What's Next?¶

Congratulations! You've completed the Seeknal Quick Start.

You've learned the pipeline builder workflow and run your first pipeline. Now what?

Choose Your Learning Path¶

Seeknal supports three main personas. Choose the one that matches your role:

Build production data pipelines at scale.

Chapter 1: Build an ELT Pipeline — Ingest data from APIs, transform with DuckDB, output to warehouses
Chapter 2: Add Incremental Models — Handle change data capture and schedule automated runs
Chapter 3: Production Environments — Virtual environments, change categorization, and promotion

Time commitment: 3 chapters × 20-30 minutes

Perfect for: Data Engineers, ETL Developers, Pipeline Engineers

Create semantic models and business metrics for self-serve analytics.

Chapter 1: Define Semantic Models — Create entities, dimensions, and measures
Chapter 2: Create Business Metrics — KPIs, ratios, cumulative metrics
Chapter 3: Deploy for Self-Serve Analytics — StarRocks deployment and BI tool integration

Time commitment: 3 chapters × 20-30 minutes

Perfect for: Analytics Engineers, Data Analysts, BI Developers

Build feature stores with point-in-time joins for ML applications.

Chapter 1: Build Feature Store — Feature groups, point-in-time joins, training data
Chapter 2: Second-Order Aggregation — Multi-level features and window functions
Chapter 3: Training-to-Serving Parity — Online serving and model integration

Time commitment: 3 chapters × 20-30 minutes

Perfect for: ML Engineers, Data Scientists, MLOps Engineers

Can't decide?

Here's a quick guide:

Pro tip

You can always come back and complete multiple paths! Each one reinforces the core concepts.

Want to understand how Seeknal works under the hood?

Looking up specific commands or syntax?

Join the Seeknal community:

Want to keep track of what you've learned?

You're ready to continue your Seeknal journey! Choose your path above and let's build something great.