Nextdata

Join Zhamak Dehghani, founder and CEO of Nextdata, as we look back on the key moments that shaped 2024 in data management and explore what’s ahead in 2025 ?? From the rise (and challenges) of generative AI to shifts in how companies approach their tech stacks, we cover the biggest trends and challenges that shaped the data ecosystem over the past year. Here’s what we cover: ?? Generative AI's Impact: Why GenAI surged in 2024, the challenges it exposed in data platforms, and what’s needed to support scalable AI workflows in the future. ?? Modern Data Stack Realities: The gap between the modular promise and the fragmented reality—and how an "hourglass model" could bring balance. Budget Pressures and DIY Platforms: How economic pressures reshaped buying habits, leading to DIY efforts and their pitfalls, and what organizations are now prioritizing. ?? What’s Ahead in 2025: The trends we’re tracking and how we’re simplifying data infrastructure to unlock new opportunities for teams. Let us know your thoughts in the comments below- we’d love to hear from you! Check out the full writeup on this conversation on our blog: https://hubs.ly/Q030PvlQ0

Data migrations often fail for three reasons: 1?? ???????????????? & ?????????????????? ?????????????????? ???????? ?????????????????? ??????????????????: Migrations are often driven by executive mandates, vendor incentives, or cost-saving strategies rather than actual technical needs. When leadership prioritizes deals over usability, migrations fail to deliver value. 2?? ?????????????????? ???????? ?????? ??????????????????: Data consumers will find and use the most accessible data, regardless of migration efforts. If legacy systems remain more useful, users will bypass new platforms, leading to shadow IT, duplication, and failure to retire old systems. 3?? ???????? ???? ???????????????? ???????????????????????? ???????? ?????????? ???????? ???????? ????????????????: Unlike transactional systems, data stacks don't have interoperability standards that abstract platform differences, so migrations are much more cumbersome. Vendor lock-in, data gravity, and infrastructure complexity also hinder success. In the clip below, Nextdata's Head of Product Engineering, Sina Jahan explains how to break the cycle by converting your existing data into decentralized, autonomous data products. Learn how this approach keeps your data accessible, minimizes disruption, and eliminates migration headaches for good. (Link to full video and blog in the comments) ?? #DataMesh #AutonomousDataProducts #DataMigration

?? Thrilled to announce our DataEngBytes Sydney 2025 Keynote Speaker: Zhamak Dehghani! The creator of Data Mesh and founder of Nextdata will present "Data Products Done Right: Decentralized, Simple and Secure" - a groundbreaking session on transforming data management in the era of GenAI. Join us to learn: - A new operating model for data management - Implementation of federated computational governance - Real-world case studies from Fortune 100 companies - The future of data mesh and GenAI Don't miss this exclusive opportunity to learn from one of the most influential voices in data architecture. #DataEngBytes #DataMesh #DataEngineering #DataArchitecture #Tech #Sydney

Data migrations can be an endless source of stress and frustration. Just ask any data engineer or architect: a project that seems simple at the outset can extend for months or even years, growing in complexity with thousands of intertwined processes, state-of-the-art tools, and too many stakeholders, and yet it may still fall short of expectations. In our latest video, Nextdata's Head of Product Engineering, Sina Jahan, shares how vendor politics, data gravity, and legacy inertia make migrations so painful. Instead of endless re-platforming, learn how converting your assets into decentralized, autonomous data products can unlock modern capabilities without disruption. Check out the writeup & video on our site: https://hubs.la/Q039PrtB0 Got a data migration war story to share? Drop us a line in the comments! ?? #DataMesh #AutonomousDataProducts #NextdataOS

??Autonomous Data Products: The Backbone of Scalable RAG Applications Data quality issues, outdated embeddings, and governance headaches make enterprise RAG applications hard to scale. But what if your data could manage itself? In this clip, J?rg Schad , Ph.D. explains how autonomous data products solve these challenges by ensuring data integrity, orchestrating inputs dynamically, and delivering multi-modal outputs. With MeshRAG, data products don’t just store information—they enforce quality, stay synchronized, and serve the right format for every use case. That means better AI results, fewer broken pipelines, and governance built-in from the start. Learn more about autonomous data products and MeshRAG on our blog: https://hubs.la/Q034V5ZG0

