DBTA E-EDITION
October 2025
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Trends and Applications
Artificial intelligence (AI) is transforming industries by automating processes, enabling smarter decisions, and unlocking new avenues for innovation. According to recent Semarchy research, 74% of businesses are investing in AI this year to boost performance and efficiency. Although AI's effectiveness relies heavily on quality data, 98% of organizations report that poor data quality undermines their AI initiatives. The result? Inaccurate AI models, biased outcomes, and operational challenges. Put simply, AI's inherent speed, agility, and precision can become liabilities if it's fed flawed data.
Data leaders and professionals are engaged in a race to prepare their organizations for robust artificial intelligence (AI) and machine learning initiatives. Notably, they are aware of and well-tuned in the roles that GenAI and large language models can serve in the AI-friendly architectures on which they are focused.
There is a growing urgency to adopt cloud services to buttress today's rapidly growing inventories of high-end analytic and AI applications. This is fueled by massive volumes of data that are spilling over the capacities and capabilities of on-prem systems. It works the other way, as well: AI is paving the way for more robust cloud services, offering ever-expanding real-time automated provisioning and scalability.
As organizations race to adopt AI, many struggle to move past proof of concept. Gartner predicts that 30% of generative AI (GenAI) projects will be abandoned by the end of 2025 largely due to issues around data readiness, governance, and deployment structure, so let's start there. In fact, as Gartner puts it: "Through 2026, those organizations that don't enable and support their AI use cases through an AI-ready data practice will see over 60% of AI projects fail to deliver on business SLAs and be abandoned." That's a wake-up call.
Columns - Database Elaborations
When we draw lines within an entity-relationship diagram (ERD) that represent a "relationship," the diagram only shows the exterior presentation. A relates to B in a one-to-many fashion. But what is the actual nature of that A-to-B relationship? Is the relationship one of composition where A is the whole and each B is a part of A? Can any B exist without an A?
Columns - DBA Corner
Data breaches are a constant, lurking threat in our interconnected world and database administrators are the front-line guardians of their organization's most valuable asset: its data. The modern database environment, with its mix of on-premises, cloud, and hybrid systems, can feel like a minefield. Navigating it successfully requires more than just technical skill—it demands a proactive, strategic approach to security.
Columns - SQL Server Drill Down
In the AI era, we're constantly talking about how important data is—storing data, disseminating data, and protecting data. As data specialists, we understand bad data management leads to bad use of AI which leads, quite frankly, to bad business outcomes.
Columns - Emerging Technologies
With fall in full swing, the conference season is reaching its peak as professionals gather across the country for major industry events. While cities such as Las Vegas and Orlando have long been mainstays for large-scale conventions, a new venue on the West Coast is beginning to draw attention.
MV Community
Rocket Software has released a multi-part series on AI, helping MultiValue customers trust, understand, and apply AI when necessary. Advised by Mike Rajkowski, MV evangelist, the four-part series of "Foundations of Trust: Navigating AI's Reliability" includes: Ensuring Generative AI Acts as Your Trusted Business Advisor, the Scope of Information and Customization, and more.