Managing Data as a Product: Scalable Data Architectures

Managing Data as a Product: Scalable Data Architectures

Instructor: Packt - Course Instructors

Access provided by NMIMS Indore

12 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

12 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Overcome challenges in scaling monolithic data platforms
Adopt a data-as-a-product approach for sustainable growth
Navigate the full lifecycle of data products from inception to decommissioning

Skills you'll gain

Tools you'll learn

Generative AI

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

12 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

There are 12 modules in this course

This course provides essential skills for modernizing data architectures by adopting a data-as-a-product approach. It emphasizes building modular, scalable systems to enhance data management and unlock greater value from data assets.

Throughout the course, you will learn to design, implement, and manage data products in a distributed environment, ensuring sustainable growth and scalability. By focusing on practical, real-world applications, the course empowers learners to overcome the challenges of traditional monolithic data platforms. What sets this course apart is its combination of theory and hands-on activities. You will not only grasp key concepts but also develop actionable strategies to modernize your data architecture effectively. Real-world case studies and best practices will guide you through the process. This course is ideal for data engineers, architects, and leaders looking to enhance their data strategies and modernize their organization’s data management. A solid understanding of core data engineering principles is recommended. This course is based on material written by an expert author, bringing the depth of a book into a more engaging, interactive format. The core content is delivered through clear, structured text you can read at your own pace, supported by short videos and quizzes to highlight key ideas and test your understanding. By combining the strengths of book learning with interactive assessments, you get the best of both worlds: the depth and clarity of an author’s expertise, plus the flexibility to revisit, practice, and reinforce concepts whenever you need.

In this section, we examine monolithic data platforms' limitations and explore modular approaches to reduce accidental complexity and improve system sustainability through data product strategies.

What's included

2 videos8 readings1 assignment

2 videos Total 2 minutes

Course Overview 1 minute
From Data as a Byproduct to Data as a Product - Overview Video 1 minute

8 readings Total 80 minutes

Introduction 10 minutes
Data Warehouse 10 minutes
DWH Versus Data Lake 10 minutes
Understanding Why Monolithic Data Platforms Fail 10 minutes
Failure Loops 10 minutes
Exploring Why We Need to Manage Data as a Product 10 minutes
Data Is Everybody's Business 10 minutes
Data Product Thinking 10 minutes

1 assignment Total 10 minutes

Data Management and System Complexity Fundamentals 10 minutes

In this section, we define data products and pure data products, analyze their structure and characteristics, and explore methods for classifying them to enhance data utilization.

What's included

1 video8 readings1 assignment

1 video Total 1 minute

Data Products - Overview Video 1 minute

8 readings Total 80 minutes

Introduction 10 minutes
Why Do We Need Pure Data Products? 10 minutes
Pure Data Product Definition 10 minutes
The Rise of Data-Driven Applications 10 minutes
Relevance 10 minutes
Composability 10 minutes
Input Ports 10 minutes
Classifying Pure Data Products 10 minutes

1 assignment Total 10 minutes

Data Product Fundamentals 10 minutes

In this section, we examine data-product-centered architecture design, operational and management planes, and alternative data management approaches for scalable, adaptable solutions.

What's included

1 video4 readings1 assignment

In this section, we explore domain-driven design and event storming to identify data products, and manage their portfolio for business alignment and operational coherence.

What's included

1 video8 readings1 assignment

1 video Total 1 minute

Identifying Data Products and Prioritizing Developments - Overview Video 1 minute

8 readings Total 80 minutes

Introduction 10 minutes
Connecting Problem and Solution Spaces 10 minutes
Identifying Subdomains 10 minutes
Identifying Bounded Contexts 10 minutes
Mapping Business Capabilities 10 minutes
Turning Business Strategy Into Actionable Business Cases 10 minutes
Analyzing Processes with Event Storming 10 minutes
Managing the Data Product Portfolio 10 minutes

1 assignment Total 10 minutes

Strategic Alignment of Data and Business Capabilities 10 minutes

In this section, we examine data product design, interactions, and implementation, focusing on metadata management, machine-readable descriptors, and data flow processes for scalable solutions.

