Access your data on Twitter Ads

The first step in loading your Twitter Ads data to any kind of data warehouse solution is to access your data and start extracting it.

By using the Ads API program businesses can create, run and manage ad campaigns programmatically on Twitter. A big part of the API is also a rich reporting system that helps you tailor your campaigns by selecting different targeting options and placement parameters. You can also retrieve detailed statistics on the performance of your campaigns by generating reporting or historical backfills.

Using this API, a user can retrieve details associated with the current account regarding the following resources:

• Campaigns
• Features
• Lineitem Apps & Lineitems
• Promoted Accounts & Promoted tweets reference
• Scheduled promoted tweets reference
• Funding Instruments
• Media Creatives
• Recommendations
• Targeting Criteria
• Account Media
• Scheduled/Promoted/Organic/Draft Tweets

Various reports can also be fetched as long as they are valid combinations between an entity and segmentation types, such as:

• Reach Campaigns Report
• Reach Funding Instruments Report
• Auction Insights Report

In addition to the above, the things that you have to keep in mind when dealing with the Twitter API, are:

1. Rate limits. There is no restriction for concurrent API calls. There is a restriction for API calls per endpoint in a 15-minute window. However, in general limits are generous for most endpoints and should not impede use cases.
2. Authentication. You authenticate on Twitter Ads using OAuth.
3. Pagination. There is a pagination ability for retrieving data in some resources, with a page count that varies from 200 to 1000 depending on the specific resource endpoint. There is also a sorting method for retrieving data in some resources.

Transform and prepare your Twitter Ads data for PostgreSQL

After you have accessed your data on Twitter Ads, you will have to transform it based on two main factors,

1. The limitations of the database that the data will be loaded onto
2. The type of analysis that you plan to perform

Each system has specific limitations on the data types and data structures that it supports. If for example, you want to push data into Google BigQuery, then you can send nested data like JSON directly.

Of course, when you are dealing with tabular data stores, like Microsoft SQL Server, this is not an option. Instead, you will have to flatten out your data, just as in the case of JSON, before loading into the database.

Also, you have to choose the right data types. Again, depending on the system that you will send the data to and the data types that the API exposes to you, you will have to make the right choices. These choices are important because they can limit the expressivity of your queries and limit your analysts on what they can do directly out of the database.

Each table is a collection of columns with a predefined data type like an integer or VARCHAR. PostgreSQL, like any other SQL database, supports a wide range of different data types.

A typical strategy for loading data from Twitter Ads to a Postgres database is to create a schema where you will map each API endpoint to a table. Each key inside the Twitter Ads API endpoint response should be mapped to a column of that table and you should ensure the right conversion to a Postgres compatible data type.

Load data from Twitter Ads to PostgreSQL

For example, if you have an endpoint from Twitter Ads that returns a value as String, you should convert it into a VARCHAR with a predefined max size or TEXT data type. tables can then be created on your database using the CREATE SQL statement.

Once you have defined your schema and you have created your tables with the proper data types, you can start loading data into your database.

The preferred way of adding larger datasets into a PostgreSQL database is by using the COPY command. COPY is copying data from a file on a file system that is accessible by the Postgres instance, in this way much larger datasets can be inserted into the database in less time. COPY requires physical access to a file system in order to load data.

Nowadays, with cloud-based, fully managed databases, getting direct access to a file system is not always possible. If this is the case and you cannot use a COPY statement, then another option is to use PREPARE together with INSERT, to end up with optimized and more performant INSERT queries.

Updating your Twitter Ads data on PostgreSQL

As you will be generating more data on Twitter Ads, you will need to update your older data on PostgreSQL. This includes new records together with updates to older records that for any reason have been updated on Twitter Ads.

You will need to periodically check Twitter Ads for new data and repeat the process that has been described previously while updating your currently available data if needed. Updating an already existing row on a PostgreSQL table is achieved by creating UPDATE statements.

Another issue that you need to take care of is the identification and removal of any duplicate records on your database. Either because Twitter Ads does not have a mechanism to identify new and updated records or because of errors on your data pipelines, duplicate records might be introduced to your database.

In general, ensuring the quality of the data that is inserted in your database is a big and difficult issue and PostgreSQL features like TRANSACTIONS can help tremendously, although they do not solve the problem in the general case.

The best way to load data from Twitter Ads to PostgreSQL

So far we just scraped the surface of what you can do with PostgreSQL and how to load data into it. Things can get even more complicated if you want to integrate data coming from different sources.

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