INTELLIGENCE
Archive
How to Set Up Julius AI for Data Analysis
Julius AI is a browser-based tool that lets you upload spreadsheets, CSVs, or connect a live database and analyze data through plain-English questions. It runs Python under the hood and returns charts, tables, and written summaries. The free plan is limited to 15 messages per month. Paid plans start at $35 per month and unlock faster models, larger file handling, and live database connectors.
How to Switch from Pandas to Polars for Faster Analysis
Polars is a DataFrame library built in Rust that processes CSV and tabular data significantly faster than Pandas, with benchmarks showing 2.5x to 11x speed improvements depending on the operation. This guide covers installing Polars, translating the most common Pandas operations into Polars syntax, and deciding when the switch makes sense based on dataset size and workflow needs.
How to Set Up Gumloop for AI Workflow Automation
Gumloop is a no-code platform for building AI-powered automation workflows using a visual drag-and-drop canvas. To get started, create a free account, select or build a workflow using the node editor, connect your integrations, configure an AI node with your preferred language model, and run the workflow. The free plan includes 5,000 credits per month and supports unlimited flows and agents with no coding required.
How to Set Up Polymer AI for Spreadsheet Dashboards
Polymer AI is a no-code business intelligence tool that converts spreadsheets and CSVs into interactive dashboards without writing code or SQL. You upload a file or connect Google Sheets, and Polymer automatically detects column types, suggests visualizations, and builds a filterable dashboard in under a minute. This guide walks through account setup, data import, dashboard creation, sharing options, and practical tips for getting clean results from messy spreadsheet data.
How to Set Up the DuckDB Local UI for CSV Analysis
DuckDB's local UI is a browser-based SQL notebook that runs entirely on your machine, letting you query CSV, Parquet, and JSON files with standard SQL and zero server setup. Install DuckDB v1.2.1 or later, run "duckdb -ui" in your terminal, and the interface opens automatically with syntax highlighting, autocomplete, and real-time result previews. Your data never leaves your computer unless you explicitly connect to a cloud service.
How to Use Google NotebookLM for Data Analysis
Google NotebookLM lets you upload CSVs, spreadsheets, and PDFs, then query them in plain English to generate structured data tables, spot trends, and cross-reference multiple sources. This tutorial walks through the full data analysis workflow, from uploading your first dataset to exporting findings, using features most guides overlook: custom instructions for analytical rigor, deep research for supplementary context, and multi-notebook queries via Gemini integration.
How to Set Up Rows AI for Spreadsheet Analysis
Rows is a cloud spreadsheet platform with a built-in AI Analyst that lets you clean, analyze, and visualize data using plain English prompts instead of formulas. You connect live data sources, ask questions like "average revenue by region," and get computed answers, new columns, and charts directly in the spreadsheet. Setup takes under five minutes with a free account, and the AI Analyst handles everything from sentiment analysis to predictive modeling without requiring any code.
How to Set Up Supermetrics AI for Marketing Reports
Supermetrics AI connects your marketing platforms to AI assistants like Claude, ChatGPT, and Gemini so you can query campaign data in plain English. Setup takes under ten minutes: connect your ad accounts through the Supermetrics Hub, enable the AI destination, and link your preferred assistant. The platform also offers a Model Context Protocol server for developers who want direct programmatic access to marketing data through AI agents.
How to Use Perplexity Deep Research for Data Analysis
Perplexity Deep Research can function as a data analysis assistant that gathers, cross-references, and synthesizes quantitative information from across the web. By structuring your prompts with specific metrics and constraints, you can extract market data, benchmark statistics, and trend figures into organized reports with full source citations. This tutorial walks through the complete workflow from query design to validated, export-ready data tables.