How to load data from DoubleClick to Redshift
Access your data on DoubleClick (for Publishers)
The first step in loading your DoubleClick data to any kind of data warehouse solution is to access them and start extracting it.
For accessing data you can use the Publishers API 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 for Publishers (DoubleClick) API, are:
- Rate limits. Depending on the chosen plan and API version that is being used, for Publishers API allows an amount of calls per hour.
- Authentication. You authenticate all for Publishers API requests using OAuth2.
- Error Handling. Make sure that you handle errors correctly
Each custom report is composed of the following:
- Dimensions. The user can select a number of dimensions for the report.
- 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.
- 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 data DoubleClick (for Publishers) for Amazon Redshift Replication
After you have accessed data on DoubleClick, you will have to transform it based on two main factors,
- The limitations of the database that data will be loaded onto
- The type of analysis that you plan to perform
Each system has specific limitations on the types of data and 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 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 data to and the 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 data, so every data types that you have to map are coming from XML and might have automatically be 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 to a table into your database. This way you will be able to join, combine and query Doubleclick’s data in order to assess the performance of various ads and finally improve ROI for display ad campaigns.
Transform and prepare your DoubleClick (for Publishers) 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, to load data into it, you will have to follow its model, which is a typical relational database model. Data you extract from a 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 types of data that are supported by Redshift.
As 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 every data on one of the supported data sources as input by Redshift, these are the following:
Export data from DoubleClick (for Publishers) to Amazon Redshift
To upload DoubleClick’s 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 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.
Redshift supports two methods for loading data into it. The first one is by invoking an INSERT command. You can connect to your 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 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.
If you are looking into other data warehouses you may check our how to’s on DoubleClick to Snowflake, DoubleClick to MS SQL Server, DoubleClick to BigQuery, DoubleClick to PostgreSQL.
The best way to load data from DoubleClick (for Publishers) to Amazon Redshift
So far we just scraped the surface of what can be done with Redshift 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 Redshift and start generating insights from your data. Don't want to go through the pain of direct integration? RudderStack’s DoubleClick to Redshift integration makes it easy to send data from DoubleClick to Redshift.