This page provides you with instructions on how to extract data from Codat and analyze it in Amazon QuickSight. (If the mechanics of extracting data from Codat seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is Codat?
Codat provides a standardized data format across multiple accountancy software applications and financial APIs.
What is QuickSight?
Amazon QuickSight is the AWS business intelligence tool for creating dashboards and visualizations. Users are charged per session only for the time when they access dashboards or reports. QuickSight supports a variety of data sources, such as individual databases (Amazon Aurora, MariaDB, and Microsoft SQL Server), data warehouses (Amazon Redshift and Snowflake), and SaaS sources (Adobe Analytics, GitHub, and Salesforce), along with several common standard file formats.
Getting data out of Codat
Codat exposes data through a REST API, which developers can use to extract information. To access information, you can use a GET method to retrieve data via the Codat API. Codat exposes data from customers, suppliers, invoices, bills, payments, creditNotes, and bankStatements endpoints. You can use an optional query
parameter in the format [propertyName][operator][value]
to select only certain data. Operators include "equal to" (%3d) and, for numeric and date values, "greater than" (%3e), and "less than" (%ec). So, to retrieve invoices for a customer whose ID is "61," you would call:
GET /companies/[companyId]/data/invoices?query=customerRef.id%3d61
Sample Codat data
A GET call returns a JSON object with all the fields of the specified dataset as a reply. Invoices, for example, have 11 possible properties, though all of them may not be present for any given record, so the JSON might look like:
{ "id": "20", "invoiceNumber": "1001", "customerRef": { "id": "55", "companyName": "Oxon - Holiday Party" }, "issueDate": "2017-01-24T00:00:00", "dueDate": "2017-02-23T00:00:00", "currency": "GBP", "totalAmount": 10800, "amountDue": 0 }
Loading data into QuickSight
You must replicate data from your SaaS applications to a data warehouse (such as Redshift) before you can report on it using QuickSight. Once you specify a data source you want to connect to, you must specify a host name and port, database name, and username and password to get access to the data. You then choose the schema you want to work with, and a table within that schema. You can add additional tables by specifying them as new datasets from the main QuickSight page.
Using data in QuickSight
QuickSights provides both a visual report builder and the ability to use SQL to select, join, and sort data. QuickSight lets you combine visualizations into dashboards that you can share with others, and automatically generate and send reports via email.
Keeping Codat up to date
At this point you've coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.
Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in Codat.
And remember, as with any code, once you write it, you have to maintain it. If Codat modifies its API, or the API sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.
From Codat to your data warehouse: An easier solution
As mentioned earlier, the best practice for analyzing Codat data in Amazon QuickSight is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Codat to Redshift, Codat to BigQuery, Codat to Azure Synapse Analytics, Codat to PostgreSQL, Codat to Panoply, and Codat to Snowflake.
Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Codat with Amazon QuickSight. With just a few clicks, Stitch starts extracting your Codat data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Amazon QuickSight.