INTELLIGENCE
Guides
How-to guides and practical walkthroughs
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 a Databricks Genie Space
Databricks Genie is a natural language analytics interface built into the Databricks Lakehouse platform. Business users ask questions in plain English and Genie translates them into SQL, runs the query against Unity Catalog data, and returns results without requiring SQL knowledge. Setting up a Genie space requires Unity Catalog data registration, a pro or serverless SQL warehouse, and a knowledge store built with table descriptions, synonyms, example SQL queries, and join definitions.
How to Set Up Hex Notebook Agent for Analysis
Hex's Notebook Agent is an AI assistant built into data notebooks that writes SQL, runs Python, and generates charts from plain-English prompts. It connects to your existing data warehouse and uses your schema to produce queries that run against real tables. Setup involves three steps: connecting a warehouse, configuring what the agent can see, and adding a workspace context file that explains your business logic and key metric definitions.
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 Power BI Copilot for AI Reports
Power BI Copilot is Microsoft's built-in AI assistant that lets users ask questions about their data, generate DAX formulas, build report pages, and get written summaries from plain-English prompts. It requires a paid Fabric capacity at F2 or higher, or Power BI Premium P1 or higher. Setup involves enabling a tenant setting in the Fabric admin portal and preparing your semantic model with clear column names so Copilot returns accurate results.
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.