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Start by logging into your Google Ads account. Navigate to the Reports section and create a report that includes the data you need. Once the report is set up, export it in a CSV format. This will allow you to manually manage and process the data for further use.
Open the exported CSV file and review the data. Ensure that all necessary fields are included and that the data is clean and well-organized. Remove any unnecessary columns or data that won’t be required in Typesense. Save the cleaned data in a CSV or JSON format which can be easily imported into Typesense.
Install Typesense on your local machine if it is not already set up. You can do this by following the installation instructions provided on the Typesense website. Typically, this involves downloading the Typesense binary for your operating system and running the executable. Ensure that Typesense is running by accessing the provided dashboard or using curl commands to verify its status.
Before importing data, you need to define a schema for your Typesense collection that matches the structure of your Google Ads data. This includes defining fields, data types, and any indexing settings. Create a JSON file that specifies these parameters and prepare it for use in creating a new collection in Typesense.
Use the Typesense API to create a new collection with the schema you defined. This can be done via HTTP requests using curl or a programming language of your choice. The command should include the endpoint for creating a collection, along with your schema JSON file. Ensure the collection is successfully created by reviewing the response or checking the Typesense dashboard.
With the collection ready, import your prepared data from the CSV or JSON file into Typesense. This can be done using the Typesense API. Use a script or HTTP requests to send batch data uploads to the Typesense server. Depending on the size of your data, you may need to split it into smaller chunks to ensure smooth processing.
Once the data is imported, verify its integrity by performing searches and retrieving records from your Typesense collection. Use the Typesense API or dashboard to ensure that all data points are correctly indexed and searchable. Conduct a few sample queries to confirm that the data behaves as expected in the search results.
By following these steps, you can manually move data from Google Ads to Typesense without relying on 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.
The Google Ads API is the modern programmatic interface to Google Ads and the next generation of the AdWords API and it is a paid online advertising platform offered by Google. Google Ads is a paid search channel. Google Ads is a key digital marketing tool for any business which is looking to get meaningful ad copy in front of its target audience. Google AdWords is a well known marketplace where companies pay to have their website ranked at the top of a search results page, based on keywords.
Google Ads API provides access to a wide range of data related to advertising campaigns, including:
- Campaigns: Information about the campaigns, such as name, status, budget, and targeting settings.
- Ad groups: Details about the ad groups, including name, status, and targeting criteria.
- Ads: Information about the ads, such as type, format, and performance metrics.
- Keywords: Data related to the keywords used in the campaigns, including search volume, competition, and performance metrics.
- Bidding: Details about the bidding strategies used in the campaigns, such as manual bidding or automated bidding.
- Conversions: Information about the conversions generated by the campaigns, including conversion rate, cost per conversion, and conversion tracking settings.
- Audience: Data related to the audience targeting used in the campaigns, such as demographics, interests, and behaviors.
- Location: Information about the geographic targeting used in the campaigns, including location targeting settings and performance metrics.
Overall, the Google Ads API provides a comprehensive set of data that can be used to optimize advertising campaigns and improve their 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:
