This post helps you with loading data from your Enchant to PostgreSQL. If you are looking to get analytics-ready data without the manual hassle, you can integrate Enchant to PostgreSQL with RudderStack, so you can focus on what matters, getting value out of your customer support data.
Access your data on Enchant
The first step in loading your Enchant data to any kind of data warehouse solution is to access your data and start extracting it.
Enchant offers a REST API built on pragmatic RESTful design principles that you can use to programmatically interact with your account.
From the available endpoints you can retrieve the following information:
- Tickets: All user requests are tracked as tickets. Tickets contain one or more messages
- Messages: Messages include the replies and notes associated with the tickets
- Attachments: Attachments are associated with messages. After uploading an attachment, a message must be created using the attachment id. An attachment can be associated with only one message.
- Users: Details about your help desk operators.
- Customers: Details about the customers associated with at least one ticket.
- Contacts: Email addresses and Twitter accounts are represented as contacts on a customer.
In addition to the above, the things that you have to keep in mind when dealing with the Enchant API, are:
- Rate limits. The API is rate limited to 100 credits per minute for an entire help desk across all endpoints, users, and tokens. A request is typically worth 1 credit.
- Authentication. Requests to the Enchant API are authenticated using access tokens.
- Pagination. Requests for collections can return between 0 and 100 results. All endpoints are limited to 10 results by default. However, not all endpoints support pagination.
Enchant is a customer support software that focuses on the support needs of small or medium-sized companies. It is self-claimed to be a simpler and much cheaper alternative for other help desk software, primarily focusing on e-mail integration.
While using Enchant as your ticketing platform you can easily keep track of all ongoing tickets as well as manage all the support-related communication across all channels. You can also produce various helpdesk reports in order to better understand your team’s performance, gauge your customers’ level of satisfaction and gain important insight regarding possible improvements.
Apart from all the above Enchant also offers a knowledge base space in order to allow customers to help themselves regarding the most frequently asked questions while enabling the live chat in your website or in your app you can improve your customer experience by resolving issues on the spot.
Transform and prepare your Enchant Data for PostgreSQL
After you have accessed your data on Enchant, you will have to transform it based on two main factors,
- The limitations of the database that the data will be loaded onto
- 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 it 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. Enchant has a very limited set of available data types which means that your work to do these mappings is much easier and straightforward, but nonetheless equally important with any other case of a data source.
Each table is a collection of columns with a predefined data type asike 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 Enchant to a Postgres database is to create a schema where you will map each API endpoint to a table. Each key inside the Enchant 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 Enchant to PostgreSQL
For example, if an endpoint from Enchant 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 Enchant data on PostgreSQL
As you will be generating more data on Enchant, 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 Enchant.
You will need to periodically check Enchant 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 Enchant 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 inserted in your database is a big and difficult issue, and PostgreSQL features like TRANSACTIONS can help tremendously. However, they do not solve the problem in the general case.
The best way to load data from Enchant 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.<