AC

SELECT 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 .

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Change: GROUP BY 1
Reasoning: Since the goal is to break down the metrics only by supply_source , we remove campaign and device_type from the SELECT and GROUP BY clauses. Grouping by the first column selected ( supply_source ) aggregates the data to the correct level.

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Change: GROUP BY 1

Reasoning: Since the goal is to break down the metrics only by supply_source , we remove campaign and device_type from the SELECT and GROUP BY clauses. Grouping by the first column selected ( supply_source ) aggregates the data to the correct level.

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About the Amazon Marketing Cloud Certification

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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Related Amazon Marketing Cloud questions

  1. 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
  2. 2How 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
  3. 3Why would this query fail? SELECT campaign, SUM(impressions) AS impressions FROM dsp_impressions
  4. 4Which table should you use in a query meant to help you choose new Amazon audiences that may benefit your Amazon DSP campaign performance?
  5. 5You 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?
  6. 6Cost and fee fields are always reported in microcents.