Access your data on DoubleClick (for Publishers)

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

For accessing your data you can use the API of Ad Manager which is implemented using the SOAP protocol and consequently this will add some complexity to your development as you will have to manage SOAP and XML responses. However, to help you get started Google offers client libraries for Java, .NET, Python, PHP, and Ruby that offer wrapper functions and various features.

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

• Rate limits. Depending on the chosen plan and API version that is being used, Ad Manager API allows a number of calls per hour.
• Authentication. You authenticate all Ad Manager API requests using OAuth2.
• Error Handling. Make sure that you handle errors correctly.

Each custom report is composed of the following:

1. Dimensions. The user can select a number of dimensions for the report.
2. Dimension Attributes. Specific dimensions can optionally be enhanced with some attributes. There are constraints on what attributes can be selected, depending on the dimensions that the user has chosen.
3. Columns. Can be considered as metrics that provide all the trafficking statistics and revenue information available for the chosen dimension object. There are constraints of what columns can be combined with what dimensions.

Transform and prepare your DoubleClick (for Publishers) Data for PostgreSQL Replication

After you have accessed your data on DoubleClick, 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, but keep in mind that in the case of a SOAP API like DoubleClick, you get XML responses.

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.

With DoubleClick data, you have two main additional sources of complexity. When it comes to data types you have to keep in mind that SOAP is using XML to describe the service and the data, so the data types that you have to map are coming from XML and might have automatically been transformed into the primitive data types of the language that you are using.

Also, you have to consider that the reports you’ll get from DoubleClick are like CSV files in terms of their structure and you need to somehow identify what and how to map a table into your database. This way you will be able to join, combine and query your data in order to assess the performance of various ads and finally improve ROI for display ad campaigns.

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 DoubleClick to a Postgres database is to create a schema where you will map each API endpoint to a table. Each key inside the DoubleClick’s 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.

Export data from DoubleClick (for Publishers) to PostgreSQL

For example, if an endpoint from DoubleClick 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 DoubleClick (for Publishers) data on PostgreSQL

As you will be generating more data on DoubleClick, 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 DoubleClick.

You will need to periodically check DoubleClick 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 DoubleClick 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 DoubleClick (for Publishers) to PostgreSQL

So far, we just scraped the surface of what can be done with PostgreSQL and how to ingest 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 RudderStack that can handle this kind of problem automatically for you.

Easily use the DoubleClick (for Publishers) connector from RudderStack, along with multiple sources or services like databases, CRM, email campaigns, analytics, and more. Quickly and safely ingest DoubleClick data into PostgreSQL and start generating insights from your data.