Data Pipelines and SQL for Product Analytics

This course is part of Product Analytics Unlocked: Metrics to Meaningful Insight Specialization

Instructor: Professionals from the Industry

Access provided by Lok Jagruti University

11 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

11 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build scalable data pipelines using SQL and Pandas to transform 10+ million rows of raw event data into structured analytics datasets.
Design and optimize star schemas with Type-2 slowly changing dimensions to track historical changes in product analytics data.
Compare and implement advanced SQL window functions across different dialects like Presto and Spark for cross-platform compatibility.
Evaluate existing data warehouse schemas and propose performance refinements using aggregation techniques and indexing strategies.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

21 assignments¹

AI Graded see disclaimer

Taught in English

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This course is part of the Product Analytics Unlocked: Metrics to Meaningful Insight Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 11 modules in this course

Learn to build complete data pipelines that transform raw event data into actionable insights using SQL and Pandas. You'll gain the skills to design efficient star schemas, implement Type-2 slowly changing dimensions for historical tracking, and optimize database performance for analytical workloads.

This course uniquely combines hands-on experience with massive datasets (10+ million rows) and practical exposure to multiple SQL dialects including Presto and Spark. You'll benefit professionally by developing the core competencies that product analytics teams depend on daily - from data transformation and pipeline architecture to performance optimization. By completion, you'll confidently tackle real-world data engineering challenges and contribute immediately to business intelligence initiatives in product analytics roles.

In this module, you will configure automated ETL pipelines using Apache Airflow to seamlessly ingest real-time event streams from sources like Mixpanel into data warehouses such as Snowflake.

What's included

2 videos1 reading1 assignment1 ungraded lab

In this module, you will implement systematic validation processes to assess mobile event implementations against predefined tracking specifications, identify compliance gaps, and create actionable remediation workflows.

What's included

1 video2 readings2 assignments

1 video Total 5 minutes

Why Data Compliance Validation Prevents Analytics Disasters 5 minutes

2 readings Total 18 minutes

Tracking Plan Compliance: Frameworks and Implementation 10 minutes
Mobile Event Schema Validation Techniques 8 minutes

2 assignments Total 18 minutes

Mobile Event Tracking Compliance & Validation Assessment 15 minutes
Mobile Event Compliance Validation Knowledge Check 3 minutes

You will learn to build scalable, maintainable data transformation pipelines through parameterized SQL scripting techniques.

What's included

3 videos1 reading2 assignments

3 videos Total 13 minutes

Why Parameterized SQL Scripts Transform Data Analytics Teams 3 minutes
Building Your First Parameterized Script: Syntax and Structure 7 minutes
Step-by-Step: Building a Customer Summary Pipeline 3 minutes

1 reading Total 3 minutes

Core Components of Parameterized SQL Data Transformation 3 minutes

2 assignments Total 21 minutes

Build Your E-commerce Revenue Pipeline 18 minutes
Parameterized SQL Pipeline Knowledge Check 3 minutes

You will learn systematic performance analysis techniques to identify and resolve database bottlenecks that impact analytical workflows.

What's included

2 videos2 readings3 assignments

2 videos Total 10 minutes

Why Query Performance Optimization Transforms Data Teams 3 minutes
Reading Execution Plans: Identifying Your Biggest Bottlenecks 7 minutes

2 readings Total 22 minutes

Systematic Performance Analysis: From Execution Plans to Optimization Strategies 10 minutes
Diagnosing and Fixing Slow Analytics Queries: A How-To Guide 12 minutes

3 assignments Total 35 minutes

SQL Performance Optimization Mastery Assessment 12 minutes
Optimize Your Data Warehouse Query Performance 20 minutes
Query Performance Analysis Knowledge Check 3 minutes

You will learn systematic approaches to transform complex nested JSON structures into pandas DataFrames, enabling reliable data preprocessing for analytics pipelines.

What's included

3 videos1 reading1 assignment

3 videos Total 16 minutes

Why JSON Transformation Skills Matter in Data Analytics 3 minutes
Understanding JSON Structure and Transformation Fundamentals 7 minutes
Step-by-Step JSON Flattening with pandas json_normalize() 6 minutes

1 reading Total 8 minutes

JSON to DataFrame Transformation Patterns and Best Practices 8 minutes

1 assignment Total 3 minutes

JSON Transformation Concepts and Implementation Knowledge Check 3 minutes

You will develop systematic approaches to identify, diagnose, and correct timezone-related data quality issues that fragment user sessions and compromise temporal analytics.

