DevStyleR’s Post

We’re heading to the Data Innovation Summit in Stockholm 🇸🇪 Enterprise data teams are under pressure to support AI, real-time analytics, and constant change but most platforms weren’t built to scale architecture, governance, and delivery together. That’s where data automation changes the equation. At Booth C68, we’ll be showing how teams are: Automating data modeling, ELT, and orchestration from metadata Scaling Data Vault 2.0 and dimensional models without rebuilding logic Embedding lineage, auditability, and governance by default Modernizing legacy SQL and on-prem environments into Azure and Snowflake 🎤 Also catch our session: “Turning Data into Decisive Power – Pohjolan Voima Prepares for AI with a High-Quality Data Platform” 📅 May 7 | 11:00–11:20 AM 🎙️ Antti Kajala, CIO, WiseDigi Oy If you’re dealing with slow development cycles, fragile pipelines, or manual rebuilds during modernization, this is worth your time. See you in Stockholm: https://ow.ly/w5jm50YFIIv #DataInnovationSummit #DataEngineering #DataArchitecture #DataAutomation #DataVault #Snowflake #Azure

If you are building your first data lakehouse or rethinking an existing architecture, you cannot miss this session at the Data Innovation Summit 2026! Round of applause for Roland Wammers, Field Architect at MinIO and his presentation on the topic of “One Store to Rule Them All: Apache Iceberg V3 and the sovereign Object-Native Lakehouse.” Roland will explore how MinIO AIStor collapses the traditional divide between object storage and analytical data stores by embedding the full Apache Iceberg V3 Catalog REST API natively into the data layer, a first in the industry. He will cover how this eliminates the overhead of managing separate catalog infrastructure, how it integrates out of the box with Spark, Trino, Dremio, Starburst and others, and why it offers a compelling path for enterprises looking to modernize their lakehouse strategy on-premises with full data sovereignty and without hyperscaler lock-in. Book your tickets because this session will give you a clear picture of what truly unified, high-performance analytical storage looks like in practice. 👉 Don’t miss this session - secure your ticket now and join 3,500+ data, analytics, and AI leaders at DIS2026! https://hubs.li/Q047hBHk0 #DISummit2030 #DIS2026x1

The real question isn’t if you have data...it’s what you’re doing with it. The Big Book of Data Engineering shares practical guidance for modernizing your data platform with Databricks, including how to: • Unify ingestion, transformation, and orchestration with Lakeflow • Build reliable pipelines with observability and data quality built in • Implement CDC and SCD Type 2 in a streamlined lakehouse architecture • Strengthen governance with Unity Catalog while accelerating delivery • Optimize performance and cost across batch and streaming workloads At Bits In Glass, we work with organizations to modernize their data platforms so teams can deliver trusted, production-ready data faster. From scalable pipelines to lakehouse architectures on Databricks, the focus is on building a foundation that supports real analytics and AI outcomes. Read now👇 https://hubs.li/Q048bdY30 #DatabricksPartner #DataIntelligence #DataAndAI

Is your Data Lake becoming a Data Swamp? Storing raw data is no longer enough. In a world that demands instant answers, enterprises are moving toward a Data Fabric—a dynamic, AI-driven architecture that connects siloed information for real-time decision-making. Discover how Ceyoon leverages AI-Augmented Engineering to architect resilient data ecosystems that transform complex information into immediate business value. Read our latest technical insight: https://lnkd.in/gnJ_p47B #Ceyoon #DataFabric #BigData #RealTimeAnalytics #EnterpriseArchitecture #AIEngineering #TechTrends2026 #DataStrategy

Data governance is becoming critical as organizations deal with growing data volumes across multiple platforms. Ensuring data security, access control, lineage, and auditability is no longer optional, it's essential. Join me for a Webinar where I’ll walk through how Databricks Unity Catalog helps implement centralized data governance. #Databricks #UnityCatalog #DataGovernance #AzureDatabricks #DataAndAI

Every data system eventually reaches a point where incremental fixes stop working. What comes next is not another tool, it’s a shift in foundation. Scaling modern data systems requires:  • Unified architecture • Real-time data processing • Scalable pipelines • AI-ready infrastructure This is where platforms like Databricks, combined with the right engineering partner, make the difference. As a Databricks consulting and implementation partner, Goavega works with organizations to move beyond fragmented systems and build scalable, decision-ready data platforms. 🤝 If you're rethinking your data architecture, this is a good place to start: https://lnkd.in/gJkxzCRq [ databricks consulting, data architecture data engineering, real-time data systems, enterprise AI platforms, data transformation ] #Databricks #DataEngineering #DataArchitecture #ArtificialIntelligence #DigitalTransformation #Goavega

Your AI strategy is only as good as your data architecture. You can build a high-performing model, but if the data feeding it is fragmented, poor quality, or slow, the system will fail. In 2026, the real shift is moving from model-centric to data-centric architecture. We achieved a 40% reduction in hallucinations and a 2x increase in reliability by focusing on: • Data Governance: Standardizing schemas and ownership to eliminate metric chaos. • Real-time Pipelines: Using streaming ingestion to ensure models have the latest context. • Entity-level Assembly: Merging data from silos into a single, trusted record before it hits the LLM. Mistake: Treating data as a one-time import. Improvement: Architecting responsibility and quality into the pipeline. #AIEngineering #DataArchitecture #GenAI #DataGovernance #SoftwareArchitecture #TechLeadership #LLM

𝐈𝐂𝐘𝐌𝐈: 𝐖𝐞 𝐛𝐫𝐨𝐤𝐞 𝐭𝐡𝐞 500𝐤 𝐞𝐯𝐞𝐧𝐭𝐬/𝐬𝐞𝐜 𝐛𝐚𝐫𝐫𝐢𝐞𝐫. 🚀 A few weeks ago, we shared a major milestone for #GlassFlow. We’ve rebuilt our architecture to ensure your data pipelines never become your bottleneck. 𝐓𝐡𝐞 𝐡𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭: GlassFlow now scales linearly to 500,000+ records per second! But the best part? It’s horizontal scaling within a single pipeline. You just add resources, and the throughput follows. Simple as that. Read how we achieved this benchmark👇 https://lnkd.in/gNUea3XU #DataEngineering #ClickHouse #RealTimeData #DataLake

AI workloads are inherently distributed, but many enterprise data platforms are not. Building an AI-ready network and data foundation today ensures your strategy can evolve—no matter where your compute lives tomorrow. Before You Scale AI, Fix Your Data Architecture!

Most businesses don't have a data problem. They have data chaos issue. Data is everywhere, but insights are nowhere. 🤷🏻♂️ - Fragmented systems - Slow pipelines - Delayed decisions - Al stuck in experimentation More data won't fix this. A stronger foundation will. ✅ That's where platforms like Databricks, combined with the right engineering approach, help turn fragmented data into unified, intelligent systems.🚀 Explore how Goavega builds scalable data & Al foundations. 🔗Link in the comment section. [ data engineering, databricks consulting, lakehouse architecture, Al data systems, data transformation, enterprise analytics ] #DataEngineering #Databricks #ArtificialIntelligence #DigitalTransformation #Goavega