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# Entry
n8n is an open-source workflow automation platform that enables you to connect applications, APIs, and services through a visual, node-based interface. It helps you automate data movement, system integration and repetitive tasks without the need for complicated code. n8n is widely used because it is malleable, self-hosted, integrates with hundreds of tools, and gives developers complete control over logic, execution, and data handling, making it a powerful alternative to closed automation platforms.
In this article, we will explore the 7 best n8n data analytics workflow templates. These templates are plug and play, which means you just need to provide the data along with the model API or database API. Everything else has already been tried and tested, so you can focus on analysis, experimentation, and results rather than creating workflows from scratch.
# 1. Automate basic stock analysis with FinnHub data and Google sheets (DCF calculator)
Link to template: Automate basic stock analysis with FinnHub data and the Google Sheets DCF calculator | n8n workflow template
This n8n workflow automates the most time-consuming parts of fundamental equity research, transforming raw financial statements into institutional-grade analysis with no execution costs.
It pulls six years of annual and quarterly data from FinnHub, cleans and organizes financial data, calculates right data for the last twelve months, calculates three- and five-year compound annual growth rates, and performs a full discounted cash flow valuation to estimate the intrinsic value of the stock.
All historical data, growth trends and valuation results are automatically delivered to a connected Google Sheets dashboard with charts and tables that are instantly populated for quick and objective analysis.
# 2. Automated stock technical analysis with xAI Grok and multi-channel notifications
Link to template: Automated stock technical analysis with xAI Grok and multi-channel notifications | n8n workflow template
This workflow is designed for stock traders, financial analysts, portfolio managers and investing enthusiasts who want automated, data-driven stock market analysis without the need for manual charting.
It analyzes selected stocks daily with technical indicators such as the Relative Strength Index and Moving Average Divergence, generates clear buy, sell or hold signals, and improves performance with AI-powered interpretation and market news.
Statistics are automatically delivered via email, instant messaging and Google Sheets, making it ideal for anyone who needs consistent trading signals, daily market summaries and centralized tracking of multiple stocks.
# 3. Turn OCR documents from Google Drive into a searchable knowledge base with OpenAI and Pinecone
Link to template: OCR documents from Google Drive into a searchable knowledge base with OpenAI and Pinecone | n8n workflow template
This workflow automates the full retrieval ingestion pipeline with extended generation for document indexing. When you add a modern OCR JSON file to a folder in Google Drive, it automatically extracts lesson metadata, cleans and parses Arabic text, splits the content into semantic fragments, generates AI embeddings, and stores them in Pinecone’s vector index for retrieval.
Once processing is complete, the file is moved to the archive folder to prevent duplication. Setup is plain and requires connecting Google Drive, OpenAI for embedding and Pinecone credentials, and then setting up input and archive folder paths before running the workflow.
# 4. Consolidate data from 5 sources for automatic 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 one master Google Sheet on a schedule.
Each data set is tagged with a unique source identifier to ensure traceability, then combined, cleansed and standardized into a consistent structure ready for reporting and analysis.
The result is a centralized, always-up-to-date reporting hub that eliminates manual data collection, reduces cleanup efforts, and provides a reliable foundation for business insights across multiple systems.
# 5. Automate data extraction with Zyte AI (products, jobs, articles and more)
Link to template: Automate data extraction with Zyte AI (products, jobs, articles and 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 Zyte API, it automatically detects page structure, handles pagination, retries errors, and aggregates results in a two-phase indexing and scraping process to achieve pristine CSV exports even for huge sites.
Users simply enter the target URL and select a scraping target, and advanced logic routes the request to the correct extraction model. Manual mode is also available for users who prefer raw data output and custom analysis.
# 6. Automation of customer reviews with sentiment analysis using GPT-4.1, Jira and Slack
Link to template: Automate customer feedback with sentiment analysis using GPT-4.1, Jira and Slack | n8n workflow template
This workflow automates the entire customer feedback lifecycle by collecting tickets via webhook, validating data, and using OpenAI for sentiment analysis.
Negative feedback and feature requests are automatically turned into Jira tickets, and invalid tickets trigger instant Slack alerts for quick action. In addition to real-time processing, the workflow generates a weekly summary of all OpenAI-powered Jira tickets and delivers them to Slack, giving teams a clear picture of customer sentiment trends without the need for manual review.
# 7. Real-time sales pipeline analysis using Glowing Data, OpenAI and Google Sheets
Link to template: Real-time sales pipeline analysis with Bright Data, OpenAI and Google Sheets | n8n workflow template
This workflow automatically monitors key sales pipeline metrics such as modern leads, deal stages, win rates, and blocked opportunities to keep teams informed about revenue health.
It connects to your CRM system on a schedule, analyzes pipeline data with OpenAI to detect threats and anomalies, sends actionable alerts and summaries to Slack, and stores daily snapshots in Google Sheets to analyze trends. The result is a fully automated sales visibility system that eliminates manual CRM exports and helps sales leaders, operations teams and reps act faster and forecast more accurately.
# Final thoughts
n8n offers thousands of templates that can automate almost any data analytics workflow. The key is to know which ones are really useful, straightforward to connect and proven in real-world apply. The seven templates listed above are some of the most practical data analysis options because they cover the entire process, from data collection to analysis to delivery.
They can be used to automate financial analysis, generate technical commercial insights, transform OCR documents into searchable knowledge bases, consolidate data from multiple databases for reporting, extract structured data from the Internet without creating custom scrapers, analyze customer feedback with sentiment and issue tracking, and monitor sales pipelines in real time with alerts and dashboards.
If you want to move faster without constantly rebuilding the same tools, these workflows are a good place to start. Connect your data source, add model or database credentials, and start iterating your logic. You’ll spend less time on setup and more time on results.
Abid Ali Awan (@1abidaliawan) is a certified data science professional who loves building machine learning models. Currently, he focuses on creating content and writing technical blogs about machine learning and data science technologies. Abid holds a Master’s degree in Technology Management and a Bachelor’s degree in Telecommunications Engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.