Oracle Eloqua Reporting Python Connector

SQL-based access to Oracle Eloqua Reporting from Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with Oracle Eloqua Reporting!

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Python Connector Libraries for Oracle Eloqua Reporting Data Connectivity. Integrate Oracle Eloqua Reporting with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Oracle Eloqua Reporting data with Python and any Python-based applications.

Features

Powerful metadata querying enables SQL-like access to non-database sources
Push down query optimization pushes SQL operations down to the server whenever possible, increasing performance
Client-side query execution engine, supports SQL-92 operations that are not available server-side
Connect to live Oracle Eloqua Reporting data, for real-time data access with the Oracle Eloqua Reporting Python Connectors
Full support for data aggregation and complex JOINs in SQL queries
Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Oracle Eloqua Reporting Connector.

Specifications

Python Database API (DB-API) Modules for Oracle Eloqua Reporting .
Write SQL, get Oracle Eloqua Reporting data. Access Oracle Eloqua Reporting through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Full Unicode support for data, parameter, & metadata.

CData Python connectors in action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

Watch the Python Connector Video Overview

Python connectivity with Oracle Eloqua Reporting

Full-featured and consistent SQL access to any supported data source through Python


Connecting to Oracle Eloqua Reporting with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Oracle Eloqua Reporting from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to Oracle Eloqua Reporting
  • Query Oracle Eloqua Reporting to retrieve or update data
  • Connect your Oracle Eloqua Reporting data with Python data tools.


Connecting to Oracle Eloqua Reporting in Python

To connect to your data from Python, import the extension and create a connection:

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

import cdata.oracleeloquareporting as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM AccountActivities")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("oracleeloquareporting///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM AccountActivities", engine)

df.plot()
plt.show()

Visualize Oracle Eloqua Reporting Data with pandas

The data-centric interfaces of the Oracle Eloqua Reporting Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

AI-assisted development with CData CLI

Build Oracle Eloqua Reporting integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Oracle Eloqua Reporting schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Oracle Eloqua Reporting.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI