This page provides you with instructions on how to extract data from Sage Intacct and load it into Amazon S3. (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 Sage Intacct?
Sage Intacct provides accounting and financial management software with automation and controls around billing, accounting, and reporting. Components include accounts payable, accounts receivable, cash management, general ledger, order management, and purchasing.
What is S3?
Amazon S3 (Simple Storage Service) provides cloud-based object storage through a web service interface. You can use S3 to store and retrieve any amount of data, at any time, from anywhere on the web. S3 objects, which may be structured in any way, are stored in resources called buckets.
Getting data out of Sage Intacct
Sage Intacct provides an API that lets developers retrieve data stored in the platform. Intacct also has a Data Delivery Service (DDS) that enables companies to extract data from the platform and send it to a cloud storage location.
Loading data into Amazon S3
To upload files you must first create an S3 bucket. Once you have a bucket you can add an object to it. An object can be any kind of file: a text file, data file, photo, or anything else. You can optionally compress or encrypt the files before you load them.
Keeping Sage Intacct data up to date
You can code 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.
The key is to build your script in such a way that it can identify incremental updates to your data. Once you've taken new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.
Other data warehouse options
S3 is great, but sometimes you want a more structured repository that can serve as a basis for BI reports and data analytics — in short, a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, Snowflake, Microsoft Azure Synapse Analytics, or Panoply, which are RDBMSes that use similar SQL syntax. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Postgres, To Snowflake, To Azure Synapse Analytics, and To Panoply.
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 Sage Intacct to Amazon S3 automatically. With just a few clicks, Stitch starts extracting your Sage Intacct data, structuring it in a way that's optimized for analysis, and inserting that data into your Amazon S3 data warehouse.