DBTA E-EDITION
February 2025
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Trends and Applications
The "data deluge" is as familiar to IT professionals as it is cliché, but what we are encountering today is very different. Will our typical response be enough? Often hyped, the data deluge has been an omnipresent theme in IT circles for years as enterprises struggled to manage an ever-increasing barrage of data.
Retrieval-augmented generation (RAG) has become a go-to architecture for companies using generative AI (GenAI). Enterprises adopt RAG to enrich large language models (LLMs) with proprietary corporate data so LLMs have the data they need, but weren't trained on, to answer questions.
AI and generative AI (GenAI) cannot function—let alone deliver trustworthy analysis—without well-vetted, quality data. Data executives across many leading organizations recognize that data has become the Achilles' heel of AI. Yet, as far as they are concerned, AI is too important to pass up, and it's still full speed ahead for AI and GenAI investments—despite near-term headwinds incurred by any lack of readiness of organizations' data infrastructure and assets.
All of the hype and high hopes around AI in recent years has focused on compelling use cases—from creating new medicines to taking over customer service. However, all AI efforts will be nonstarters without well-governed, well-sourced data. That is the leading challenge for enterprises going forward in the competitive economy of 2025.
Columns - Database Elaborations
Normalization clusters data items together based on functional dependencies within the data items. This normalized arrangement expresses the semantics of the business items being presented. Denormalization means that, for some reason, grouping the data strictly by functional dependencies has been ignored. Why might one cast aside reasonable designs for something less rational? There are many reasons for denormalizing.
Columns - DBA Corner
The role of the Database Administrator (DBA) is constantly evolving to adapt to changes in technology and application development methods. Once primarily focused on managing physical hardware and software, DBAs now find themselves navigating a complex landscape of cloud technologies, AI-driven automation, and ever-increasing data volumes. Here at the beginning of 2025, let's explore the top five concerns that keep DBAs up at night.
Columns - SQL Server Drill Down
Since the term's inception in the late 2000s, "DevOps" is by far the most common approach to product development. During the last 15 years, DevOps processes have evolved to new speeds and scales, with the latest iteration including AI-assisted coding and platform engineering. Simultaneously, certain companies are struggling to master database operations. As a result, many organizations have data that sits in silos and/or can be hard to track down. What today's businesses need is a way to combine DevOps and data management, ultimately creating a Database DevOps framework.
Columns - Emerging Technologies
The World Economic Forum has made a bold statement: We are in the midst of the Fourth Industrial Revolution, and this revolution is more challenging than any before it. What makes it so difficult? This new era is defined by technologies we can't see, touch, or fully understand. From AI to big data and augmented reality, these innovations are transforming every aspect of our lives at a pace that many believe humanity simply can't keep up with.
MV Community
In the thick of the 2020s now, organizations are entering a new tech era, one dominated around conversations declaring, "What AI can do for your enterprise!" As 2025 begins, DBTA presents the annual MultiValue (MV) Special Report and asks MV executives to address several questions.
Rocket Software announced the latest enhancements to the Rocket U2 System Builder Extensible Architecture version 6.6.2. This release brings a host of improvements and fixes that enhance the functionality and reliability of the platform.