Why Pyne chooses Steep for data-driven clients

Pyne is a Copenhagen-based data consultancy specializing in data engineering, analytics, strategy, machine learning, and AI, helping clients optimize data infrastructure, enhance analytics capabilities, and enable data-driven decision-making.

Client challenges

Emilio identified three common data challenges that most of his clients faced when he began working with them.

• Fragmented metrics: Clients struggled with fragmented and inconsistent metrics, leading to confusion and poor decision-making. “They had conflicting metrics that didn’t make sense. The lack of clarity slowed decision-making and complicated governance.”
• Hard-to-use tools: Tools like Tableau and Power BI were too complex for clients to use effectively across teams. “Getting the entire company on board was impossible because the technical curve was too steep (no pun intended).”
• Struggling to be data-driven: Companies that lack reliable and structured data tend to rely more on instinct rather than insights. For e-commerce businesses, this can mean missed opportunities, slower decision-making, and difficulty staying competitive. Reliable, accessible data is essential for driving growth and making informed decisions.

Why Steep?

Emilio has seen his clients opt for Steep for four main reasons.

1. Semantic layer: Steep's semantic layer standardizes data, creating a single source of truth and data consistency throughout the tool. “Steep creates a common language, so we focus on what’s important without debating definitions.”
2. Intuitive for users of all skill levels: Designed to be user-friendly, Steep ensures that everyone in the company can easily navigate and do their own analysis.
3. Fast setup: Setting up your company’s data on Steep takes only a couple of hours—a fraction of the time compared to traditional BI tools. “Time is our most valuable resource, so it’s really important to us that Steep is fast and easy to set up.”
4. Easy to maintain: When working with many clients it’s important that the tools they choose to implement are easy to maintain. With Steep, maintenance is minimal. From a data team perspective, you only need to update metric definitions and add new metrics when needed. Otherwise Steep runs itself.

Implementing Steep

To implement Steep for his clients, Emilio follows four simple and quick steps.

1. Identify metrics with stakeholders: This crucial first step ensures Steep is set up optimally to support the companies’ data needs. Emilio gathers relevant stakeholders to align on which metrics to add to Steep and their definitions. "These conversations can get heated, but aligning upfront saves countless headaches down the road."
2. Create data models: Once the metrics are aligned, Emilio creates data models that support the metric definitions. His favorite data stack for supporting clients is using Weld with BigQuery and Steep.
3. Connect database and define metrics in Steep: With the data models and database set up, connecting the database to Steep only takes a few minutes. Typical e-commerce businesses need between 20-30 metrics added which takes about an hour to add into Steep.
4. Introduce Steep to end users: “We spend 30 minutes introducing Steep and the semantic principles – the teams are amazed at how intuitive it is. They can start using Steep immediately.”

Benefits of using Steep

Since rolling out Steep for several clients, Emilio has observed significant results in their productivity and ways of working with data for both Pyne as a consultancy and their customers:

1. Improved productivity: Teams are working more efficiently with reliable data. Business users no longer need to wait for answers since they can find them themselves. With no more disagreements about which numbers are correct.
2. Reduced demand on technical teams: “Now, everything just flows naturally.” Business users can answer their questions independently, only approaching Emilio when a new metric is needed.
3. Increased data adoption: More people within the company are interacting with the data and making data-based decisions. “Steep has been a game changer when it comes to data adoption.”
4. Happy clients: “All clients we’ve rolled out Steep to are super happy with the tool, especially those who were paying for legacy tools like Tableau without being able to use them.”

Ready to transform your analytics? Book a demo with Steep today and discover how our intuitive BI tool can streamline how you work with data.