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Begin by accessing your Amazon Ads account. Use the Amazon Ads API to programmatically extract the desired data. You'll need to have API access credentials, which can be obtained from the Amazon Ads Developer portal. Use the API to fetch the data in a structured format like JSON or CSV.
Once you have extracted the data, transform it into a format compatible with Starburst Galaxy. If your extracted data is in JSON, you might need to convert it to CSV or Parquet, as these formats are commonly used in data processing platforms. Use scripting languages like Python or tools like AWS Lambda for this transformation.
Upload the transformed data to an Amazon S3 bucket. Amazon S3 is a reliable and scalable storage service that can be easily accessed by Starburst Galaxy. Ensure you have the appropriate permissions set up on the S3 bucket to allow for data access.
Set up the necessary permissions for Starburst Galaxy to access the data in your Amazon S3 bucket. This typically involves creating an AWS Identity and Access Management (IAM) role with permissions to read from the S3 bucket and then granting Starburst Galaxy access to assume this role.
Within Starburst Galaxy, configure a catalog to connect to your Amazon S3 bucket. Use the built-in S3 connector in Starburst Galaxy, which allows you to define the location of your data in S3 and the format in which it is stored. Specify the IAM role that was configured for access in the previous step.
Once the connection is established, use SQL queries within Starburst Galaxy to interact with your data. You can perform various operations such as filtering, aggregating, and joining with other datasets stored in Starburst Galaxy.
To streamline the process, automate these steps using a combination of AWS services. You can use AWS Lambda for data transformation and scheduling tools like Amazon EventBridge or AWS Step Functions to automate data extraction, transformation, and loading (ETL) processes. This ensures that your data is regularly updated in Starburst Galaxy.
By following these steps, you can effectively move your data from Amazon Ads to Starburst Galaxy without the need for third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Amazon Advertising, or Amazon Pay-Per-Click (PPC) advertising, is becoming a significant threat to both Facebook and Google's monopoly on the PPC market share. Consumers of all sorts use Amazon to check and compare prices, find new products, begin product searches, and make immediate purchases. Amazon itself claims that 76% of its shoppers use the search bar to find an item, opening the door to PPC advertising. This allows sellers and brands to reach a wide range of consumers while they shop, which means they are often already in the buying phase of the consumer journey. With over 300 million active customer accounts, leveraging this powerful advertising channel is undeniably integral to any e-commerce campaign. Not to mention, Amazon is only getting bigger. Amazon Advertising positions your brand ahead of the competition, and your business should be taking full advantage of this platform. Below, we’ve put together a comprehensive guide to further your knowledge and understanding of Amazon Advertising tools, products, and opportunities to equip your brand with the necessary knowledge to maximize its reach and boost results.
Amazon Ads API provides access to a wide range of data related to advertising campaigns on Amazon. The following are the categories of data that can be accessed through the API:
1. Campaign data: This includes information about the campaigns such as campaign name, start and end dates, budget, targeting options, and bid strategy.
2. Ad group data: This includes information about the ad groups such as ad group name, targeting options, and bid strategy.
3. Keyword data: This includes information about the keywords such as keyword match type, bid, and performance metrics.
4. Product data: This includes information about the products being advertised such as product name, ASIN, and product category.
5. Performance data: This includes information about the performance of the campaigns, ad groups, keywords, and products such as impressions, clicks, conversions, and cost.
6. Audience data: This includes information about the audiences being targeted such as demographics, interests, and behaviors.
7. Inventory data: This includes information about the inventory being advertised such as availability, pricing, and product details.
Overall, Amazon Ads API provides access to a comprehensive set of data that can be used to optimize advertising campaigns and improve performance.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