What's included

1 video8 readings1 assignment

1 video Total 1 minute

Designing and Implementing Data Products - Overview Video 1 minute

8 readings Total 80 minutes

Introduction 10 minutes
Understanding the Data Product Global Ecosystem 10 minutes
Understanding Data Product Internals 10 minutes
Managing Data Product Metadata 10 minutes
Introducing the Data Product Descriptor Specification 10 minutes
Describing Interface Components in DPDS 10 minutes
Describing Internal Components in DPDS 10 minutes
Processing Data 10 minutes

1 assignment Total 10 minutes

Data Product Design and Implementation Fundamentals 10 minutes

In this section, we explore deploying data products using CI/CD, governing them with policies, and managing their evolution to ensure reliability and alignment with organizational standards.

What's included

1 video9 readings1 assignment

1 video Total 1 minute

Operating Data Products in Production - Overview Video 1 minute

9 readings Total 90 minutes

Introduction 10 minutes
Infrastructure as Code 10 minutes
Automating Integration Tests 10 minutes
Understanding CD 10 minutes
Defining the Deployment Pipeline 10 minutes
Governing Data Products 10 minutes
Implementing Computational Policy 10 minutes
Observing Data Products 10 minutes
Controlling Data Products 10 minutes

1 assignment Total 10 minutes

Operating Data Products in Production 10 minutes

This section covers automating data product lifecycle management with XOps, focusing on platform capabilities and implementation strategies.

What's included

1 video6 readings1 assignment

1 video Total 1 minute

Automating Data Product Lifecycle Management - Overview Video 1 minute

6 readings Total 60 minutes

Introduction 10 minutes
Understanding Platform Value Engines 10 minutes
Leveraging Platform Value Engines 10 minutes
Boosting Developer Experience 10 minutes
Defining Data Product Modules and Blueprints 10 minutes
Supporting Computational Policy and Ontology Development 10 minutes

1 assignment Total 10 minutes

Data Product Lifecycle and XOps Fundamentals 10 minutes

In this section, we explore the adoption phases of data as a product, focusing on challenges, strategies, and adaptive data governance to ensure sustainable and scalable implementation.

What's included

1 video8 readings1 assignment

1 video Total 1 minute

Moving through the Adoption Journey - Overview Video 1 minute

8 readings Total 80 minutes

Introduction 10 minutes
Preparing for the Assessment 10 minutes
Understanding the Why 10 minutes
Setting the Foundation 10 minutes
Defining Key Governance Policies 10 minutes
Enabling the Enablers 10 minutes
Dealing with Legacy Systems 10 minutes
Planning the Execution with EDGE 10 minutes

1 assignment Total 10 minutes

Navigating the Adoption Journey 10 minutes

In this section, we explore team topologies and data ownership strategies to optimize organizational structures for scalable data product delivery and efficient team collaboration.

What's included

1 video9 readings1 assignment

1 video Total 1 minute

Team Topologies and Data Ownership at Scale - Overview Video 1 minute

9 readings Total 90 minutes

Introduction 10 minutes
Understanding Team Types 10 minutes
Collaboration 10 minutes
Mapping the Organizational Architecture 10 minutes
Data Product Teams 10 minutes
Platform Teams 10 minutes
Defining Management Teams 10 minutes
Understanding When to Decentralize 10 minutes
Moving toward decentralization 10 minutes

1 assignment Total 10 minutes

Team Topologies and Data Ownership at Scale 10 minutes

In this section, we explore distributed data modeling techniques, focusing on physical and conceptual approaches to design explicit models for data products in decentralized systems.

What's included

1 video11 readings1 assignment

1 video Total 1 minute

Distributed Data Modeling - Overview Video 1 minute

11 readings Total 110 minutes

Introduction 10 minutes
Data Modeling Process 10 minutes
Operational and Analytical Data Modeling Methodologies 10 minutes
Centralized Dimensional Modeling 10 minutes
Distributed Dimensional Modeling 10 minutes
Data Vault Modeling 10 minutes
Managing Hubs and Links as a Service 10 minutes
Join Traps 10 minutes
Puppini Bridge 10 minutes
Exploring Distributed Conceptual Modeling 10 minutes
From String to Things 10 minutes

1 assignment Total 10 minutes

Data Modeling Fundamentals in Distributed Systems 10 minutes

In this section, we explore building an AI-ready information architecture by designing a knowledge plane for semantic interoperability and constructing an enterprise knowledge graph for AI integration.