What's included

2 videos1 reading3 assignments1 ungraded lab

2 videos Total 14 minutes

Understanding Timezone Issues and Detection Strategies in Analytics Data 9 minutes
Systematic Timezone Correction Workflow Using Python and Pandas 5 minutes

1 reading Total 10 minutes

Systematic Timezone Correction Techniques for Production Data 10 minutes

3 assignments Total 36 minutes

Comprehensive JSON and Timezone Data Transformation Mastery Assessment 15 minutes
Diagnose and Correct Timezone Inconsistencies in Global User Analytics Dataset 18 minutes
Timezone Data Quality Analysis and Correction Techniques Knowledge Check 3 minutes

1 ungraded lab Total 20 minutes

Transform JSON & Fix Time Data 20 minutes

You will learn the critical syntax variations between SQL dialects that can make or break analytical queries in enterprise data environments.

What's included

2 videos2 readings1 assignment

2 videos Total 10 minutes

Why SQL Dialect Mastery Defines Your Analytics Career 5 minutes
Window Function Syntax Comparison: ANSI-SQL vs Spark-SQL 5 minutes

2 readings Total 18 minutes

SQL Dialect Architecture: Understanding Cross-Platform Variations 8 minutes
Troubleshooting Cross-Platform SQL Migration Issues 10 minutes

1 assignment Total 3 minutes

SQL Dialect Mastery Knowledge Check 3 minutes

You will learn advanced techniques for transforming raw event streams into structured analytical datasets using both SQL and Pandas aggregation methods.

What's included

2 videos1 reading3 assignments1 ungraded lab

2 videos Total 14 minutes

Why Event Data Aggregation Drives Modern Analytics Success 6 minutes
Pandas GroupBy Mastery for Event Data Transformation 8 minutes

1 reading Total 8 minutes

Event Data Architecture: Streams, Storage, and Aggregation Patterns 8 minutes

3 assignments Total 28 minutes

Enterprise Event Processing Mastery Assessment 10 minutes
Multi-Million Record Event Aggregation Pipeline 15 minutes
Event Data Aggregation Techniques Mastery Check 3 minutes

1 ungraded lab Total 20 minutes

Lab_Transform Data: SQL & Pandas Mastery 20 minutes

You will learn the fundamental concepts and practical implementation of Type-2 slowly changing dimensions to preserve complete historical data records in dimensional models.

What's included

2 videos2 readings1 assignment

2 videos Total 9 minutes

Why Historical Data Tracking Transforms Business Analytics 3 minutes
Understanding Type-2 SCD Fundamentals and Implementation Patterns 6 minutes

2 readings Total 18 minutes

SCD Implementation Strategies and Best Practices 8 minutes
Professional Guide: Implementing Type-2 SCD with dbt Step-by-Step Configuration 10 minutes

1 assignment Total 3 minutes

Type-2 SCD Implementation Knowledge Check 3 minutes

You will learn systematic evaluation techniques to assess star schema effectiveness and develop comprehensive refinement strategies that balance query performance, storage efficiency, and analytical capabilities.

What's included

2 videos2 readings3 assignments

2 videos Total 9 minutes

Why Star Schema Optimization Drives Business Intelligence Success 3 minutes
Schema Assessment Techniques: Performance Analysis and Bottleneck Identification 7 minutes

2 readings Total 15 minutes

Star Schema Evaluation Framework and Assessment Methodologies 8 minutes
Optimization Strategy Development: Prioritizing Schema Refinements 7 minutes

3 assignments Total 33 minutes

Star Schema Optimization Strategy Comprehensive Evaluation 12 minutes
Complete Star Schema Evaluation and Optimization Plan Development 18 minutes
Star Schema Evaluation and Optimization Knowledge Check 3 minutes

You will build a complete data pipeline system that automates event data ingestion, transforms complex data structures, and creates optimized analytical datasets. This project integrates skills from automated data ingestion, SQL optimization, JSON transformation, time data correction, advanced aggregation techniques, and dimensional modeling to create a production-ready analytics infrastructure.