How to load data from Twitter Ads to Redshift

Blendo Team

This post will help you with syncing your Twitter Ads data to Amazon Redshift. By doing this you will be able to perform advanced analytics on a system that is designed for this kind of data payloads, like Amazon RedshiftAlternatively, you can simplify the process of syncing data from Twitter Ads to Amazon Redshift by using Blendo, where the whole process will be handled by Blendo and you can focus on what matters, the monitoring of your digital marketing spending and performance data. By analyzing the data produced by Twitter Ads you can launch campaigns tailored based on your business goals and effectively expand your products reputation to new audiences. 

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

You will need more time to read this post than integrating Twitter Ads to Redshift.

Effortlessly Sync All Your Twitter Ads Data to Redshift

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.

About Twitter Ads

Twitter Ads is a self-service advertising platform, announced in April 2013 by Twitter. The ads launched within this platform belong to one of the following categories:

  1. Promoted Trends. A sponsored topic on the top of trending news section which is supposed to be one of the most discussed topics at the given time.

  2. Promoted Accounts. Accounts that are put at top of the suggested accounts box. They are usually a way for brands to gain more followers.

  3. Promoted Tweets. Tweets that shown first in the search results of related topics.

Transform and prepare your Twitter Ads data for Amazon Redshift

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.

Transform and prepare your Twitter Ads data for Amazon Redshift

Amazon Redshift is built around industry-standard SQL with added functionality to manage very large data sets and high-performance analysis. So, in order to load your data into it, you will have to follow its data model which is a typical relational database model. The data you extract from your data source should be mapped into tables and columns. Where you can consider the table as a map to the resource you want to store and columns the attributes of that resource.

Also, each attribute should adhere to the data types that are supported by Redshift.

As your data is probably coming in a representation like JSON that supports a much smaller range of data types you have to be really careful about what data you feed into Redshift and make sure that you have mapped your types into one of the datatypes that are supported by Redshift.

Designing a Schema for Redshift and mapping the data from your data source to it is a process that you should take seriously as it can both affect the performance of your cluster and the questions that you can answer. It’s always a good idea to have in your mind the best practices that Amazon has published regarding the design of a Redshift database. When you have concluded on the design of your database you need to load your data on one of the data sources that are supported as input by Redshift, these are the following:

Load your Twitter Ads data into Amazon Redshift

To upload your data to Amazon S3 you will have to use the AWS REST API, as we see again APIs play an important role in both the extraction but also the loading of data into our data warehouse. The first task that you have to perform is to create a bucket, you do that by executing an HTTP PUT on the Amazon AWS REST API endpoints for S3.

You can do this by using a tool like CURL or Postman. Or use the libraries provided by Amazon for your favorite language. You can find more information by reading the API reference for the Bucket operations on Amazon AWS documentation.

After you have created your bucket you can start sending your data to Amazon S3, using again the same AWS REST API but by using the endpoints for Object operations. As in the Bucket case you can either access the HTTP endpoints directly or use the library of your preference.

Amazon Redshift supports two methods for loading data into it. The first one is by invoking an INSERT command. You can connect to your Amazon Redshift instance with your client, using either a JDBC or ODBC connection and then you perform an INSERT command for your data.

The way you invoke the INSERT command is the same as you would do with any other SQL database, for more information you can check the INSERT examples page on the Amazon Redshift documentation.

Redshift is not designed for INSERT like operations, on the contrary, the most efficient way of loading data into it is by doing bulk uploads using a COPY command.

You can perform a COPY command for data that lives as flat files on S3 or from an Amazon DynamoDB table. When you perform COPY commands, Redshift is able to read multiple files in simultaneously and it automatically distributes the workload to the cluster nodes and performs the load in parallel.

The best way to load data from Twitter Ads to Amazon Redshift and possible alternatives

So far we just scraped the surface of what can be done with Amazon Redshift and how to load data into it. The way to proceed relies heavily on the data you want to load, from which service they are coming from and the requirements of your use case. Things can get even more complicated if you want to integrate data coming from different sources.

A possible alternative, instead of writing, hosting and maintaining a flexible data infrastructure, is to use a product like Blendo that can handle this kind of problems automatically for you.

Blendo integrates with multiple sources or services like databases, CRM, email campaigns, analytics and more. Quickly and safely move all your data from Twitter Ads to Redshift and start generating insights from your data.

Help your marketing and executive team take ownership of the advertisement data that live inside Twitter Ads to transform performance marketing and ROI.

Blendo is the easiest way to automate powerful data integrations.

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