Photo produced by the Author
# Introduction
n8n is an open source workflow automation platform that allows you to connect applications, APIs, and services using an environment-based interface. It helps automate data movement, system integration, and repetitive tasks without requiring complex coding. n8n is widely used because it is flexible, supports self-hosting, includes hundreds of tools, and gives developers full control over logic, execution, and data management, making it a strong alternative to closed automation platforms.
In this article, we will learn about the top 7 n8n data science workflow templates. These templates are plug and play, meaning all you need to do is provide your data and model API or database API. Everything else has been tried and tested, allowing you to focus on analysis, testing, and results instead of building a workflow from scratch.
# 1. Basic fundamental analysis with FinnHub Data and Google Sheets (DCF Calculator)
Template link: Automate Basic Stock Analysis with FinnHub Data and Google Sheets DCF Calculator | n8n workflow template
This n8n workflow automates the time-consuming parts of basic equity research by converting raw investment into institutional grade analysis without transaction costs.
It pulls six years of annual and quarterly data from FinnHub, cleans and sorts the funds, calculates accurate figures for a Trailing Twelve Months, calculates three-year and five-year compound growth rates, and uses a fully discounted cash flow ratio to estimate the stock's intrinsic value.
All historical data, growth trends, and analysis results are automatically delivered to a connected Google Sheets dashboard with charts and tables that populate quickly for quick, targeted analysis.
# 2. Automated Analysis of Technical Stocks with xAI Grok & Multi-Channel Alerts
Template link: Automated Stock Technical Analysis with xAI Grok & Multi-Channel Alerts | 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 works daily to analyze selected stocks using technical indicators such as relative strength index and moving average variance, generates clear buy, sell, or hold signals, and improves results with AI-based interpretation and market news.
Data is delivered automatically via email, messaging apps, and a Google Sheets log, making it ideal for anyone looking for consistent trading signals, daily market summaries, and centralized tracking across multiple stocks.
# 3. Process OCR documents from Google Drive into a searchable database with OpenAI & Pinecone
Template link: Process OCR documents from Google Drive into a Searchable Knowledge Base with OpenAI & Pinecone | n8n workflow template
This workflow automatically performs a complete retrieval of the generational import line to index the document. When a new OCR JSON file is added to the Google Drive folder, it automatically extracts the subject metadata, cleans and parses the Arabic text, breaks the content into semantic chunks, generates an AI embedding, and stores it in a Pinecone vector index for retrieval.
Once processing is complete, the file is moved to an archive folder to prevent duplicate imports. Setup is simple and requires connecting Google Drive, OpenAI embeds, and Pinecone credentials, and configuring the installation paths and archive folder before running the workflow.
# 4. Aggregate Data From 5 Sources for Automated Reporting with SQL, MongoDB and Google Tools
Template link: Combine Data From 5 Sources for Automated Reporting with SQL, MongoDB and Google Tools | n8n workflow template
This workflow automatically merges data from Google Sheets, PostgreSQL, MongoDB, Microsoft SQL Server, and Google Analytics into a master Google Sheet on a scheduled basis.
Each dataset is tagged with a unique source identifier to maintain traceability, then aggregated, cleaned, and formatted into a consistent structure ready for reporting and analysis.
The result is a centralized, up-to-date reporting hub that eliminates manual data collection, reduces cleanup effort, and provides a reliable foundation of business insights across multiple systems.
# 5. Automate Data Extraction with Zyte AI (Products, Jobs, Articles & More)
Template link: Change Data Extraction with Zyte AI (Products, Jobs, Articles and more) | n8n workflow template
This workflow provides an AI-enabled web automation solution that extracts structured data from commerce sites, articles, job boards, and search engine results without requiring custom selectors.
Using the Zyte API, it automatically detects page layouts, captures browsing, retries errors, and aggregates 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 routes the request to the correct extraction model. A manual mode is also available for users who prefer raw data output and custom analysis.
# 6. Automating Customer Feedback with Sentiment Analysis using GPT-4.1, Jira & Slack
Template link: Customer Feedback Automated with Sentiment Analysis using GPT-4.1, Jira & Slack | n8n workflow template
This workflow automates the entire customer feedback lifecycle by collecting submissions via webhooks, validating data, and using OpenAI for sentiment analysis.
Negative feedback and feature requests are automatically converted into Jira issues, while invalid submissions trigger instant Slack notifications for immediate action. In addition to real-time processing, the workflow generates an OpenAI-enabled weekly summary of all feedback-related Jira tickets and delivers it to Slack, giving teams a clear view of customer sentiment trends without manual updates.
# 7. Real-Time Sales Pipeline Analytics with Light Data, OpenAI, and Google Sheets
Template link: Real-Time Sales Pipeline Analytics with Light Data, OpenAI, and Google Sheets | n8n workflow template
This workflow automatically monitors key sales metrics such as new leads, deal categories, win rates, and set opportunities to keep teams informed about revenue health.
It connects to your CRM with a scheduler, analyzes pipeline data with OpenAI to detect risks and anomalies, sends alerts and actionable summaries to Slack, and saves daily summaries to Google Sheets for trend analysis. The result is a fully automated sales visibility system that eliminates manual CRM deployments 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 to know which ones are really useful, easy to install, and proven to actually work. The seven templates listed above are some of the most practical options for data science because they cover the full pipeline, from data collection to analysis to delivery.
You can use them to automate financial analysis, generate technical trading information, turn OCR documents into searchable databases, aggregate data from multiple databases for reporting, extract structured data from the web without building custom scrapers, analyze customer feedback emotionally and extract leads, and monitor sales pipelines in real time with alerts and dashboards.
If you want to move quickly without rebuilding the same tools, this workflow is a solid start. Connect your data source, add your model or database information, and start iterating logically. You'll spend less time on setup and more time on results.
Abid Ali Awan (@1abidiawan) is a data science expert with a passion for building machine learning models. Currently, he specializes in content creation and technical blogging 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 idea is to create an AI product using a graph neural network for students with mental illness.
