How to load data from BaseCRM to PostgreSQL

Access your data on BaseCRM

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

As previously mentioned, using Base’s rich Core API you can get access to data from 25 resources including, among others, the following:

• Account: The Account API provides read-only access to your account details.
• Calls: The Calls API provides a simple interface to manage calls.
• Contacts: The Contacts API provides a simple interface to manage your contacts. A contact represents an individual or an organization.
• Deals: The Deals API provides a simple interface to manage deals.
• Leads: The Leads API provides a simple interface to manage leads. A lead represents an individual or an organization that expresses interest in your goods or services.
• Orders: Through the Orders API you can manage your orders.
• Pipelines: The Pipelines API provides a read-only interface to your sales pipeline definition.
• Products:The Products API offers an interface for managing the Product Catalog. The catalog lists products that are available in your account.
• Users: Using the User’s API you can interact with your account’s users. You can retrieve a single user as well as list of all users associated with your account.

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

1. Rate limits. According to the documentation, you can make up to 36,000 requests per hour (10 requests/ip/second).
2. Authentication. You can authenticate on BaseCRM using OAuth.
3. Pagination. API endpoints that return a collection of items are always paginated. The number of results to display can vary with a maximum value of 100.

Transform and prepare your BaseCRM data for PostgreSQL

After you have accessed your data on BaseCRM, 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.

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.

Also, you have to consider that the reports you’ll get from BaseCRM 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.

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

For example, if you an endpoint from BaseCRM 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 the 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 BaseCRM data on PostgreSQL

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

You will need to periodically check BaseCRM 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 BaseCRM 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 BaseCRM 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.

Are you striving to achieve results right now?

Instead of writing, hosting and maintaining a flexible data infrastructure use RudderStack that can handle everything automatically for you.

RudderStack, with one click, integrates with sources or services, creates analytics-ready data and syncs your BaseCRM to PostgreSQL right away.