Revolutionizing AI Data Access: A Look at Denodo Platform 9.3 and the New DeepQuery Engine
In the race to harness the power of artificial intelligence and machine learning, organizations face a persistent and critical bottleneck: data access. AI models, especially large language models (LLMs), are incredibly data-hungry, yet the information they need is often trapped in disparate silos across hybrid and multi-cloud environments. The process of preparing and delivering this data can be slow, complex, and a major drain on resources.
A new advancement in logical data management aims to solve this challenge head-on. The release of Denodo Platform 9.3 introduces DeepQuery, a groundbreaking AI-powered engine designed to dramatically accelerate data delivery for the most demanding analytical and AI workloads. This isn’t just an incremental update; it’s a fundamental shift in how organizations can optimize their data pipelines for the age of AI.
The Growing Challenge: Feeding the AI Beast
Data scientists and engineers consistently report that a significant portion of their time—often up to 80%—is spent on data preparation and retrieval rather than on building and training models. This inefficiency stems from several core issues:
- Data Silos: Data is spread across on-premises databases, cloud data lakes, SaaS applications, and more.
- Complex Queries: AI and ML tasks require complex queries that join massive datasets from these varied sources.
- Performance Bottlenecks: Traditional query optimizers struggle to efficiently plan and execute these highly complex queries, leading to long wait times.
This friction not only slows down innovation but also increases the total cost of ownership for data infrastructure. To truly unlock the potential of AI, businesses need a smarter, faster way to manage and query their data.
What is DeepQuery? The AI-Powered Engine at the Core
At the heart of Denodo Platform 9.3 is DeepQuery, which reimagines query optimization. Unlike traditional rule-based optimizers that follow a predefined set of instructions, DeepQuery leverages artificial intelligence to learn from past queries and understand the unique patterns within an organization’s data landscape.
Think of it as the difference between a simple GPS that follows a static map and an advanced navigation app that uses real-time traffic data to find the absolute fastest route. DeepQuery analyzes query history, data statistics, and system performance to dynamically rewrite and accelerate incoming data requests. This self-learning capability allows it to find optimization paths that would be impossible for a human or a rule-based engine to discover.
Key Benefits for AI and Analytics Workloads
The introduction of this AI-driven optimization delivers tangible benefits for any organization investing in data science and machine learning.
- Drastically Reduced Query Times: By intelligently optimizing how data is retrieved and combined, DeepQuery can slash query execution times. This means data scientists get the data they need for model training and inference in a fraction of the time, accelerating the entire MLOps lifecycle.
- Enhanced Data Scientist Productivity: With faster data access and less time spent on manual query tuning, data teams can focus on their core mission: extracting value and insights from data. This boosts productivity and allows teams to tackle more complex and innovative projects.
- Simplified Access Across Complex Environments: DeepQuery operates within Denodo’s logical data fabric, meaning it can optimize queries that span a wide array of underlying data sources. It seamlessly accelerates data access across hybrid and multi-cloud architectures without requiring costly and time-consuming data movement.
- Unlocks Advanced and Generative AI: The massive scale of data required by Generative AI and LLMs makes traditional data delivery methods unfeasible. DeepQuery is specifically engineered to handle the complexity and scale of these next-generation workloads, making it possible to power advanced AI initiatives with a logical, governed data foundation.
A More Powerful and Cohesive Platform
Beyond DeepQuery, the Denodo Platform 9.3 release includes further enhancements that strengthen its position as a leading logical data management solution. These improvements focus on providing a more cohesive, secure, and user-friendly experience for managing enterprise-wide data. Enhanced governance capabilities and refined user interfaces ensure that as data access is accelerated, control and security are never compromised.
Actionable Advice for Your Data Strategy
The advancements in Denodo Platform 9.3 offer a clear path forward for organizations struggling with AI data bottlenecks. To leverage these capabilities, consider the following steps:
- Evaluate Your AI Data Pipeline: Identify where your data science teams are currently facing the longest delays. Is it in accessing data from multiple sources, waiting for complex queries to run, or managing data preparation?
- Explore a Logical Data Fabric Approach: Instead of defaulting to building more complex and costly ETL/ELT pipelines, investigate how a logical data management layer can provide a unified, virtualized view of your data. This approach breaks down silos without requiring physical data consolidation.
- Empower Teams with Self-Learning Tools: Equip your data engineers and scientists with platforms that automate the difficult parts of query optimization. An AI-powered engine like DeepQuery reduces the manual burden and delivers superior performance, freeing up valuable human expertise for higher-level tasks.
By embracing an intelligent, logical approach to data management, organizations can finally overcome the data access hurdles that have long hindered AI innovation and pave the way for faster, more impactful business outcomes.
Source: https://datacenternews.asia/story/denodo-platform-9-3-boosts-ai-data-tasks-with-deepquery
