The countdown has already begun and the momentum around this year’s Databricks Data & AI Summit (DAIS) 2026 is building up. It is bigger, sharper and solution driven. Over the past few years, conversations around AI have evolved from cautious experimentation to urgent execution. Speed, along with the ability to operationalize AI, maintain strong governance,

We’re excited to introduce DQPulse, a Databricks-certified Brickbuilder Accelerator from Hoonartek. DQPulse is an automated data quality framework that embeds rule-driven validation, comprehensive logging, and intuitive dashboards directly into enterprise data pipelines on the Databricks Data Intelligence Platform. Solving the Scalability Gap in Enterprise Data Quality Without a formal data quality framework, organizations face significant

We’re excited to introduce MaskXccelerate, a Databricks-certified Brickbuilder Accelerator from Hoonartek. MaskXccelerate is a comprehensive data masking framework that enables secure, role-based access to sensitive data across enterprise data pipelines without disrupting analytics or AI workloads on the Databricks Data Intelligence Platform. The Challenge: Security Without Friction Enterprises face a persistent dilemma: how do you

There’s always a discernible difference between what is announced at conferences, and what is actually signaled. Google Cloud Next 2026 at Las Vegas attested to the latter. The sheer scale of capital and engineering that was showcased confirmed a definitive shift in the industry: the generative AI honeymoon phase is over. We have entered the era of production-scale autonomous agents. Walking the floor as a partner last week, the message was unambiguous: Google is no

Why AI Is the Ultimate Truth-Teller In boardrooms across the UK, Europe, and India, the conversation has moved past the novelty of generative models to a more sobering question: why isn’t our AI scaling with confidence? The uncomfortable answer is that AI did not create your governance problem. It removed the conditions that allowed you

The prevailing boardroom narrative frames data governance as a something birthed by generative AI and the tangled data estates of the 2020s. Having worked through the transitions from legacy mainframe architecture to modern cloud ecosystems, I’d argue this narrative is getting the diagnosis wrong. Enterprises are not facing a ‘governance gap’ created by new technology.

The landscape of 2025 makes one thing clear: cloud migration is no longer a choice, but a necessity for sustained business growth and innovation. Predictions suggest that a vast majority of businesses will adopt cloud-first strategies, highlighting the urgency for cloud integration into core infrastructure. For enterprises aiming to thrive in this era of rapid

Data is a key factor in every aspect of a business. Everything revolves around it. Organizations store, manage and use large amounts of data daily. In the world of business, data is like the puzzle pieces that help us make decisions. But just having the pieces isn’t enough – they need to fit perfectly. That’s

In today’s competitive financial landscape, loan approvals depend on more than just a loan officer’s intuition. This makes way for Business Rules Engine (BRE) – the invisible maestros orchestrating lending decisions with precision and speed. Think of them as silent partners, tirelessly scrutinizing data, applying pre-defined rules, and delivering accurate verdicts within seconds. Gone are

Data Governance is often given low priority by most organizations since it is seen as an avoidable cost. The CIO doesn’t have a convincing response to the question on the ROI of Data Governance—it is seen as a cost to manage data with no impact on revenues or EBITDA. We’ve all been there – asking