INTELLIGENCE
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How to Get Started with Microsoft Fabric
Microsoft Fabric is Microsoft's unified analytics platform that combines data engineering, warehousing, real-time analytics, and Power BI in a single workspace. As of April 2026, Copilot is available on all paid F2-and-above SKUs, removing the previous F64 minimum requirement. Teams can ingest data from files or databases, run SQL queries, build pipelines, and create dashboards without switching tools. A free 60-day trial is available at app.fabric.microsoft.com.
How to Set Up RisingWave for Real-Time Analytics
RisingWave is a PostgreSQL-compatible streaming database that lets analysts define real-time materialized views using standard SQL. It replaces the traditional Kafka-plus-Flink streaming stack with a single system that ingests, transforms, and serves live data through any PostgreSQL client. This guide covers local installation, connecting a data source via PostgreSQL CDC or the built-in datagen connector, writing materialized views, and querying live results with zero new tooling beyond SQL you already know.
How to Get Started with Polars for Data Analysis
Polars is an open-source Python DataFrame library written in Rust that processes data 5-14x faster than pandas on most tasks. It reads CSVs roughly 5x faster and uses 87% less memory, with a multi-threaded engine that handles million-row files in seconds on a standard laptop. For analysts dealing with slow pandas notebooks or memory errors on large files, switching to Polars requires installing one package and learning a new expression-based API.
How to Use Julius AI for Data Analysis
Julius AI is a browser-based data analysis tool that lets analysts, ops managers, and founders upload a CSV, Excel file, or database connection and run statistical analysis and visualizations through plain-language prompts. It generates and executes Python or R code in the background, returning charts and summaries without requiring coding knowledge. The free plan provides 15 messages per month; the Plus plan at $35 per month removes most practical limits for individual use.
How to Set Up Ibis for Portable Python Analytics
Ibis is a portable Python analytics library that lets you write dataframe code once and run it against more than 24 backends -- including DuckDB, BigQuery, Snowflake, and Postgres -- without rewriting your analysis. Version 12.0.0, released in 2026, ships with DuckDB as a zero-config default, making it the fastest path from a local CSV file to production-grade analytical queries without touching a SQL string directly.
How to Analyze CSV Files with DuckDB
DuckDB is a free, serverless SQL database that runs on your laptop and queries CSV files directly with standard SQL. Install it in under two minutes, point it at any CSV, and run aggregation, filtering, and join queries on files that would crash Excel. There is no server to configure, no Python required, and no import step before querying. You run SQL against the raw file from the terminal.
How to Use Tableau Agent for Data Analysis
Tableau Agent is a conversational AI feature built into Tableau Desktop, Tableau Cloud, and Tableau Server (2025.3+) that lets you build visualizations, create calculated fields, and explore datasets using plain English. You type a question like "show me monthly revenue by region" and Tableau Agent generates the chart. It supports CSV, Excel, and Hyper file uploads, works with live database connections, and launched a Dashboard Narratives beta in February 2026 that summarizes insights across full dashboards. A free trial with full Tableau Agent access is available at tableau.com/products/trial.
How to Set Up Copilot in Excel for Data Analysis
Copilot in Excel requires three things before it works: a Microsoft 365 Copilot license ($30 per user per month add-on), the workbook saved to OneDrive or SharePoint, and data formatted as an Excel Table. Skip any one of those and Copilot either refuses to act or produces errors. This guide covers every setup step and shows how to run a complete analysis from a raw CSV to a finished chart using only natural language prompts.
How to Set Up Jupyter AI for Data Analysis
Jupyter AI is an open-source JupyterLab extension that connects AI models to your notebook environment. Install it with a single pip command, enter your OpenAI or Anthropic API key in settings, and use the %%ai magic command to generate analysis code, summarize results, and debug errors without leaving the notebook. This guide covers installation, model configuration, and three practical data analysis tasks you can run immediately.