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Databricks Certified Data Analyst Associate Exam Sample Questions (Q11-Q16):

NEW QUESTION # 11
What describes the variance of a set of values?

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

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

NEW QUESTION # 12
A data organization has a team of engineers developing data pipelines following the medallion architecture using Delta Live Tables. While the data analysis team working on a project is using gold-layer tables from these pipelines, they need to perform some additional processing of these tables prior to performing their analysis.
Which of the following terms is used to describe this type of work?

A. Data blending
B. Data testing
C. Last-mile
D. Last-mile ETL
E. Data enhancement

Answer: D

Explanation:
Last-mile ETL is the term used to describe the additional processing of data that is done by data analysts or data scientists after the data has been ingested, transformed, and stored in the lakehouse by data engineers. Last-mile ETL typically involves tasks such as data cleansing, data enrichment, data aggregation, data filtering, or data sampling that are specific to the analysis or machine learning use case. Last-mile ETL can be done using Databricks SQL, Databricks notebooks, or Databricks Machine Learning. Reference: Databricks - Last-mile ETL, Databricks - Data Analysis with Databricks SQL

NEW QUESTION # 13
Which of the following should data analysts consider when working with personally identifiable information (PII) data?

A. Legal requirements for the area in which the data was collected
B. Organization-specific best practices for Pll data
C. None of these considerations
D. Legal requirements for the area in which the analysis is being performed
E. All of these considerations

Answer: E

Explanation:
Data analysts should consider all of these factors when working with PII data, as they may affect the data security, privacy, compliance, and quality. PII data is any information that can be used to identify a specific individual, such as name, address, phone number, email, social security number, etc. PII data may be subject to different legal and ethical obligations depending on the context and location of the data collection and analysis. For example, some countries or regions may have stricter data protection laws than others, such as the General Data Protection Regulation (GDPR) in the European Union. Data analysts should also follow the organization-specific best practices for PII data, such as encryption, anonymization, masking, access control, auditing, etc. These best practices can help prevent data breaches, unauthorized access, misuse, or loss of PII data. Reference:
How to Use Databricks to Encrypt and Protect PII Data
Automating Sensitive Data (PII/PHI) Detection
Databricks Certified Data Analyst Associate

NEW QUESTION # 14
Which of the following approaches can be used to ingest data directly from cloud-based object storage?

A. Create an external table while specifying the DBFS storage path to PATH
B. Create an external table while specifying the object storage path to LOCATION
C. Create an external table while specifying the DBFS storage path to FROM
D. It is not possible to directly ingest data from cloud-based object storage
E. Create an external table while specifying the object storage path to FROM

Answer: B

Explanation:
External tables are tables that are defined in the Databricks metastore using the information stored in a cloud object storage location. External tables do not manage the data, but provide a schema and a table name to query the data. To create an external table, you can use the CREATE EXTERNAL TABLE statement and specify the object storage path to the LOCATION clause. For example, to create an external table named ext_table on a Parquet file stored in S3, you can use the following statement:
SQL
CREATE EXTERNAL TABLE ext_table (
col1 INT,
col2 STRING
)
STORED AS PARQUET
LOCATION 's3://bucket/path/file.parquet'
AI-generated code. Review and use carefully. More info on FAQ.

NEW QUESTION # 15
A data analyst has been asked to configure an alert for a query that returns the income in the accounts_receivable table for a date range. The date range is configurable using a Date query parameter.
The Alert does not work.
Which of the following describes why the Alert does not work?

A. Queries that return results based on dates cannot be used with Alerts.
B. Queries that use query parameters cannot be used with Alerts.
C. The wrong query parameter is being used. Alerts only work with drogdown list query parameters, not dates.
D. Alerts don't work with queries that access tables.
E. The wrong query parameter is being used. Alerts only work with Date and Time query parameters.

Answer: B

Explanation:
According to the Databricks documentation1, queries that use query parameters cannot be used with Alerts. This is because Alerts do not support user input or dynamic values. Alerts leverage queries with parameters using the default value specified in the SQL editor for each parameter. Therefore, if the query uses a Date query parameter, the alert will always use the same date range as the default value, regardless of the actual date. This may cause the alert to not work as expected, or to not trigger at all. Reference:
Databricks SQL alerts: This is the official documentation for Databricks SQL alerts, where you can find information about how to create, configure, and monitor alerts, as well as the limitations and best practices for using alerts.

NEW QUESTION # 16
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Databricks Certified Data Analyst Associate Exam Sample Questions (Q11-Q16):

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