Use Dash to Build Web Apps on Sage Intacct Data via CData Connect AI
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK, the pandas module, and the Dash framework, you can build Sage Intacct-connected web applications for Sage Intacct data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Sage Intacct data.
The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so pandas can read query results directly from the SDK connection object. There is no driver to install per source: connect with a Personal Access Token and build your app.
About Sage Intacct Data Integration
CData provides the easiest way to access and integrate live data from Sage Intact. Customers use CData connectivity to:
- Access Sage Intacct without worrying about API updates or changes.
- Access custom objects and fields in Sage Intacct with no extra configuration steps involved.
- Write data back to Sage Intacct using embedded Web Services credentials with Basic authentication.
- Use SQL stored procedures to perform functional operations like approving or declining vendors, inserting engagements, and creating or deleting custom objects or fields.
Users frequently integrate Sage Intact with analytics tools such as Tableau, Power BI, and Excel, and leverage our tools to replicate Workday data to databases or data warehouses.
To learn about how other customers are using CData's Sage Intacct solutions, check out our blog: Drivers in Focus: Accounting Connectivity.
Getting Started
Connect to Sage Intacct in Connect AI
CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Sage Intacct" from the Add Connection panel
-
Enter the necessary authentication properties to connect to Sage Intacct.
To connect using the Login method, the following connection properties are required: User, Password, CompanyId, SenderId and SenderPassword.
User, Password, and CompanyId are the credentials for the account you wish to connect to.
SenderId and SenderPassword are the Web Services credentials assigned to you by Sage Intacct.
- Click Save & Test
- Navigate to the Permissions tab and update the user-based permissions.

Generate a Personal Access Token (PAT)
The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.
- Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
- Give the PAT a name and click Create.

- The PAT is only visible at creation, so copy it and store it securely.
Install Required Modules
Install the SDK (with the pandas extra), Dash, and Plotly using the pip utility:
pip install "cdata-connect-ai[full]" pip install dash pip install plotly
Build a Web App on Sage Intacct Data in Python
Once the required modules are installed, you are ready to build the web app. Code snippets follow, but the full source code is available at the end of the article.
First, import the modules, then connect to Connect AI with your account email and PAT and read Sage Intacct data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, SageIntacct1).
import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
df = pd.read_sql(
"SELECT Name, TotalDue "
"FROM [SageIntacct1].[SageIntacct].[Customer] "
"WHERE CustomerId = '12345'",
conn,
)
conn.close()
Configure the App and Layout
With the query results stored in a DataFrame, build a bar graph from the Sage Intacct data and configure the app layout.
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['Name'], y=df['TotalDue'], name='Name')
app.layout = html.Div(
children=[
html.H1("CData Connect AI + Dash", style={'textAlign': 'center'}),
dcc.Graph(
id='example-graph',
figure={
'data': [trace],
'layout': go.Layout(title='Sage Intacct Customer Data', barmode='stack'),
},
),
],
className="container",
)
Set the App to Run
With the connection, app, and layout configured, you are ready to run the app.
if __name__ == '__main__':
app.run(debug=True)
Now, use Python to run the web app and a browser to view the Sage Intacct data.
python sageintacct-dash.py
More Information and Free Trial
Now you can build interactive Dash web apps on live Sage Intacct data using the CData Connect AI Python SDK. For more information on connecting to Sage Intacct (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Sage Intacct data in Python.
Full Source Code
import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
df = pd.read_sql(
"SELECT Name, TotalDue "
"FROM [SageIntacct1].[SageIntacct].[Customer] "
"WHERE CustomerId = '12345'",
conn,
)
conn.close()
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['Name'], y=df['TotalDue'], name='Name')
app.layout = html.Div(
children=[
html.H1("CData Connect AI + Dash", style={'textAlign': 'center'}),
dcc.Graph(
id='example-graph',
figure={
'data': [trace],
'layout': go.Layout(title='Sage Intacct Customer Data', barmode='stack'),
},
),
],
className="container",
)
if __name__ == '__main__':
app.run(debug=True)