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.
Correct Answers
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.
Exam guide and all 94 Amazon Marketing Cloud questions →Related Amazon Marketing Cloud questions
- 1How 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
- 2Why would this query fail? SELECT campaign, SUM(impressions) AS impressions FROM dsp_impressions
- 3Which table should you use in a query meant to help you choose new Amazon audiences that may benefit your Amazon DSP campaign performance?
- 4You 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?
- 5Cost and fee fields are always reported in microcents.
- 6What formula would you use to calculate Amazon DSP CPM using the fields available in dsp_impressions?