INTELLIGENCE
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How to Build Reports with Power BI Copilot
Power BI Copilot lets analysts and business users build complete report pages from plain English prompts, without writing DAX or configuring visuals manually. It works within Power BI service and Desktop, requires a paid Fabric capacity (F2 or higher), and performs best when the underlying semantic model has clean column names and field descriptions. Copilot handles chart selection, layout, and narrative summaries, but accurate output depends heavily on how well the data model is prepared before use.
How to Use Julius AI for Data Analysis
Julius AI is a browser-based data analysis tool that accepts CSV, Excel, PDF, and other file formats and answers questions about your data in plain English. Users upload a file, type a question, and receive charts, statistical summaries, or cleaned datasets within seconds. The platform supports regression, t-tests, ANOVA, and custom visualizations without any coding. A free tier offers 15 messages per month; the Pro plan costs $37 per month billed annually.
How to Use Hex Notebook Agent for Analysis
Hex's Notebook Agent lets analysts run SQL queries, generate Python code, and build charts from plain English prompts inside a shared notebook. Available in beta on all Hex paid plans since August 2025, it connects directly to your data warehouse, understands your schema, and can create cells across multiple types without manual coding. This guide walks through setup, effective prompting, and a real analysis workflow from start to finish.
How to Set Up Airtable AI for Structured Data
Airtable's "Generate structured data" automation action lets you define an output schema so AI extracts consistent, typed fields from unstructured text, PDFs, or form submissions. This tutorial walks through creating the automation trigger, configuring the JSON schema, mapping outputs to Airtable fields, and testing the pipeline. All Airtable plans include AI credits, starting at 500 per month on Free.
How to Analyze CSV Files with DuckDB
DuckDB is an in-process SQL database that lets you query CSV files directly with standard SQL, without installing a database server or loading data into a separate tool. You can run it from the command line or inside a Python script, and it handles files of several gigabytes without significant setup. This guide walks through installing DuckDB, querying CSVs, running aggregations and window functions, and exporting results, covering the steps that most beginner tutorials skip.
How to Use Google Colab Data Science Agent
Google Colab's Data Science Agent is a free Gemini-powered tool that generates complete Python notebooks from a plain-English prompt and an uploaded CSV. You describe what you want to analyze, the agent writes the code, runs it, and returns charts and statistical summaries. It works best with structured tabular data and clear analysis goals. As of April 2026, it is available to all Colab users age 18 and older in supported regions.
How to Set Up Sigma Computing AI Query
Sigma Computing AI Query lets you call warehouse AI models directly from a spreadsheet formula bar, returning classifications, translations, summaries, and sentiment scores into new columns without writing Python or moving data. You connect your Snowflake, Databricks, or BigQuery warehouse, enable AI functions, then use passthrough formulas like CallText to run models on live data. Sigma crossed $200M ARR in April 2026, with AI Query among its fastest-adopted features.
How to Create Interactive Charts with Datawrapper
Datawrapper is a free, browser-based tool that turns raw data into interactive charts, maps, and tables in four steps without writing any code. You paste or upload your data, pick a chart type, customize colors and labels, then publish an embed link or PNG export. Over 40,000 organizations use it, including Reuters, the BBC, and the UN. This tutorial walks through each step with practical examples for business reporting.
How to Set Up Datadog Experiments for A/B Testing
Datadog Experiments is a new product that lets teams run A/B tests inside the Datadog platform, connecting product changes directly to business metrics stored in their data warehouse. It launched in general availability on April 2, 2026, built on technology from Datadog's acquisition of Eppo. This guide walks through the full setup process, from configuring data sources to launching your first experiment with feature flags and guardrail metrics.