You are writing a query and would like to know the total impressions that have been delivered per campaign, per supply_source, and per device_type. Which of the following represents how you should write the query?
SELECT total_impressions SUM(impressions) AS device_type FROM campaign, supply_source GROUP BY 1,2,3
SELECT campaign, supply_source, device_type, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3
SELECT campaign, supply_source, SUM(impressions) AS impressions FROM device_type GROUP BY 1,2
Correct Answer
SELECT campaign, supply_source, device_type, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3
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The Amazon Marketing Cloud Certification covers Amazon's clean-room analytics environment: how AMC data is structured, writing SQL queries against it, and turning results such as overlap and path-to-conversion analysis into audience and media decisions.
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- 1SELECT total_impressions SUM (impressions) AS device_type FROM campaign, supply_source GROUP BY 1,2,3 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 The correct answer is: SELECT campaign, supply_source, device_type, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3 Explanation: The correct query to get the total impressions delivered per campaign, per supply source, and per device type is: SQL SELECT campaign, supply_source, device_type, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1, 2, 3 ✅ Explanation of the Query This is a standard and efficient SQL query structure for use in Amazon Marketing Cloud (AMC) .Multiple correct
- 2SELECT supply_source, SUM (total_cost)/100000000 AS total_cost_dollars, ((SUM (total_cost)/100000000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_inventory GROUP BY 1 SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2 SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1 The correct answer is: SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1 Explanation: That’s the correct query. Here is an explanation of the adaptation and why it works: The adapted query focuses on aggregating the desired metrics at the supply_source level, utilizing fields available in the dsp_impressions table: SQL SELECT supply_source, SUM(total_cost) / 100000 AS total_cost_dollars, ((SUM(total_cost) / 100000) / SUM(impressions)) * 1000 AS avg_cpm, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1 🔍 Explanation of Changes The core principle of the adaptation is to replace the previous grouping dimensions with the single dimension required: supply_source .Multiple correct
- 3How would you adapt this query to limit results to Sponsored Products keyword targeting only? SELECT ad_product_type, targeting, customer_search_term, match_type, SUM (spend)/100000000 AS total_cost_dollars, ((SUM (spend)/100000000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions, SUM (clicks) AS clicks, (SUM (clicks)/SUM (impressions)) AS ctr FROM sponsored_ads_traffic WHERE match_type IN (‘PHRASE’, ‘BROAD’, ‘EXACT’) GROUP BY 1,2,3,4
- 4Iris, a consumer electronics brand, would like to modify a query to only include purchase records from the underlying table. Which of the following represents how the query should be written?
- 5Why would this query fail? SELECT campaign, SUM(impressions) AS impressions FROM dsp_impressions
- 6When determining total impressions served over a given date range, you can use dsp_impressions or dsp_views.