Break Free from Boring Dashboards with Data Exploration

Data-driven businesses rely on dashboards created by data teams to steer various functions. These dashboards are crucial for decision-making, like assessing a product feature's performance. Yet, they often fall short when it comes to explaining complex phenomena, such as unexpected traffic spikes.

The role and benefits of data exploration

Data exploration is more than just a supplement to dashboards—it’s a game-changer for any organization aiming to accelerate its success. It offers the flexibility to uncover insights that static dashboards can’t provide, delivering the actionable intelligence business teams need for strategic decisions and allowing data teams to perform quick, ad hoc analyses.

What is data exploration?

Defining data exploration

Data exploration is essential for a range of analytical needs—self-service analytics, ad hoc reporting, and strategic business improvements. It empowers teams to refine their questions iteratively, adapting strategies as new data and insights emerge.

The significance of data exploration

Data exploration is crucial for addressing various analytical needs, such as self-service analytics, ad hoc reporting, and strategic business improvements. It empowers teams to refine their questions iteratively, incorporating new data and insights to adapt their strategies effectively.

How data exploration enhances business strategy

Enhancing strategic decision-making

Dashboards alone can’t answer all strategic queries, like prioritizing your product roadmap. Data exploration provides deeper insights, guiding critical decisions with precision.

Accelerating hypothesis testing and experimentation

As data evolves, data exploration speeds up hypothesis testing and experimentation, allowing for swift adaptation and the discovery of fresh insights.

Improving day-to-day business decisions

Operational decisions demand more than basic dashboard metrics. Data exploration enables detailed investigations into specific issues, helping teams swiftly address and resolve problems.

Utilizing data exploration for product analytics

Supporting product development

Understanding product health metrics and their broader implications is key. Beyond basic usage stats, data exploration helps answer complex questions about customer engagement and product value.

Addressing common product strategy questions with data exploration

• What is the relationship between support tickets and customer retention?
• Should we develop a freemium model?
• Which markets should we target during economic shifts?
• What should our product roadmap priorities be?
• Was our recent product launch successful in driving revenue?
• Did the product launch improve customer retention?

Ensuring reliable and valuable data exploration

The importance of data governance

Trustworthy data starts with solid governance. Data teams must work with business units to define and validate metrics, ensuring consistent, reliable data throughout the organization.

Collaborative metric definitions

Data teams should collaborate with business stakeholders to set and govern key metrics. With Sigma, integrating data governance platforms ensures accurate, explorable metrics for all business users.