Dashboards and reports are two common terms used interchangeably in discussions around business intelligence (BI) and data analytics platforms. Both are analysis tools used to present operational information graphically, provide visibility into organizational performance, and enable informed decision-making based on hard-tracked metrics. But what is the actual difference between BI dashboards vs a report?

Apache DataSketches in BigQuery enable approximate analytics with minimal memory or computational overhead, and with a single pass through the data.

Insights from 100+ data professionals in our latest cost and pricing survey report.

AI.GENERATE_TABLE() in BigQuery lets you convert unstructured data into a structured table based on the provided prompt and table schema.

As a long-established ERP, SAP has earned its trust by helping users streamline and improve financial operations. But the global economy is in a state of rapid flux, making financial navigation challenging. Further, the SAP ecosystem’s technical intricacies add another layer of complexity for those without specialized expertise in managing financial decisions.

At the heart of any enterprise data management strategy is the driving principle of infrastructure as code (IaC), the practice of defining, provisioning and managing infrastructure through code, and a foundational approach for enabling continuous delivery (CD).

After years of feedback from customers and quiet development, we officially launched a powerful new set of advanced analytics features during our May 7th launch event. This release marks a major milestone in our mission to make Business Intelligence (BI) accessible to everyone. We call it DIY BI (Do-It-Yourself Business Intelligence): the idea that anyone, regardless of technical skill, can explore data, find answers, and improve performance without relying on complex tools or a busy data analyst.

Your reports are only as good as your data. When your team spends hours building dashboards and answering leadership questions, mismatched or messy data can quickly erode trust. That’s why data preparation-cleaning, organizing, and aligning your data through structured preparation processes is the first (and most critical) step before you can analyze trends, track goals, or forecast results.

Unlocking SAP data to power analytics, AI, and better business decisions is only part of the equation: Securing that data is just as critical.