INTELLIGENCE
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How to Set Up DuckLake for Your Data Lake
DuckLake is an open table format released in April 2026 that stores lakehouse metadata in a SQL database instead of thousands of JSON and Avro files. To set it up, install the ducklake DuckDB extension, attach a local catalog file for testing, then swap to PostgreSQL and S3 for production. The result is a multi-user, ACID-compliant data lake with time travel and branching, running on infrastructure most teams already have.
How to Build Dashboards with Rill Developer
Rill Developer is a free, open-source BI tool that turns CSV files, Parquet files, or cloud data sources into interactive dashboards without requiring a database server or SQL expertise. You install it with one command, point it at your data, and use its built-in AI to generate a metrics view and Explore dashboard in under five minutes. Rill runs locally using DuckDB as its embedded engine, meaning there is nothing to configure or host before you start.
How to Set Up Notion Dashboard Views
Notion Dashboard Views, released in March 2026, let you add charts, KPI cards, and progress bars directly on top of any Notion database. You add a Dashboard view to an existing database, choose which properties to visualize, and arrange widgets on a free-form canvas. Notion AI can suggest chart types from your property names and types automatically. Setup takes under 15 minutes. No external BI tool is required.
How to Get Started with ThoughtSpot
ThoughtSpot is a cloud-based analytics platform that lets you query any connected data warehouse using plain English, without writing SQL. To get started, sign up for a free trial at thoughtspot.com, connect a data source (CSV, Google Sheets, or a cloud warehouse like Snowflake or BigQuery), and use Spotter AI to ask questions in natural language. Setup takes under 30 minutes and requires no SQL or coding knowledge.
How to Get Started with Hex AI Analytics
Hex is a collaborative analytics platform that combines SQL notebooks, Python, and a drag-and-drop app builder in a single browser-based workspace. Its Notebook Agent, built on Claude Sonnet 4, generates queries, builds charts, and drafts full analyses from plain-English prompts. Teams connect directly to warehouses like Snowflake and BigQuery or upload CSV files, then publish finished notebooks as shareable interactive apps without writing deployment code.
How to Analyze CSV Data with AI
Analyzing a CSV file with AI means uploading the file to a platform, describing your question in plain English, and letting the tool handle column detection, data cleaning, statistical method selection, and chart generation automatically. No Python or SQL is required. Most AI CSV tools return labeled charts and written summaries within seconds, and support analysis types including correlation, regression, clustering, and time-series forecasting.
How to Analyze Data Faster with Polars
Polars is a Python DataFrame library written in Rust that reads and processes tabular data 5 to 10 times faster than pandas on datasets over 100MB. It installs with a single pip command, accepts the same CSV and Parquet files you already work with, and handles filtering, grouping, and aggregation with a clear expression syntax. Analysts migrating from pandas can run most everyday tasks with minimal changes to their existing workflow.
How to Set Up Copilot in Power BI
Copilot in Power BI is Microsoft's generative AI assistant that creates report pages, writes DAX formulas, and produces natural-language summaries from your data using plain English prompts. As of 2025, Copilot is available on any Microsoft Fabric capacity at F2 or above, or Power BI Premium at P1 or above. This guide walks through enabling Copilot at the tenant and workspace level, then covers the practical prompts that produce reliable output for analysts, ops managers, and business users who do not write code.
How to Get Started with Apache Superset
Apache Superset is an open-source business intelligence platform that lets analysts and operations managers build interactive dashboards and explore data without writing code. Released as version 6.0 in December 2025, it connects to dozens of databases including PostgreSQL, MySQL, BigQuery, and Snowflake. You install it locally with Docker Compose, connect a data source, and start building charts in under 30 minutes. Over 1,000 organizations run Superset in production, from startups to large enterprises.