How data lakes will transform AI engineering by 2025

AIStor Tables unifies data for the AI Enterprise, bringing structured and unstructured data into a single, object-native platform. All enterprise data in one Iceberg-native foundation for smarter analytics and AI. This is the bridge from today’s analytics to tomorrow’s AI. Apache Iceberg | #DataStore #Iceberg #AIStor #AI

This isn’t just about storage it’s about creating the bridge between today’s analytics and tomorrow’s AI, with Iceberg as the backbone. With the convergence of data lakes, analytics, and AI, MinIO’s move is especially exciting creating a unified foundation that seamlessly integrates structured and unstructured data into one powerful platform. #AIStor #MInIO #Analytics #iceberg #Datalake #datalakehouse #lakehousekeeper

🌟 New Blog Just Published! 🌟 📌 Riverbed Speeds Up AI Data Transfer 🚀 ✍️ Author: Hiren Dave 📖 AI model training today depends on massive data sets that often sit in isolated silos. Consequently, moving terabytes between storage tiers introduces days of latency, and in extreme cases months of..... 🕒 Published: 2025-10-17 📂 Category: AI/ML 🔗 Read more: https://lnkd.in/d7Q9TBcY 🚀✨ #aidatatransfer #riverbedspeed #databottlenecks

Is your data holding back your AI ambitions? Many enterprises struggle to prepare their complex data ecosystems for artificial intelligence. EXLdata.ai is the first-of-its-kind agentic AI-native suite of data solutions built to solve this exact challenge. It unifies your disparate systems, making both structured and unstructured data ready for AI. Learn more: https://bit.ly/475bZDQ

Scale data monitoring without scaling your workload 📈 Our new Bulk Anomaly Detection makes it easy to set up AI-powered monitoring across all your key data warehouse tables in just a few clicks. Now you can: ✔️ Achieve comprehensive data quality coverage in minutes ✔️ Be the first to know if something goes wrong through continuous monitoring of freshness, volume, and schema anomalies ✔️ Ensure reliability at scale without the manual setup 👉 Learn more in the latest release: https://lnkd.in/g_w6ph_2  #DataHub #AI #DataQuality #DataOps #DataEngineering #ProductRelease

🚨New Blog Alert! Perficient’s latest blog explores the recent acquisition of Tecton by Databricks, a strategic move that signals major momentum in the AI agent space. The article breaks down what this means for the future of data platforms and how Perficient is uniquely positioned to help clients integrate, optimize, and scale with these enhanced capabilities. 💪 📖 Read the full blog here: https://lnkd.in/e55pznSa #Databricks #Tecton #AI #DataPlatforms #Perficient #DigitalTransformation #AgentBricks

AIStor Tables unifies data for the AI Enterprise, bringing structured and unstructured data into a single, object-native platform. All enterprise data in one Iceberg-native foundation for smarter analytics and AI. This is the bridge from today’s analytics to tomorrow’s AI. #DataStore #Iceberg #AIStor #AI

AIStor Tables unifies data for the AI Enterprise, bringing structured and unstructured data into a single, object-native platform. All enterprise data in one Iceberg-native foundation for smarter analytics and AI. This is the bridge from today’s analytics to tomorrow’s AI. #DataStore #Iceberg #AIStor #AI

🧠 Traditional Databases vs. Vector Databases — The Foundation of AI Search Traditional databases built the web we use today — structured, reliable, and rule-based. But in the age of AI, vector databases are redefining how machines understand context, relationships, and intent. In this blog, we explore: 🔹 Why traditional databases struggle with semantic understanding 🔹 How vector embeddings capture relationships between concepts 🔹 The core differences between relational and vector data systems 🔹 Why the future of AI search lies in hybrid intelligence Read the full blog 👇 🔗 https://lnkd.in/dTRmDCH7 #AI #Databases #VectorSearch #MachineLearning #DataScience #ArtificialIntelligence #Innovation #SemanticSearch #RAG #MachineLearning #DataInfrastructure #Invowork

🚀 Are you ready for the next big challenge in machine learning? As we approach 2026, the deployment of machine learning models is becoming increasingly critical for businesses to stay competitive. What are some of the biggest hurdles you're facing when it comes to deploying your models? Is it production scalability, integration with existing systems, or perhaps real-time data processing? Let’s discuss the strategies we can implement to navigate these challenges effectively. Share your thoughts and experiences below! #MachineLearning #AI #ModelDeployment #DataScience #TechTrends #2026Goals #Innovation ---