This page provides you with instructions on how to extract data from QuickBooks and load it into Google BigQuery. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is QuickBooks?
QuickBooks is Intuit's accounting software, which is available in both Desktop and Online editions. Targeted at small and medium-sized businesses, it manages payroll, inventory, and sales, and includes marketing tools, merchant services, and training resources.
What is Google BigQuery?
Google BigQuery is a data warehouse that delivers super-fast results from SQL queries, which it accomplishes using a powerful engine dubbed Dremel. With BigQuery, there's no spinning up (and down) clusters of machines as you work with your data. With that said, it's clear why some claim that BigQuery prioritizes querying over administration. It's super fast, and that's the reason why most folks use it.
Getting data out of QuickBooks
Sample QuickBooks data
QuickBooks' APIs return XML-formatted data, as in this example.
<IntuitResponse xmlns="http://schema.intuit.com/finance/v3" time="2017-04-03T10:22:55.766Z"> <QueryResponse startPosition="10" maxResults="2"> <Customer> <Id>2123</Id> <SyncToken>0</SyncToken> ... <GivenName>Srini</GivenName> </Customer> <Customer> <Id>2124</Id> <SyncToken>0</SyncToken> ... <GivenName>Peter</GivenName> </Customer> </QueryResponse> </IntuitResponse>
Loading data into Google BigQuery
Google Cloud Platform provides an introduction to loading data into BigQuery. Use the
bq tool, and in particular the
bq load command, to upload data. Its syntax is documented in the Quickstart guide for bq. You can supply the table or partition schema, or, for supported data formats, you can use schema auto-detection. Iterate through this process as many times as it takes to load all of your tables and table data into BigQuery.
Keeping QuickBooks data up to date
It's great that you've developed a script that pulls data from QuickBooks and loads it into a data warehouse, but what happens when you have new transactions, invoices, and payments?
The key is to build your script in such a way that it can identify incremental updates to your data. Use fields like CreateTime and LastUpdatedTime to identify records that are new since your last update, or since the most recent record you copied. Once you've taken new data into account, you can set up your script as a cron job or continuous loop to keep pulling down new data as it appears.
Other data warehouse options
BigQuery is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Amazon Redshift, PostgreSQL, Snowflake, or Microsoft Azure Synapse Analytics, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. Others choose a data lake, like Amazon S3 or Delta Lake on Databricks. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To Postgres, To Snowflake, To Panoply, To Azure Synapse Analytics, To S3, and To Delta Lake.
Easier and faster alternatives
If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.
Thankfully, products like Stitch were built to move data from QuickBooks to Google BigQuery automatically. With just a few clicks, Stitch starts extracting your QuickBooks data, structuring it in a way that's optimized for analysis, and inserting that data into your Google BigQuery data warehouse.