This page provides you with instructions on how to extract data from Sage Intacct and load it into Panoply. (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 Panoply?
Panoply is a fully managed data warehouse service that can spin up an Amazon Redshift instance in just a few clicks. It uses machine learning and natural language processing (NLP) to learn, model, and automate standard data management activities from source to analysis. It can import data with no schema, no modeling, and no configuration. With Panoply, you can use your favorite analysis, SQL, and visualization tools just as you would if you were creating a Redshift data warehouse on your own.
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 Panoply
Once you have identified all of the columns you want to insert, you can use the CREATE TABLE statement in Panoply's Redshift data warehouse to create a table to receive all of the data.
With a table built, it may seem like the easiest way to migrate your data (especially if there isn't much of it) is to build INSERT statements to add data to your Redshift table row by row. If you have any experience with SQL, this will be your gut reaction. But beware! Redshift isn't optimized for inserting data one row at a time. If you have a high volume of data to be inserted, you would be better off loading the data into Amazon S3 and then using the COPY command to load it into Redshift.
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
Panoply 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, Google BigQuery, PostgreSQL, Snowflake, or Microsoft Azure Synapse Analytics, which are RDBMSes that use similar SQL syntax. 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 BigQuery, To Postgres, To Snowflake, To Azure SQL Data Warehouse, 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 Sage Intacct to Panoply 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 Panoply data warehouse.