vmartinez

Super Power Batteries, a consumer packaged goods brand, is new to AMC and wants to learn more about what tables are available to query. Where in the AMC UI can they find this information?

• Submitted queries
• Query editor
• Instance info
• Schema explorer

 

Explanation:

The correct answer is **Schema explorer** because the Schema Explorer in the AMC (Amazon Marketing Cloud) user interface provides users with a comprehensive view of all the available tables and their structure within the AMC environment. It allows users, like Super Power Batteries, to explore the different tables, fields, and relationships in order to better understand the data they can query. This tool is essential for discovering which tables are relevant to their analysis and for navigating through the available datasets. The other options, such as Submitted queries, Query editor, and Instance info, focus on different aspects of query creation or instance management but do not provide direct access to a list of all available tables like the Schema Explorer does.

 

 

Which of the following statements is true about using queries within the instructional query library?

 

• Instructional query templates cannot be modified ahead of running
• Query templates can be edited to include relevant dimensions and metrics for your use case
• Queries can be uploaded by AMC users and saved for future use

 

Explanation: The correct answer is **Query templates can be edited to include relevant dimensions and metrics for your use case** because within the Instructional Query Library (IQL) in Amazon Marketing Cloud (AMC), query templates are provided to help users get started with common types of analyses. These templates are editable, allowing users to customize them by adding or modifying dimensions, metrics, and filters to fit their specific use case. This flexibility enables users to tailor the provided templates to their unique analytical needs, ensuring that the queries align with the data they are interested in analyzing. The other options are incorrect because users can indeed modify the query templates and save them for future use, making them adaptable for ongoing analysis. Additionally, the statement that templates cannot be modified ahead of running is false, as users are encouraged to edit and adjust them before executing the queries.

 

If you want to understand more about which product or pixel your conversion events are associated with, which field in the amazon_attributed_events_* tables should you leverage?

• tracked_item
• conversion
• tracked_asin
• ad_product_type

 

Explanation:

The correct answer is **tracked_item** because the **tracked_item** field in the amazon_attributed_events_* tables is specifically used to identify the product or pixel associated with a conversion event. This field provides the information about the specific item that was tracked and resulted in a conversion, allowing you to link the conversion data back to the relevant product or pixel. This is essential for understanding which products or pixels contributed to conversions in your advertising campaigns. The other fields, such as ad_product_type, conversion, and tracked_asin, are related to different aspects of the data but do not directly provide the product or pixel association in the way that **tracked_item** does.

 

Why would this query fail?

SELECT campaign,
SUM(impressions) AS impressions
FROM dsp_impressions

 

• There is no GROUP BY statement; this query cannot be run without aggregation on the campaign dimension.
• There is no WHERE clause to filter the query results based on one or more conditions.
• SELECT statements can not be used to choose metrics from a table.

 

Nutrition Co., a health snack company, would like to know the total impressions that have been delivered per campaign, per supply_source, per device_type. Which of the following represents how to write this query?

• SELECT campaign, supply_source, SUM(impressions) AS impressions FROM device_type GROUP BY 1,2
• SELECT campaign, supply_source, device_type, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3
• SELECT total_impressions SUM(impressions) AS device_type FROM campaign, supply_source GROUP BY 1,2,3

 

Explanation:

The correct answer is **SELECT campaign, supply_source, device_type, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3** because this query correctly aggregates the total impressions by campaign, supply source, and device type using the **dsp_impressions** table. The **dsp_impressions** table tracks impressions delivered through Amazon DSP, and the query groups the data by the relevant dimensions (campaign, supply source, and device type) while calculating the sum of impressions for each combination. This approach ensures that you can track how impressions are distributed across different campaigns, supply sources, and devices. The other options do not correctly group the data or reference the appropriate tables, making them incorrect for this analysis.

 

 

You can use a _________ filter to limit your query results based on one or more conditions.

 

• WHERE
• FROM
• SELECT

 

Explanation:

The correct answer is **WHERE** because the **WHERE** filter is used in SQL to limit query results based on specific conditions. By applying the **WHERE** clause, you can specify criteria that must be met for records to be included in the query result. This allows you to filter the data based on values in specific columns, such as limiting the results to a certain date range, campaign type, or other relevant factors. The **FROM** clause is used to specify the data source or table from which to query data, while the **SELECT** clause is used to define which columns to retrieve. Therefore, the **WHERE** clause is the correct choice for filtering query results based on conditions.