Analytics Engineer Path¶

Duration: ~75 minutes | Format: YAML | Prerequisites: SQL, DE Path Chapter 1 completed

Build semantic models and business metrics that enable self-serve analytics for your organization.

What You'll Learn¶

The Analytics Engineer path teaches you to build a governed semantic layer with Seeknal. You'll learn to:

Build Semantic Models - Define entities, dimensions, and measures on top of existing transforms
Define Business Metrics - Create simple, ratio, cumulative, and derived metrics
Deploy for Self-Serve - Deploy metrics as StarRocks materialized views for BI tools

Prerequisites¶

Before starting this path, ensure you have:

DE Path Chapter 1 completed — You'll build on the orders_cleaned transform
Basic SQL knowledge (JOINs, aggregations, window functions)
Familiarity with business metrics (KPIs, ratios)

Chapters¶

Chapter 1: Build a Semantic Model (~25 minutes)¶

Define a semantic model on top of your e-commerce data:

orders_cleaned → Semantic Model → Queryable Metrics
                      ├── Entities (order, customer)
                      ├── Dimensions (date, status)
                      └── Measures (revenue, count, AOV)

You'll build: - A semantic model YAML with entities, dimensions, and measures - Queryable semantic layer using seeknal query - Foundation for business metrics in Chapter 2

Start Chapter 1 →

Chapter 2: Define Business Metrics (~25 minutes)¶

Create reusable business metrics from your semantic model:

Semantic Model → Metrics (YAML) → seeknal query
                    ├── Simple (Total Revenue)
                    ├── Ratio (AOV)
                    ├── Cumulative (Running Total)
                    └── Derived (Revenue Growth)

You'll build: - Simple metrics (total revenue, order count) - Ratio metrics (average order value) - Cumulative and derived metrics - Multi-metric queries with dimensions

Start Chapter 2 →

Chapter 3: Deploy to StarRocks (~25 minutes)¶

Deploy your metrics as materialized views for BI consumption:

Metrics → seeknal deploy-metrics → StarRocks MVs → BI Tools
                                        ↓
                                  MySQL Protocol

You'll learn: - StarRocks connection configuration - Deploying metrics as materialized views - DDL preview with --dry-run - BI tool integration via MySQL protocol

Start Chapter 3 →

What You'll Build¶

By the end of this path, you'll have a complete semantic layer:

Component	Technology	Purpose
Semantic Model	YAML	Define entities, dimensions, measures
Simple Metrics	YAML	Aggregate single measures
Ratio Metrics	YAML	Numerator/denominator calculations
Cumulative Metrics	YAML	Running totals over time
Derived Metrics	YAML	Compose metrics from other metrics
StarRocks MVs	Materialized Views	Fast BI queries

Key Commands You'll Learn¶

# Query semantic layer metrics
seeknal query --metrics total_revenue,order_count --dimensions status

# Show generated SQL without executing
seeknal query --metrics total_revenue --compile

# Deploy metrics to StarRocks
seeknal deploy-metrics --connection starrocks://root@localhost:9030/analytics

# Preview DDL before deploying
seeknal deploy-metrics --connection starrocks://... --dry-run

# Interactive SQL on your data
seeknal repl

Resources¶

Reference¶

CLI Reference — All commands and flags
YAML Schema Reference — Semantic model and metric schemas

Data Engineer Path — ELT pipelines (prerequisite)
ML Engineer Path — Feature stores and ML pipelines

Last updated: February 2026 | Seeknal Documentation