Use Dash to Build Web Apps on Adobe Analytics 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 Adobe Analytics-connected web applications for Adobe Analytics data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Adobe Analytics 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.

Connect to Adobe Analytics in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Adobe Analytics" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Adobe Analytics.

   Adobe Analytics uses the OAuth authentication standard. To authenticate using OAuth, create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the "Getting Started" section of the help documentation for a guide.

   Retrieving GlobalCompanyId

   GlobalCompanyId is a required connection property. If you do not know your Global Company ID, you can find it in the request URL for the users/me endpoint on the Swagger UI. After logging into the Swagger UI Url, expand the users endpoint and then click the GET users/me button. Click the Try it out and Execute buttons. Note your Global Company ID shown in the Request URL immediately preceding the users/me endpoint.

   Retrieving Report Suite Id

   Report Suite ID (RSID) is also a required connection property. In the Adobe Analytics UI, navigate to Admin -> Report Suites and you will get a list of your report suites along with their identifiers next to the name.

   After setting the GlobalCompanyId, RSID and OAuth connection properties, you are ready to connect to Adobe Analytics.

   
4. Click Save & Test
5. 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.

1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. 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 Adobe Analytics 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 Adobe Analytics data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, AdobeAnalytics1).

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 Page, PageViews "
    "FROM [AdobeAnalytics1].[AdobeAnalytics].[AdsReport] "
    "WHERE City = 'Chapel Hill'",
    conn,
)

conn.close()

Configure the App and Layout

With the query results stored in a DataFrame, build a bar graph from the Adobe Analytics data and configure the app layout.

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

trace = go.Bar(x=df['Page'], y=df['PageViews'], name='Page')

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='Adobe Analytics AdsReport 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 Adobe Analytics data.

python adobeanalytics-dash.py

More Information and Free Trial

Now you can build interactive Dash web apps on live Adobe Analytics data using the CData Connect AI Python SDK. For more information on connecting to Adobe Analytics (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Adobe Analytics 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 Page, PageViews "
    "FROM [AdobeAnalytics1].[AdobeAnalytics].[AdsReport] "
    "WHERE City = 'Chapel Hill'",
    conn,
)

conn.close()

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

trace = go.Bar(x=df['Page'], y=df['PageViews'], name='Page')

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='Adobe Analytics AdsReport Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

if __name__ == '__main__':
    app.run(debug=True)