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# Introduction
N8N is an open source workflow automation platform that allows you to integrate applications, APIs and services using a visual, node-based interface. It helps automate data movement, system integration, and repetitive tasks without the need for complex code. N8N is widely used because it is flexible, supports self-hosting, integrates with hundreds of tools, and gives developers complete control over logic, execution, and data handling, making it a strong alternative to closed automation platforms.
In this article, we will learn about the top 7 N8N workflow templates for data science. These templates are plug-and-play, meaning you provide your data with either the Model API or the Database API. Everything else is already tried and tested, allowing you to focus on analysis, experimentation and results rather than building a workflow from scratch.
# 1. Automate Basic Stock Analysis with FanHub Data and Google Sheets (DCF Calculator)
Link to Template: Automate Basic Stock Analysis with FanHub Data and Google Sheets DCF Calculator N8N Workflow Template
This N8N workflow automates the most time-consuming parts of fundamental equity research by converting raw financial filings into institutional-grade analysis at no execution cost.
It pulls six years of annual and quarterly data from FanHub, cleans and structures financials, calculates trailing twelve-month figures, calculates three-year and five-year compound annual growth rates, and runs a fully discounted cash flow valuation to estimate intrinsic stock value.
All historical data, growth trends, and assessment results are automatically delivered to a connected Google Sheets dashboard with charts and tables that populate instantly for fast, objective analysis.
# 2. Automated stock technical analysis with Z-Growk and multi-channel notifications
Link to Template: Automated stock technical analysis with ZGrowk and multi-channel notifications N8N Workflow Template
This workflow is designed for stock traders, financial analysts, portfolio managers, and investment enthusiasts who want automated, data-driven stock market analysis without manual charting.
It runs daily to analyze selected stocks using technical indicators such as relative strength index and moving average convergence-divergence, generates clear buy, sell or stop signals, and augments results with AI-based interpretation and market news.
Insights are provided automatically via email, messaging apps, and Google Sheets logs, making it ideal for anyone who wants consistent trading signals, daily market summaries, and centralized tracking across multiple stocks.
# 3. Process OCR documents from Google Drive into a searchable knowledge base with OpenAI and Pincon
Link to Template: Process OCR documents from Google Drive into a searchable knowledge base with OpenAI and Pinecone N8N Workflow Template
This workflow automates a complete retrieval-enhanced generation ingestion pipeline for document indexing. When a new OCR JSON file is added to a Google Drive folder, it automatically extracts the lesson metadata, cleans and analyzes the Arabic text, divides the content into semantic segments, embeds AI, and stores them in the Pinecone vector index for retrieval.
Once the processing is complete, the file is moved to an archive folder to avoid disconnecting the copy. Setup is simple and requires connecting Google Drive, OpenIAI for embedding, and Pincon credentials, then configuring the input and archive folder paths before running the workflow.
# 4. Consolidate data from 5 sources for automated reporting with SQL, MongoDB and Google Tools
Link to Template: Consolidate data from 5 sources for automated reporting with SQL, MongoDB and Google Tools N8N Workflow Template
This workflow automatically consolidates data from Google Sheets, PostgreSQL, MongoDB, Microsoft SQL Server, and Google Analytics into a single master Google Sheet based on a schedule.
Each dataset is tagged with a unique source identifier to maintain traceability, then integrated, cleaned and ready for reporting and analysis in a standardized format.
The result is a centralized, always-up-to-date reporting hub that eliminates manual data collection, reduces cleaning effort, and provides a reliable foundation for business insights across multiple systems.
# 5. Automate data extraction with Zite AI (products, jobs, articles and more).
Link to Template: Automate Data Extraction with Zite AI (Products, Jobs, Articles & More) N8N Workflow Template
This workflow provides an automated AI-powered web scraping solution that extracts structured data from e-commerce sites, articles, job boards, and search engine results without the need for custom selectors.
Using the Zite API, it automatically detects page structure, handles pagination, retries errors, and crawls results through a two-stage crawling and scraping process to produce clean CSV exports even for large websites.
Users simply enter a target URL and select a scraping goal, while advanced logic directs the request to the correct extraction model. A manual mode is also available for users who prefer raw data output and custom parsing.
# 6. Customer feedback automation with sentiment analysis using GPT 4.1, Jira and Slack
Link to Template: Customer Feedback Automation with Sentiment Analysis using GPT-4.1, JIRA and Slack | N8N Workflow Template
This workflow automates the entire customer feedback lifecycle by collecting submissions via webhooks, validating data, and using OpenAI to analyze sentiment.
Negative feedback and feature requests are automatically converted to JIRA issues, while incorrect submissions trigger immediate Slack alerts for immediate action. In addition to real-time processing, the workflow generates a weekly summary of all feedback related Jira tickets related to OpenAI and delivers it on the fly, giving teams a clear view of user sentiment trends without manual reviews.
# 7. Real-time sales pipeline analytics with Bright Data, OpenAI, and Google Sheets
Link to Template: Real-Time Sales Pipeline Analytics with Bright Data, OpenAI, and Google Sheets | N8N Workflow Template
This workflow automatically monitors key sales pipeline metrics like new leads, deal stages, win rates, and closing opportunities to inform teams about revenue health.
It connects to your CRM on a schedule, analyzes pipeline data with OpenAI to detect risks and anomalies, sends actionable alerts and summaries on slow, and stores daily snapshots in Google Sheets for trend analysis. The result is a fully automated sales prospecting system that eliminates manual CRM exports and helps sales leaders, operations teams, and reps work faster and forecast more accurately.
# Final thoughts
N8N has thousands of templates that can automate almost any data science workflow. The key is knowing which ones are genuinely useful, easy to plug in, and proven in real use. The above seven templates are some of the most practical options for data science as they cover the complete pipeline from data collection to analysis.
You can use them as financial analysts, generate technical business insights, turn OCR documents into searchable knowledge bases, consolidate data from multiple databases for reporting, extract structured data from the web without building custom scrapers, analyze and track customer feedback with sentiment, and monitor sales pipelines in real time with alerts and dashboards.
If you want to move quickly without constantly rebuilding the same tooling, these workflows are a solid starting point. Connect your data source, add your model or database credentials, and start iterating on the logic. You’ll spend less time on setup and more time on results.
Abid Ali Owan For centuries.@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in Technology Management and a Bachelor’s degree in Telecommunication Engineering. His vision is to create an AI product using graph neural networks for students with mental illness.