Data Product Slides

Recommended learning path

A straightforward series that follows the slide advancement—from basics and definitions to testing, drivetrain, and organizational design.

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1
Data Product 101: Overview
Slide 1
2
From Resource to Product
Slide 2
3
The Data Product Mindset
Slide 3
4
What is a Data Product?
Slide 4
5
Data Product Attributes
Slide 5
6
Software vs Data Products
Slide 6
7
Balancing R&D and Validation
Slide 7
8
Data Product Experimentation
Slide 8
9
The Drivetrain Approach
Slide 9
10
Data Product Operating Model
Slide 10
11
Data Product Life Cycle
Slide 11
12
Using Knobs
Slide 12
13
Triad - User Task and Data
Slide 13
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User Centric DP
Slide 14
15
Different Ways of Using DP
Slide 15

Why CDO/CAIO/CPO focus on Data Product

A Chief Data Officer should focus on data products because they convert data from a managed asset into a revenue-generating and decision-enabling capability. By adopting a data product operating model, the CDO can drive domain accountability, improve data quality at the source, reduce duplication across teams, and accelerate time-to-value. This approach also strengthens cross-functional alignment with business, technology, and product leaders, positioning the CDO not as a custodian of data, but as a strategic enabler of enterprise intelligence and growth.

How AI / GenAI Accelerates Data Product Development

Reduces build time from months to weeks.

Auto-generates SQL, transformations, and pipeline code

Speeds up schema discovery and data profiling

Assists with feature engineering and model prototyping

How Agentic AI Keeps Data Products Updated

Monitors schema drift and upstream changes

Detects anomalies and data quality issues proactively

Auto-validates SLAs and data contracts

Update Documentation, Publish Web Pages Dynamically

Why Agentic AI need Data Products

Data products serve as the foundation for AI and agentic systems, offering a reliable framework for LLMs, robust feature stores for ML models, effective retrieval layers for RAG architectures, and enforceable data contracts for real-time decision-making. In the realm of agentic AI, stable and clearly defined data products empower autonomous agents to think, act, and adapt workflows independently.

File list (

1-data-product-101
2-data-as-resource-vs-data-as-product
3-data-product-mindset
4-what-is-data-product
5-data-product-attributes
6-software-product-vs-data-products
7-inherent-tension-algorithm-usability
8-data-product-experimentation
9-drive-train-approach
10-data-product-operating-model

Data As Product Built for Outcomes Not Dashboards.

Recommended learning path

Slides and Guide

Data Product 101: Overview

From Resource to Product

The Data Product Mindset

What is a Data Product?

Data Product Attributes

Software vs Data Products

Balancing R&D and Validation

Data Product Experimentation

The Drivetrain Approach

Data Product Operating Model

Data Product Life Cycle

Build Data Products with Knobs

3 Pillars of Data Products

Value Chain of Data Products

Data Product Usage

Why Agentic AI need Data Products