Data Product Developer Learning Track

This track is designed to equip you with the skills needed to develop robust and scalable Data Products using DataOS.

By the end of this course, you'll be able to:

• Understand business needs: Align Data Products with business goals and define quality and security requirements.

• Design effective data models: Use DataOS Metis and Workbench to analyze and refine data assets.

• Build and implement Data Products: Develop logical semantic models, data pipelines, and apply access control.

• Deploy and manage Data Products: Utilize CI/CD practices for seamless deployment and updates.

Module 1: Understanding data needs

To create a successful Data Product, it’s crucial to first understand the business context and requirements. This module focuses on capturing key needs and expectations:

• Understanding business goals

• Collaboration with stakeholders

• Quality & security expectations

• Understanding consumption

Module 2: Designing Data Products

This module dives into the detailed process of designing Data Products tailored to meet specific business needs. It covers every aspect from defining use cases, and discovering existing resources, to creating a robust design and ensuring quality, security, and compliance.

• Designing Data Products

Module 3: Building Data Products

In the previous module, we explored the essential steps for designing a Data Product. We started by defining the use case of Customer Purchase Behavior for an online retail company. This use case focuses on analyzing customer buying patterns to identify cross-sell opportunities and enhance marketing strategies.

Now that we have a clear design plan, it’s time to move into the development phase. In this module, we will build the Data Product step by step, setting up the necessary components within DataOS.

• Establishing data connections

• Building data pipelines

• Creating semantic models

• Implementing quality checks to maintain data integrity

• Creating APIs to expose data for consumption by other systems

• Implementing Data Policies that govern access and security

Module 4: Deploying Data Products

The final step is to deploy the Data Product, making it available for consumption and ensuring it can be easily managed and updated.

• Packaging the Data Product and related Resources into a deployment Bundle

• Defining Data Product spec file

• Deploying Bundle and Data Product specifications using CLI

• Implementing CI/CD integration to automate updates for reliable Data Products