Table of Contents

• Pre-Configured Reports Get You Far
• Ad-Hoc Analysis — Powerful but Demanding
• AI Takes Data Exploration Further
• What About Data Privacy?
• Next Steps

Pre-Configured Reports Get You Far

Pivot tables, dashboards, OLAP cubes — these are powerful tools for analyzing business data and they deliver tremendous value. But at some point you want to go deeper — ask a question nobody anticipated, slice the data from a new angle, or explore a hunch. Pre-configured views, by definition, can only show what was planned in advance.

Ad-Hoc Analysis — Powerful but Demanding

Ad-hoc analysis opens the door to those unplanned questions. In practice, though, it comes with its own challenge: where do you start?

A typical enterprise database has hundreds of tables. Which ones matter? Which columns hold the answers you need? Once you find the right tables, there are dozens of ways to slice the same data — some more revealing than others depending on the context. Switching between views, trying different angles, iterating quickly — this is where even skilled analysts slow down.

AI Takes Data Exploration Further

AI is a natural complement to the tools you already use. Instead of building queries manually, you ask questions in plain English and get answers — SQL, charts, and insights — instantly.

More importantly, AI handles the open-ended questions that go beyond what any dashboard can anticipate:

• "Which tables in my database are most relevant to sales performance?"
• "Show me revenue trends by region — and suggest a better way to visualize this."
• "You've seen thousands of CRM databases. What queries do people usually find valuable for a schema like mine?"

AI brings pattern recognition across industries and domains. You bring the context of your specific situation. Together, you reach useful insights faster than either could alone.

What About Data Privacy?

AI-powered analysis sounds compelling — but does it mean handing your data to an AI vendor? Your most valuable data — the data you most want to analyze — is often the data you least want to share.

ReportBurster was designed with this tension in mind. When you use AI for data exploration, your data is not sent to the AI vendor. The AI works with your database schema and metadata — not with the actual data rows.

For the full explanation, read

Few Notes on AI Usage within ReportBurster & Data Privacy

Next Steps

• Database Connections — connect to your database, explore the schema, generate ER diagrams, and build a shared understanding of your data model
• Chat2DB AI — ask questions about your data in plain English and get SQL, charts, and insights