What it means, why it matters, and how it works. This guide provides definitions and practical advice to help you understand and practice modern self-service analytics.
Self-service analytics provides all users the ability to gain insights from their data, even if they don’t have data or analytics expertise. By giving end users the tools they need to access, visualize and explore data, design dashboards and run reports, IT teams, analysts and data scientists can focus on more critical strategic projects.
Today, businesses are creating and accumulating data at an incredible pace. But making that data easily available to everyday users is one of the biggest hurdles to turning your data into real business value. With self-service data analytics, users can gain insights far more easily and quickly, helping organizations realize the value of their data faster.
Access to self-service analytics tools means business users no longer have to submit a request to IT or an analyst and then wait for answers that may already be outdated. Nor do they have to rely solely on intuition, which could result in poor decisions and costly mistakes.
Instead, self-service analytics facilitates a data-driven culture by giving non-technical users insights at the exact moment they need them, and informed guidance in the form of recommendations. When combined with streamlined business processes and employee training, businesses can also increase data literacy across all business functions.
See how to explore information and quickly gain insights.