Studio

Studio is both the web management console for Singdata Lakehouse and a serverless data services platform. The data sync jobs, SQL scheduling tasks, and Python scripts you configure in the UI are automatically executed by Singdata-managed serverless infrastructure — no compute resources to manage. Data engineers, analysts, and administrators can handle the full pipeline from data ingestion to data consumption in a single interface, without switching between tools.

Data Agent — AI Assistant

Studio has a built-in Data Agent — a fully AI-driven interaction layer built on top of Lakehouse, covering the full lifecycle of development, operations, and governance. You can tell the Agent what to do in natural language, and it operates the platform on your behalf — shifting from "person operates platform" to "person directs Agent."

Typical use cases:

ETL development assistance: Describe your data processing requirements, and the Agent generates SQL tasks and configures scheduling
Natural language data retrieval: Ask "What are the order amounts by region for the last 7 days?" and the Agent translates it to SQL and returns results
Day-to-day operations Q&A: Ask "Which tasks are currently failing?" and the Agent queries and provides remediation suggestions
Data insight generation: Upload data or specify a table, and the Agent automatically generates an analysis report

💡 Tip: Click "Data Agent" at the top of the menu bar to launch this feature. See Data Agent for details.

💡 AI Agent integration: If you are building your own AI Agent or automation pipeline, you can programmatically invoke Studio capabilities via cz-cli — cz-cli is the command-line interface for AI Agents to control Lakehouse & Studio, covering all major Studio modules.

Six Core Modules

Data Sync
Visually configure real-time CDC sync and offline batch sync for 40+ data sources — no code required. Supports MySQL, PostgreSQL, Oracle, Kafka, and other mainstream sources.

→ Data Sync Overview

Task Development (IDE)
Built-in SQL / Python / Shell editors with support for composite tasks, loop tasks, and conditional branching — develop your data transformation logic end-to-end in one place.

→ Task Development and Scheduling

Task Scheduling
Cron-based scheduling with upstream/downstream dependency management, support for historical backfill, and real-time visibility into task execution status.

→ Task Scheduling Dependencies

Workspace (SQL Query)
Interactive SQL editor with multi-tab support, result visualization, and query history — ideal for ad-hoc analysis and data exploration.

→ Workspace

Operations & Monitoring
View task run history, logs, and failure reasons. Configure alert notifications and stay on top of your data pipeline health.

→ Task and Instance Operations

Data Catalog
Browse and manage table schemas, column comments, and data lineage. Supports permission requests and approval workflows.

→ Data Catalog

💡 Tip: Studio vs cz-cli — Studio is the web GUI, suited for manual operations and visual configuration. cz-cli is the command-line interface, suited for scripting, CI/CD pipelines, and programmatic AI Agent calls. Both cover the same feature set.

I want to sync external data in

Recommended: Data Sync module — supports 40+ data sources with visual configuration, no code required.

Scenario	Approach	Reference
Relational databases (MySQL / PG / Oracle, etc.), real-time sync	Real-time sync task (CDC)	Real-time Sync Task
Full database sync, migrating multiple tables at once	Multi-table real-time sync	Multi-table Real-time Sync Guide
Offline periodic sync (T+1 or hourly)	Offline sync task	Offline Sync Task
Not sure which data source to use	Check supported sources	Data Source Support

Configuring a data source for the first time? Start with Data Source Management, then look up your database type in the Data Source Configuration Guide.

I want to develop data processing tasks

Recommended: Task Development module (IDE) — supports SQL, Python, and Shell with composable orchestration.

Scenario	Approach	Reference
SQL-based data transformation	SQL task	Task Development and Scheduling
Python processing logic	Python task	Python Task
Multiple tasks in sequence with dependencies	Composite task	Composite Task
Loop over multiple partitions or objects	For each loop task	For Each Loop Task
Conditional branching (if/else logic)	Branch task	Branch Task
Incremental computation with auto-maintained result tables	Dynamic table task	Dynamic Table Task

I want to configure scheduled execution

Recommended: Task Scheduling module — supports Cron expressions and upstream/downstream dependency management.

Scenario	Reference
Set up timed task execution	Task Scheduling and Instance Execution
Configure dependencies between tasks	Task Scheduling Dependencies
Backfill historical data	Data Backfill

I want to check task run status / troubleshoot issues

Recommended: Operations & Monitoring module.

Scenario	Reference
View task run history and logs	Task and Instance Operations
Configure alert notifications	Monitoring and Alerting
Understand monitoring metric definitions	Monitoring Metric Specifications

I want to query and analyze data

Scenario	Approach	Reference
Interactive SQL queries	Workspace	Workspace
Visualize query results	Analysis (Notebook)	Analysis
View and manage table schemas	Data Catalog	Data Catalog

I want to manage compute resources

Scenario	Reference
Create, start, or stop a VCluster	Compute Clusters
View historical job resource consumption	Job History
Understand cluster size codes	Compute Cluster Size Reference

I want to manage permissions and approvals

Scenario	Reference
Request data access permissions	Permission Requests
Process approval tickets	Approval Tickets

New to Studio?

Follow this sequence to get started:

Lakehouse Studio Quick Tour — 5-minute overview of the interface layout
Lakehouse Studio Getting Started Guide — complete your first end-to-end workflow
Studio Overview — deep dive into each module's capabilities