How to load data from Twitter Ads to Snowflake

Access your data on Twitter Ads

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

Using the Twitter Ads API program, businesses can create, run and manage ad campaigns programmatically on Twitter. A big part of the API is 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 15-minute windows. 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 Snowflake

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

1. The limitations of the database that is going to be used
2. The type of analysis that you plan to perform

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

Of course, when you deal 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 a database.

Also, you have to choose the right data types. Again, depending on the system that you will send 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.

Data in Snowflake is organized around tables with a well-defined set of columns with each one having a specific data type.

Snowflake supports a rich set of data types. It is worth mentioning that a number of semi-structured data types is also supported. It is possible to load data directly in JSON, Avro, ORC, Parquet, or XML format with Snowflake. Hierarchical data is treated as a first-class citizen, similar to what Google BigQuery offers.

There is also one notable common data type that Snowflake does not support. LOB or large object data type is not supported; instead, you should use a BINARY or VARCHAR type. But these types are not that useful for data warehouse use cases.

A typical strategy for loading data from Twitter Ads to Snowflake 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 Snowflake data type.

Of course, you will need to ensure that as any data types from the Twitter Ads API might change, you will adapt your database tables accordingly. There’s no such thing as automatic data type casting.

After you have a complete and well-defined data model or schema for Snowflake, you can move forward and start loading your data into the database.

Load data from Twitter Ads to Snowflake

Usually, data is loaded into Snowflake in a bulk way, using the COPY INTO command. In JSON format, files containing data are stored in a local file system or in Amazon S3 buckets. Then a COPY INTO command is invoked on the Snowflake instance, and data is copied into a data warehouse.

The files can be pushed into Snowflake using the PUT command, into a staging environment before the COPY command is invoked.

Another alternative is to upload every data directly into a service like Amazon S3 from where Snowflake can access them directly.

Updating Twitter Ads data on Snowflake

As you will be generating more data on Twitter Ads, you will need to update your older data on Snowflake. 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. For example, updating an already existing row on a Snowflake table is achieved by creating UPDATE statements.

Another issue that you need to take care of is identifying and removing 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 data that is inserted into your database is a big and difficult issue.

The best way to load data from Twitter Ads to Snowflake

So far we just scraped the surface of what you can do with Snowflake 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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