewed the visualization and is complaining that the visualization is difficult to interpret. After looking at the visualization, the analyst determines that the scale of the y-axis must be changed.
Where are the controls for changing the scale of the y-axis in Databricks SQL?

A. Dashboard Editor # Axes # Y Axis
B. Query Editor # Y Axis
C. Settings # User Settings # Scaling
D. Visualization Editor # Y Axis

Answer: D

Explanation:
The correct answer is C because axis settings are configured in the visualization editor, specifically under the Y-axis settings. The Query Editor is for writing SQL, not configuring chart axes. User Settings do not control individual chart scales. Dashboard editing may contain visualizations, but the specific control is in the visualization editor's Y Axis configuration.
Official documentation extract used: Databricks chart options state that to configure formatting for the X axis or Y axis, click the corresponding axis tab, and the Y-axis supports scale and range controls.

NEW QUESTION # 58
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