Drill to Detail Ep.116 ‘Spotify, Semantic Layers and Steep’s Metrics-First Approach to BI Tools’ with Special Guest Johan Baltzar
Nov 18, 2024
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Johan Baltzar, co-founder and CEO of Steep, shares insights from his time as Product Analytics Manager at Spotify. He discusses how analytics fueled Spotify's explosive growth and the challenges of making data accessible to all employees. Johan also delves into Steep's user-friendly business intelligence tools, emphasizing semantic layers for real-time data access. Additionally, he explores the vibrant startup culture in Stockholm, highlighting effective collaboration and innovation in the tech scene.
Steep aims to empower non-technical users by shifting data responsibilities from specialists to all employees, enhancing data-driven decision-making.
The focus on integrating with existing semantic layers ensures seamless access to metrics, promoting consistency and structured analysis throughout the organization.
Deep dives
Content Creation Beyond Data Teams
The primary focus of Steep is shifting the responsibility of content creation from data teams to all employees within a company. This change empowers non-technical business users, such as marketing and finance teams, to access and analyze data without constantly relying on analytics specialists. Steep aims to eliminate the bottleneck created by traditional BI tools, where data teams are frequently inundated with requests for dashboards and reports. By enabling everyone to engage directly with data, Steep improves efficiency and fosters a culture of data-driven decision-making across the organization.
Innovative Metrics Catalog and Composable Analysis
Steep introduces a unique metrics catalog that serves as a user-friendly starting point for analyzing data, contrasting with traditional BI tools that often present overwhelming lists of tables and columns. This approach simplifies the user experience and allows employees to easily find and work with relevant metrics. The concept of composable analysis is central to this model, as users can overlay multiple metrics and conduct analyses without preparing complex queries in advance. This flexibility promotes exploration and fosters a deeper understanding of data relationships, making analytics more intuitive for all users.
Integration with Semantic Layers
Steep prioritizes compatibility with existing semantic layers, such as DBT and Cube, allowing organizations to leverage their current data infrastructure without disruption. This integration ensures that users can seamlessly access and analyze metrics defined in these external tools, providing a consistent and cohesive user experience across platforms. By aligning with the principles of the semantic layer, Steep aims to enable more structured and systematic data analysis, ensuring that business users can trust the insights derived from their metrics. This approach highlights the importance of flexibility in data analytics, accommodating various users' needs without losing coherence.
Empowering Collaborative Data Use
Steep's design philosophy embraces collaboration and accessibility, modeled after successful tools like Figma that democratize design work. By removing barriers to data access, Steep encourages teamwork between data teams and business users, allowing for more impactful and innovative analytics processes. This collaboration is supported by a well-defined semantic layer that maintains consistency and governance while enabling exploration. The emphasis on a minimalist and intuitive design further reinforces the goal of empowering users, ensuring that they can efficiently interact with data, which should continually evolve based on user feedback and needs.
Mark is joined in this episode by Johan Baltzar, previously Product Analytics Manager at Spotify and now co-founder and CEO at Steep to talk about the role analytics played in Spotify’s growth story, the startup scene in Stockholm, Sweden and Steep’s metrics-first approach to user-centric business analytics.