From Data to Dollars: Getting Started with Data Analytics and AI in Startups (eng)

Turn raw data into real traction—and real revenue.

This hands-on guide is built for the realities of startup life—where time is short, resources are limited, and every decision counts. Whether you're just getting started or scaling fast, this book is your essential toolkit for building a data-driven startup ready for growth and innovation—and for turning insight into impact, and data into dollars.

Drawing from years of experience as the first data hire at multiple high-growth startups across the US and Europe, author Piotr Sidoruk shares practical insights into building data systems that are both affordable and scalable, agile and reliable. You’ll explore how to create a strong data foundation free from the rigidity of traditional corporate models, and how to use analytics and AI to inform product development, customer insights, and investor communication—ultimately turning data into measurable business outcomes and revenue growth.

What sets this book apart is its unified approach. Instead of siloing data engineering, analytics, and machine learning, it brings them together into one actionable playbook tailored for startup environments. With real-world examples from companies lsuch as Spotify, Airbnb, and Stripe, you’ll see how data can become a strategic asset from day one. From your first data hire to your next funding round, this book is your manual for building a startup where data drives every decision.

What You Will Learn

• Develop a data-driven strategy aligned with startup goals, using rapid, iterative methods to support fast growth
• Set up and manage data warehouses, build pipelines, and integrate diverse data sources seamlessly
• Design and scale flexible, cost-effective data infrastructure tailored to startup constraints
• Use data to drive decision making that directly impacts customer retention and revenue
• Build dashboards and reports in BI tools to track the metrics that matter most for customer engagement, retention, and growth
• Master data storytelling to influence stakeholders and secure investor funding
• Demystify and apply advanced techniques in AI and machine learning to enhance innovation and competitiveness
• Calculate and monitor essential startup metrics, such as Customer Acquisition Cost (CAC), Lifetime Value (LTV), retention, and growth KPIs
• Combine quantitative data with qualitative insights to deeply understand user behavior and optimize product experience

Who This Book Is For

Data engineers, analysts, and scientists who are the first data hires at startups—or preparing to work in fast-paced, high-growth startup environments. Ideal for professionals looking to build scalable data systems, drive product insights, and grow their careers in early-stage tech companies.

Piotr Sidoruk is a startup data expert with a unique experience of being the first data hire at several startups across both the US and Europe. He has built data infrastructure from scratch, helping startups scale and secure around $20 M in funding and revenue through strategic recommendations and data storytelling that convinces investors to fund their growth (e.g. He helped Playbook build data storytelling to raise $9.3 M).

With a degree in Quantitative Methods in Economics and Information Systems and a background in Psychology, Piotr brings a multidisciplinary approach to data-driven problem-solving. He has worked across a range of industries, including fitness, retail, FMCG, financial services, pharma, igaming, crypto, and real estate, collaborating with major corporations such as IBM, Bain, and Roche. He also has extensive experience in the startup world, having contributed to ventures such as Playbook, a New York-based fitness and creator economy platform; Rentier, a European real estate valuation platform; and MyMenu, an AI-powered meal planning engine that was purchased and implemented by a large German international discount retail chain.