Use Dash to Build Web Apps on Dynamics 365 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 Dynamics 365-connected web applications for Dynamics 365 data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Dynamics 365 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 Dynamics 365 Data Integration
CData simplifies access and integration of live Microsoft Dynamics 365 data. Our customers leverage CData connectivity to:
- Read and write data in the full Dynamics 365 ecosystem: Sales, Customer Service, Finance & Operations, Marketing, and more.
- Extend the native features of Dynamics CRM with customizable caching and intelligent query aggregation and separation.
- Authenticate securely with Dynamics 365 in a variety of ways, including Microsoft Entra ID, Azure Managed Service Identity credentials, and Azure Service Principal using either a client secret or a certificate.
- Use SQL stored procedures to manage their Dynamics 365 entities - listing, creating, and removing associations between entities.
CData customers use our Dynamics 365 connectivity solutions for a variety of reasons, whether they're looking to replicate their data into a data warehouse (alongside other data sources) or analyze live Dynamics 365 data from their preferred data tools inside the Microsoft ecosystem (Power BI, Excel, etc.) or with external tools (Tableau, Looker, etc.).
Getting Started
Connect to Dynamics 365 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 "Dynamics 365" from the Add Connection panel
-
Enter the necessary authentication properties to connect to Dynamics 365.
Edition and OrganizationUrl are required connection properties. The Dynamics 365 connector supports connecting to the following editions: CustomerService, FieldService, FinOpsOnline, FinOpsOnPremise, HumanResources, Marketing, ProjectOperations and Sales.
For Dynamics 365 Business Central, use the separate Dynamics 365 Business Central driver.
OrganizationUrl is the URL to your Dynamics 365 organization. For instance, https://orgcb42e1d0.crm.dynamics.com
- 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 Dynamics 365 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 Dynamics 365 data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, Dynamics3651).
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 GoalHeadingId, Name "
"FROM [Dynamics3651].[Dynamics365].[GoalHeadings] "
"WHERE Name = 'MyAccount'",
conn,
)
conn.close()
Configure the App and Layout
With the query results stored in a DataFrame, build a bar graph from the Dynamics 365 data and configure the app layout.
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['GoalHeadingId'], y=df['Name'], name='GoalHeadingId')
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='Dynamics 365 GoalHeadings 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 Dynamics 365 data.
python dynamics365-dash.py
More Information and Free Trial
Now you can build interactive Dash web apps on live Dynamics 365 data using the CData Connect AI Python SDK. For more information on connecting to Dynamics 365 (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Dynamics 365 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 GoalHeadingId, Name "
"FROM [Dynamics3651].[Dynamics365].[GoalHeadings] "
"WHERE Name = 'MyAccount'",
conn,
)
conn.close()
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['GoalHeadingId'], y=df['Name'], name='GoalHeadingId')
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='Dynamics 365 GoalHeadings Data', barmode='stack'),
},
),
],
className="container",
)
if __name__ == '__main__':
app.run(debug=True)