Certified Data Analyst Associate Exam Questions

A- Create a new table from CustomerInteractions using GROUP BY customer_id, interaction_date and aggregate functions to capture the latest interaction.

B- Utilize Delta Lake's time travel feature to revert CustomerInteractions to a state before duplicates were introduced.

C- Implement a WINDOW function partitioned by customer_id and ordered by interaction_date to rank interactions and delete lower-ranked duplicates.

D- Employ SELECT DISTINCT customer_id, interaction_date, ... FROM CustomerInteractions to create a distinct list of interactions.

E- Use DELETE FROM CustomerInteractions WHERE ... to remove duplicate rows based on a subquery that identifies the earliest interactions.

A- By the speed of query execution on the table.

B- By the type of data stored in the table.

C- By the number of columns in the table.

D- By the location of the data files specified in the table definition.

E- By the size of the table data.

A- The key audience includes both data analysts and data scientists, with no significant side audiences.

B- The key audience is exclusively data engineers, with software developers as a side audience.

C- The key audience is data scientists, with both data engineers and software developers as side audiences.

D- The primary audience consists of data analysts, with data scientists and data engineers forming the side audiences.

E- The main audience comprises business intelligence professionals, with data analysts and data engineers as side audiences.

A- SELECT ProductID FROM SalesRecords WHERE SaleAmount > 500 AND SaleID IN (SELECT MIN(SaleID) FROM SalesRecords GROUP BY ProductID);

B- SELECT ProductID FROM SalesRecords WHERE SaleAmount > 500 AND SaleDate = (SELECT MIN(SaleDate) FROM SalesRecords WHERE ProductID = SalesRecords.ProductID);

C- SELECT DISTINCT ProductID FROM SalesRecords WHERE SaleAmount > 500 GROUP BY ProductID HAVING SaleDate = MIN(SaleDate);

D- SELECT ProductID FROM SalesRecords WHERE SaleAmount > 500 AND SaleDate = (SELECT MIN(SaleDate) FROM SalesRecords GROUP BY ProductID);

E- SELECT ProductID FROM (SELECT ProductID, MIN(SaleDate) AS FirstSaleDate FROM SalesRecords GROUP BY ProductID) AS FirstSales WHERE FirstSaleDate > 500;

A- Only the original creator of a Databricks SQL dashboard has the ability to view and run it, making it unsuitable for team collaboration.

B- Only data engineers and IT professionals can view and run Databricks SQL dashboards due to their technical nature.

C- Databricks SQL dashboards are exclusively for top-level executives for strategic decision-making and are not accessible to other users.

D- A variety of users, including analysts, managers, and other stakeholders, can view and run Databricks SQL dashboards for collaborative data analysis and decision-making.

E- Databricks SQL dashboards are publicly accessible and can be viewed and run by anyone with internet access, without any restrictions.

A- To specify the computational resources for processing data in the catalog or schema.

B- To determine the default file format for the catalog or schema.

C- To define the cloud object storage location for data of managed tables and volumes.

D- To set the encryption type for data stored in the catalog or schema.

E- To configure the network access settings for the catalog or schema.

A- SELECT order_info:items.product_id, order_info:items.quantity FROM customer_orders;

B- SELECT order_info:items[0].product_id AS product_id, order_info:items[0].quantity AS quantity FROM customer_orders;

C- SELECT FLATTEN(order_info:items.product_id[0], order_info:items.quantity[0]) FROM customer_orders;

D- SELECT EXPLODE(order_info:items) AS (product_id, quantity) FROM customer_orders;

E- SELECT order_info:items[*].product_id, order_info:items[*].quantity FROM customer_orders UNNEST items;

A- A view is session-specific, while a temporary view persists across sessions.

B- Both views and temporary views store data physically in the workspace.

C- A view stores data physically, whereas a temporary view only exists during the session.

D- Temporary views allow data modifications, unlike regular views.

E- Both views and temporary views do not store data physically, but a view persists beyond the session.

A- ROLLUP generates aggregations in a random order, ignoring the hierarchy of columns in the GROUP BY clause. It produces subtotals only for individual employees, without generating department-level subtotals or a grand total.

B- Both ROLLUP and CUBE produce identical aggregations, including subtotals for each 'Department', each 'Employee', each combination of 'Department' and 'Employee', and a grand total.

C- Neither ROLLUP nor CUBE will generate subtotals for individual 'Departments' or 'Employees'; they only provide a grand total.

D- ROLLUP provides aggregations only for each combination of 'Department' and 'Employee', while CUBE gives a detailed breakdown including each 'Department', each 'Employee', and a grand total.

E- CUBE creates aggregations for all possible combinations of the columns in the GROUP BY clause. It would generate subtotals for each 'Department', each 'Employee', each combination of 'Department' and 'Employee', but not a grand total.

A- To act as the primary interface for application development and deployment within the Databricks ecosystem.

B- To facilitate SQL-based data querying and analysis, offering a managed environment for running SQL queries on large datasets.

C- To offer a centralized platform for advanced machine learning model development and deployment.

D- To provide a secure environment for data encryption and compliance management.

E- To serve as the primary storage location for large-scale data sets, replacing traditional data warehouses.