We’re excited to share Nextdata CEO, Zhamak Dehghani’s recent appearance on The Tech Icon podcast! In this short clip, Zhamak reveals the “hourglass of data innovation,” a model that provides autonomy to different business domains through standardization of data products across data stacks, applications and organizational boundaries. On the Bottom: Data stored across a diverse collection of storage infrastructure and data stacks, often "owned" by different operating units At the Top: An increasingly complex collection of tools and applications serving unique data scenarios for analytics, ML and Gen AI In the Middle: a narrow waist of abstraction to allow interoperability across diverse data sources and applications By blending just enough standardization and a flexible, multi-modal concept of data products, data engineers can sidestep the bottleneck of wholly centralized, monolithic data teams and respond to the diversity of application and tooling requirements. https://hubs.la/Q037tX9l0

?? Mark your calendars for Data Mesh Live, the #1 conference dedicated entirely to #DataMesh, happening in Antwerp this June! We’re happy to announce that our very own J?rg Schad , Ph.D., Head of Engineering at Nextdata, will be delivering Data Mesh Live's keynote on transitioning from legacy data stacks to an operational Data Mesh in today’s GenAI and ML-driven world. During his keynote, J?rg will dive into: ?? Common hurdles and traps teams encounter while adopting Data Mesh ??Hacks and workarounds that derail large-scale implementations ??A holistic solution that helps organizations gain the necessary “escape velocity” to realize decentralized data at scale Attendees will also hear from Data Mesh experts covering everything from Data as a Product and automated federated governance to AI-driven insights and real-world implementation strategies. ?? When: June 5-6, 2025 ?? Where: Antwerp, Belgium ??? Tickets: https://lnkd.in/ggDhBwzN Looking forward to seeing you all and sharing data mesh tips, and maybe some chocolates too! ?? #DataMeshLive #DataEngineering #AI #GenAI #ML #Nextdata #DataManagement #Conference #DataProduct #DataMesh cc: Tom De Wolf, Data Mesh Learning Community, Andrew Jones, Jacek Majchrzak, Kiran Prakash, Karin H?kansson, Dr. Simon Harrer, Prof. Dr. Arif Wider, Kinda El Maarry, Ph.D., Emma Houben, Andrea Gioia, Jean-Georges Perrin, Rachel Barton, Jochen Christ

How do you build a data platform that scales without breaking under legacy constraints? On this episode of Born In Silicon Valley by Match Relevant, Nextdata CEO Zhamak Dehghani discusses her journey as a solo founder and how she reimagined data management through the lens of autonomy and decentralization. From containerizing the data stack to enabling data products that are discoverable and governable, she reveals the practical steps behind her breakthrough approach. #datamesh #dataproducts #decentralizeddata #nextdata

What if your data platform worked like an operating system - one that abstracts complex processes and empowers you with simple, composable functions? In the clip below, Zhamak Dehghani shares how Nextdata OS converts cumbersome data workflows into agile, self-governing data products that autonomously manage the entire data lifecycle—from creation to deployment and governance. #DataMesh #AutonomousDataProducts #DataInnovation #Nextdata

We’re excited to share Nextdata CEO, Zhamak Dehghani’s recent appearance on The Tech Icon podcast! In this short clip, Zhamak reveals the “hourglass of data innovation,” a model that provides autonomy to different business domains through standardization of data products across data stacks, applications and organizational boundaries. On the Bottom: Data stored across a diverse collection of storage infrastructure and data stacks, often "owned" by different operating units At the Top: An increasingly complex collection of tools and applications serving unique data scenarios for analytics, ML and Gen AI In the Middle: a narrow waist of abstraction to allow interoperability across diverse data sources and applications By blending just enough standardization and a flexible, multi-modal concept of data products, data engineers can sidestep the bottleneck of wholly centralized, monolithic data teams and respond to the diversity of application and tooling requirements. https://hubs.la/Q037tX9l0