Better Analyst is an all-in-one analytics application for individuals, small businesses, and growing teams. It connects data sources, supports analysis and enrichment, creates dashboards and reports, and automates recurring workflows.
Better Analyst is an all-in-one analytics workspace for preparing data, asking questions, creating visualizations and dashboards, producing reports and presentations, and automating recurring analysis. It is aimed at individuals, small businesses, and growing teams that need to work with business data without maintaining a separate collection of preparation, BI, reporting, and automation tools.
The application connects to databases, analytics services, business apps, cloud files, spreadsheets, documents, and uploaded files. Users can combine sources, clean and reshape data, enrich it with operations such as sentiment analysis or text extraction, and export results into formats including Excel workbooks and reports.
Better Analyst also supports reusable AI agents and scheduled Tasks. A saved Task can run a defined sequence of analysis steps on current data, on demand or on a daily, weekly, or monthly schedule, with a history of runs, results, and errors. Dashboards can be generated from natural-language descriptions, customized, and refreshed automatically.
Connect analytics services, databases, warehouses, cloud storage, spreadsheets, documents, and uploaded files in one workspace. The site lists sources including GA4, Google Search Console, Airtable, BigQuery, Snowflake, MySQL, PostgreSQL, Supabase, Excel, PDF, and CSV.
Clean, standardize, merge, reshape, and organize raw data into analysis-ready datasets. Enrichment options include sentiment analysis, language translation, and extracting structured information from unstructured text.
Ask questions about connected data and generate analysis, charts, or other outputs. Better Analyst shows generated Python, SQL, or R code so users can review, learn from, or export the underlying work.
Describe a dashboard in natural language to generate an interactive starting point, then customize its appearance and schedule refreshes. Results can also be exported to Excel and turned into formatted reports or presentations.
Save proven analysis workflows as Tasks and run them manually or on daily, weekly, or monthly schedules. Multi-step runs can pull data, calculate metrics, generate visualizations, and export results while retaining execution history.
Add business definitions, metrics, and context files to guide AI responses; use Brand Kits to keep colors, typography, number formats, and artifact styling consistent; or add AI-powered analytics chat to a website through an iframe.
Save a workflow that pulls current data, calculates metrics, creates visualizations, and exports a report. Schedule it daily, weekly, or monthly and review each run through its history.
Combine data from applications, databases, spreadsheets, or files, then clean and reshape it before analysis. This is suited to teams that need a repeatable preparation step before reporting or decision-making.
Use sentiment detection, translation, or text extraction to process customer reviews and other unstructured text, then incorporate the results into broader analysis.
Describe the information an audience needs, generate an interactive dashboard, customize its presentation, and turn findings into reports or presentation-ready outputs.
Add branded analytics chat to a website with an iframe, or use the Slack integration in beta to request answers, charts, and files in channels or direct messages.
The site lists analytics services, databases, warehouses, cloud storage, spreadsheets, documents, and uploaded files. Examples include GA4, Google Search Console, Airtable, BigQuery, Snowflake, MySQL, PostgreSQL, Supabase, Excel, PDF, and CSV.
Yes. Save a working analysis as a Task, attach files or connected data sources, and run it manually or on a daily, weekly, or monthly schedule. The documentation says scheduled daily runs are available on paid plans; weekly and monthly schedules are also supported.
Task history records when an execution ran, whether it succeeded or failed, the results generated, and any error messages. A Task can contain multiple steps and use one or more agents.
The product page says it displays the exact Python, SQL, or R code generated for requests. Users can review, learn from, and export that code.
The company says data is encrypted in transit and at rest, chats run in dedicated isolated sandboxes, row-level security can be applied to database connections, and customer data is not used to train AI models.
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