Why This Matters

Teams don’t struggle because they lack data.

They struggle because they lack a way to reach it meaningfully.

• Engineers know the tables
• Analysts know the joins
• Business users know the questions
• Executives know the outcomes

But the path between question and answer feels painfully long.

Chat QnA removes that friction with:

• Natural language access
• Context-aware understanding
• Visualisations on demand
• Clear citations for every answer
• Governed access across all data sources

Insight becomes a dialogue, not a ticket.

The Problem: Data Is Fragmented. Insight Shouldn’t Be.

Modern data estates are powerful but complex.

• Dozens of schemas and hundreds of tables
• Relationships hidden behind joins and keys
• Business terms that don’t map to column names
• Users are asking questions that require data stitching
• Multiple storage systems across the estate

The result:

• Slow responses
• Repetitive requests
• Confusion over definitions
• Dependence on engineers for simple insight

Data fragmentation is the enemy of clarity. Chat QnA closes the gap.

The Hidden Bottleneck: “Where Does That Data Live?”

Before a business user can ask a question, they quietly worry:

• Which table has this?
• How do these datasets connect?
• What does the column actually mean?
• Is this from CRM or ERP?
• Do I need SQL for this?

This cognitive overhead kills analytics adoption.

Chat QnA’s assumptions engine eliminates the guesswork by mapping schemas, keys, joins, synonyms, lexicons, and business rules automatically.

It creates an intelligent mesh of your entire data estate, so users simply ask… and get answers.

Why Chat QnA Solves the Last-Mile Problem

BI tools show great metrics.

But people still need a way to ask follow-ups.

Traditional dashboards can’t handle:

• Exploratory questions
• “What if?” scenarios
• Business terminology
• Complex relationships across systems

Chat QnA provides:

• Conversational access
• Charts rendered instantly
• Citations pointing back to the source
• Safe, governed queries across all systems

The user gets a clean, accurate answer without knowing schemas or SQL.

How It Works

Once connected to your data, the accelerator:

1. Scans your estate — reading schemas, inferring joins, exploring patterns
2. Learns your business language — terminology, acronyms, domain rules
3. Builds the knowledge graph — the “assumptions engine” maps relationships
4. Presents a secure chat interface — ask anything, with permission boundaries enforced
5. Delivers answers + charts — supported by citations and explanations
6. Sources everything through governance — Unity Catalog controls access and lineage

Every response is explainable, auditable, and linked to trusted data.

Powered by Databricks + Azure AI

Chat QnA doesn’t need a perfect data warehouse — it makes the warehouse smarter.

See It in Action

Security and Governance

Chat QnA only answers using data the user has permission to see.

• Unity Catalog-managed access
• All queries auditable
• PII-aware response filtering
• No data extraction or duplication
• Fully governed semantic mappings

Everything stays inside your compliance perimeter.

Business Impact You Can Measure

The right answer, every time, for every user.

Start Small. Scale Everywhere.

We typically launch Chat QnA in 3–6 weeks:

1. Connect a few key datasets
2. Train the assumptions engine
3. Define business lexicon and rules
4. Deploy chat interface to pilot users
5. Expand across new systems and domains

Each new dataset and team makes the system smarter.

Ask Better Questions. Get Better Answers.

With Chat QnA, every user becomes data-capable.

Every question becomes insight.

Every insight reinforces trust.

📩 Contact us for more infomation and demos.