Data activation goes beyond traditional BI – it’s about making your business more data-driven, automating processes, and increasing productivity.
Peliqan’s low-code Python data apps combine SQL and Python to unlock powerful automation, integrations, and interactive applications.
Activate data in your data warehouse (Snowflake, BigQuery, Redshift, Peliqan DW) using a combination of SQL and low-code Python. Write, test, and run scripts directly in Peliqan’s built-in IDE and runtime, or develop locally with pip install Peliqan.
Write, test, and run Python scripts directly in Peliqan – schedule runs, view logs, and publish apps without any local setup or infrastructure management.
Install pip install peliqan to develop locally in your favorite IDE, then deploy to Peliqan’s cloud runtime – seamlessly switch between local development and cloud execution.
Demo
Learn about low-code Python Data Apps, covering their use cases for automation, custom data pipelines, and API endpoints, as well as features like Streamlit UI, scheduling, versioning, and built-in dwh functions.
Move data seamlessly between systems with automated integration pipelines and one-time migrations. Whether you’re migrating from legacy systems or syncing data between modern SaaS applications, Peliqan handles complex transformations and validations.
Migrate historical data from legacy ERP, CRM, or custom databases into modern cloud systems- handle schema mapping, data validation, deduplication, and transformation with low-code Python.
Build bi-directional integrations between business applications using 250+ connectors – sync customers, orders, invoices, and inventory across systems with custom mapping and business logic.
Give internal teams governed self-service access to the data they need – and share curated datasets, live feeds, and reports with external partners and customers through a branded portal, APIs, or custom delivery pipelines.
Expose any dataset as a REST API endpoint or MCP server. Partners and AI tools pull live data directly, with authentication and rate limiting built in.
Provision a managed data warehouse for each partner. They get their own Peliqan DWH or bring their own — you control what flows in.
Spin up isolated sub-accounts per partner or customer. Manage permissions, pipelines, and a satellite data warehouse independently for each.
Push data to each partner the way they need it: API sync, SFTP file drop, cloud storage, Excel export, BI connector, or ERP writeback.
From automated reports to intelligent chatbots, Peliqan’s Python data apps unlock limitless possibilities. Build exactly what your business needs – whether it’s interactive dashboards, API endpoints, or custom integrations – all with low-code simplicity.
Build personalized reports in Excel or Google Sheets with dynamic data from your warehouse.
Distribute them automatically via email, SFTP, or cloud storage like Google Drive, OneDrive, and Sharepoint.
Schedule daily, weekly, or trigger-based delivery to keep stakeholders informed.
Create web-based forms and interfaces for data entry or data access using Streamlit.
Build dashboards with filters, charts, and real-time data updates that business users can interact with.
Deploy self-service tools that eliminate manual data requests and empower teams.
Automate data-related processes like file imports at scale, data quality checks, and business alerts on Slack or Teams.
Set up scheduled data syncs and custom workflows triggered by data changes.
Eliminate repetitive manual tasks and ensure data operations run reliably 24/7.
Implement LLM chatbots based on your internal company data for natural language interaction.
Enable Text-to-SQL queries and RAG (retrieval-augmented generation) on business information.
Let users ask questions in plain English and get instant answers from your data warehouse.
Publish REST APIs with selected datasets for data sharing with partners & customers.
Handle custom logic in API endpoints with low-code Python to validate, transform, or enrich data.
Serve data using JSON or any format with authentication and rate limiting built-in.
Sync data between business applications or from your warehouse to SaaS tools using bi-directional flows.
Use our connectors with custom transformation logic for complex mapping and business rules.
Keep all your systems in sync automatically with scheduled or real-time updates.
Peliqan’s specialized Python functions turn complex data operations into simple one-liners. Access your entire data platform through code – pipelines, warehouses, APIs, and business applications.
Create buttons, tables, and charts with Streamlit – build rich, interactive user interfaces in minutes.
Enable data entry forms, dynamic visualizations, and real-time dashboards without frontend expertise.
st.button('Click me')
st.table(dataframe)
st.chart(data)Access any table in your data warehouse instantly with dbconn.fetch() – retrieve data as a Pandas DataFrame with a single function call.
Work with your data locally, apply transformations, and seamlessly integrate with any Python library or workflow.
df = dbconn.fetch('table_name')Trigger and manage data pipelines from code with pq.run_pipeline() – automate your data workflows with full programmatic control.
Schedule runs, chain multiple pipelines together, and handle complex orchestration logic without leaving your Python environment.
pq.run_pipeline('pipeline_name')Write data to any table with dbconn.write() – a single function that has the power of a full-blown ELT pipeline.
Handle upserts, schema changes, and incremental loads automatically without complex configuration.
dbconn.write(dataframe, 'table_name')Peliqan provides specialized Python modules that turn complex data operations into simple one-liners. Access your entire data platform through code – pipelines, warehouses, APIs, and business applications – all with unified syntax.
The peliqan module gives you programmatic access to pipeline automation, data warehouse operations, metadata management, and all Peliqan platform capabilities.
Build interactive apps and dashboards instantly using Streamlit – create forms, charts, filters, and data entry interfaces with just a few lines of Python.
Write data to any table with dbconn.write() – a single function that has the power of a full-blown ELT pipeline. Handle upserts, schema changes, and incremental loads automatically without complex configuration.
Write from Pandas DataFrames, API responses, or CSV files to your warehouse, databases, or business applications – the function handles all the complexity.
Use dbconn.write(dataframe, ‘table_name’) to intelligently write data with automatic schema detection, type conversion, and incremental updates.
Push data from your warehouse back into business applications with simple one-line functions. Create invoices in your ERP, update CRM records, or sync data to marketing tools – all from Python.
Create a draft invoice in your ERP with one line: connector.create(‘invoices’, {‘customer_id’: ‘123’, ‘amount’: 1000, ‘status’: ‘draft’})
Push new leads into your CRM instantly: salesforce.create(‘Lead’, {‘FirstName’: ‘John’, ‘LastName’: ‘Doe’, ‘Company’: ‘Acme Inc’, ‘Email’: ‘[john@acme.com](mailto:john@acme.com)’})
Peliqan’s AI assistant writes Python code for you. Describe what you want in plain English, and the AI generates the data app, complete with data access, transformations, and writebacks.
Ask “Create a script to sync new customers from Salesforce to my accounting system” and watch the AI write the entire Python script with proper error handling
The AI explains the code it generates, helping you understand Python and Peliqan functions – perfect for non-developers building their first data apps.
Get the right data to the right people. Go beyond static dashboards to truly empower your team.
Push personalized data updates (tables, charts) to channels and people in Slack or Teams.
Generate and distribute personalized PDF and Excel reports at scale. Use the Peliqan Excel add-in for real-time updates.
Build custom forms for data entry and retrieval. Implement AI Chatbots based on your company data.
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Combine SQL and low-code Python to implement your data use case fast