When enterprise teams discuss improving their business intelligence, the conversation often begins with tools: upgrading dashboards, layering predictive models, and automating reports. But beneath the surface of this endless stack expansion lies an issue more fundamental than any technical gap.
Everyone claims to be data-driven. From enterprise resource planning exports and customer relationship management dashboards to ESG metrics and sales forecasts—Business Intelligence teams are swimming in data. But in reality, most BI initiatives struggle because people can’t align fast enough to
Business Intelligence (BI) allows companies to minimize risks and surprises, which is a major advantage. Missed earnings, regulatory enquiries, and the like; usually result from unpreparedness or the inability to recognize red flags. Due to this fact, a significant portion of BI tools seems to aim
You can run the best models on pristine datasets. Still, a messy dashboard shuts the whole thing down. If it’s cluttered, hard to read, or built around developer logic instead of user needs, expect drop-off. Business Intelligence lives or dies by the experience. A dashboard isn't just a reporting
Knowing how your enterprise functions (especially in times of almost constant disruptions, be it economic, geopolitical, or technological) is harder than it has ever been before, for both you and your peers. All companies are facing a significant headache in driving business: fast-changing trends,
Imagine generating a presentation in minutes with a simple prompt, or drafting an insight-filled proposal with accurate data, moments before a meeting with management. With regenerative AI, these tasks are easily achievable and, supposedly, very common. Since the inception of artificial
