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Explore your Databricks data through simple conversation

Swiftask turns your Databricks Lakehouse into a knowledge source accessible to everyone. Ask business questions, get instant answers.

Result:

Cut data discovery time from hours to seconds, without writing a single line of SQL.

Lakehouse complexity hinders data access

In Big Data architectures, finding the right table or metric is a challenge. Analysts spend valuable time navigating Unity Catalog or writing complex SQL queries for simple questions.

Main negative impacts:

  • Technical bottleneck: Business teams are constantly dependent on data engineers for basic extractions, creating significant delays.
  • Knowledge silos: Lack of documentation and opaque schemas prevent smooth data discovery across the organization.
  • Compliance risks: Unstructured access to sensitive data without clear governance exposes the company to security breaches.

Swiftask connects your AI agents directly to your Databricks catalogs. Through a conversational interface, your teams query data in natural language and get immediate, secure, and audited results.

BEFORE / AFTER

What changes with Swiftask

Without Swiftask

An analyst needs the customer retention rate. They search Databricks, identify multiple tables, ask an engineer to confirm the schema, write a SQL query, check the results. Process: 2 hours.

With Swiftask + Databricks

The analyst asks the Swiftask agent: 'What is the customer retention rate for the last quarter?'. The agent accesses the tables, calculates the result, and answers instantly. Process: 30 seconds.

Streamline your data access in 4 steps

STEP 1 : Connect Swiftask to Databricks

Configure the Databricks connector in Swiftask using your secure credentials and access to your Unity catalogs.

STEP 2 : Index your metadata

The AI agent analyzes the schemas and descriptions of your tables to understand the business context of your data.

STEP 3 : Ask your questions

Use the Swiftask chat to query your data. The AI translates your natural language into optimized queries.

STEP 4 : Visualize and share

Get answers as raw data or analytical summaries, shareable directly in your collaboration tools.

Intelligent exploration capabilities

The agent understands relationships between tables, data lineage, and business metadata to provide contextual answers.

  • Target connector: The agent performs the right actions in databricks based on event context.
  • Automated actions: Automatic SQL querying, metadata summarization, multi-catalog search, compliance verification, ad-hoc report generation.
  • Native governance: All queries are logged to ensure transparency and data access governance.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-databricks@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

Why choose Swiftask for Databricks

1. Data democratization

Enable your non-technical teams to access insights without knowing SQL.

2. Massive productivity gains

Drastically reduce the time spent by Data Teams on repetitive ad-hoc queries.

3. Enhanced security

Access control is respected at every step, ensuring only authorized users see sensitive data.

4. Unified governance

Benefit from full traceability on who queries what data and for what purpose.

5. Decision-making agility

Make decisions based on real-time data rather than static reports.

Secure architecture

Swiftask applies enterprise-grade security standards for your databricks automations.

  • RBAC compliance: Swiftask aligns with the role-based access control policies of Databricks Unity Catalog.
  • Encrypted communication: All communication between Swiftask and your Databricks instance is encrypted end-to-end.
  • Full audit trail: Every question asked and every data access is logged for your internal audits.
  • Zero data storage: Swiftask queries your data in real-time without duplicating or persistently storing it.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Measurable impact on your Data stack

MetricBeforeAfter
Discovery timeSeveral hoursA few seconds
IT ad-hoc queriesHigh volume80% reduction
Business autonomyLowFull on standard queries
Data reliabilityManual error riskStandardized by AI

Take action with databricks

Cut data discovery time from hours to seconds, without writing a single line of SQL.

Databricks Compliance Audit: Intelligent Automation

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