Nextdata

Last week we showed off Nexdata OS at our co-working space at SHACK15 to some of the most demanding data leaders and practitioners we know, representing data mesh use cases from conventional analytics to generative AI. Many were attending the Data and AI summit, and their feedback was detailed and timely. Here’s what we learned: 1️⃣ Data infrastructure integration of the modern data stack remains a challenge - building a cohesive and end to end experience, across diverse storage, compute, transport, and quality tools using a set of single-feature products as building blocks remains a challenge; data leaders are burnt out doing metal work. 😖 2️⃣ Customers are stuck between the extremes of centralized, single-vendor single-solution, single-experience stacks or building their own from different point products. Both options have material downsides. What most are looking for is a way to hide complexity but still have optionality - a personalized user and data product developer experience, delivered across the arbitrarily complex data estate that typifies most large enterprises, with standardization as the backbone. 🤨 3️⃣ RAG is shiny, but need to clean up the mess first and fast. GenAI and RAG are all the rage, and are under rapid experimentations. There is a chasm to cross from operationalizing democratized data for humans, let alone Generative AIs. While multi-modal data (i.e. used by multiple applications with different modalities) was a winning feature of Nextdata OS, most enterprises have a lot of work to do to make their data products RAG-ready. 😓 We’re deeply grateful for the insight and input into our plans as we take data mesh from conceptual architecture to product reality at scale - both the confirmation of our current approach and the challenges to our thinking.  Thank you to all who participated! Shoutout to Nextdata team for the hard work, their tenacity and curiosity! We are up for fixing the hard parts of data mesh at scale. Happy Friday! ❤️ #datamesh #meshnative #dataproduct

We finally did it! I sat with my friend, Zhamak Dehghani, Creator of Data Mesh on The Ravit Show at the Nextdata Office in San Francisco. Here are the key points we discussed: (Full interview on video) -- State of Data Mesh: We delved into the current state of data mesh and its impact on the industry. -- Motivation: Zhamak shared the gaps and opportunities that motivated the founding of Nextdata. -- Product Development: We explored what Nextdata is building and the innovative solutions they are bringing to the table. -- Current Progress: Zhamak provided an update on where the product stands today and its development milestones. -- Access to the Product: We discussed how people can get their hands on Nextdata's product and start leveraging its benefits. Stay tuned for more insights and developments from Nextdata! #data #ai #nextdata #theravitshow

I caught up with Zhamak Dehghani at a private preview of the Nextdata product showcase... we chatted about how the product has evolved and what's in store for the rest of 2024... enjoy!

Dear Data/AI Executive, You are one of the most courageous leaders of our times —  - you walk into the valley of data transformations, dealing with complexity and unruly data at a scale never seen before;  - you face tremendous expectations to deliver on the promise of GenAI without hesitation;  - you carry the load of years of accumulated brown-field data and legacy technology; and  - you have to make it to the other side with shortages of talent, specialized skill sets, and in this economy, capital. I know many of you, have worked with some of you, and I want to work with more of you on these challenges. If you are on a data democratization / data mesh transformation, my colleagues and I at Nextdata would love to host you and connect you with your peers, for a roundtable discussion on the intersection of data mesh transformation and AI. We’d love to share the first private preview of our platform purpose-built for your kind of journey. ❤️ Joins us on June 11th-12th in San Francisco. https://lnkd.in/g8Z9FYpU

Next(data) Adventure: From Database to Data Mesh After exiting 5 years as VP Engineering/CTO at  ArangoDB working with Databases, Cloud, and Machine Learning, it is time for a new challenge by making Data Mesh a reality with the amazing team at Nextdata. Such changes are equally the best of times and worst of times… Looking back, we really achieved quite a lot, from growing the core database, ArangoGraph, and especially the latest GraphML and Analytic solution. But probably more than all of the products, I will sincerely miss a lot of supersmart people Dr. Frank Celler, Shekhar Iyer , Claudius Weinberger, Michael Hackstein, Max Neunhöffer, Lars Maier, Jan Steemann, and Kaveh Vahedipour just to name a few. Also big kudos to the OSS community whose contributions have made ArangoDB a very special place. On the other hand, I am more than excited to work on turning Data Mesh into reality, and I am sincerely grateful to Zhamak Dehghani for allowing me to join the amazing team at Nextdata! If you are unfamiliar with the idea, I recommend this blogpost (https://lnkd.in/d6KKuGvT )or even the “official book” (https://lnkd.in/dB8wfmgt). DataMesh is an especially exciting topic for me as it combines all my interests and experiences from Systems Engineering, Databases, Analytics, Machine Learning, Data/Container Orchestration, and  Data Platforms into one single product. Not to mention hearing from customers about the impact it has on their infrastructure and productivity! Thanks to all my dear Avocado friends, and stay tuned for more updates from the Nextdata universe!

If you love coding in Rust, passionate about building elegantly designed distributed systems, and deeply care about decentralizing data from quantized LLMs to plain old structured data, and everything in between, I would love you to join our team at Nextdata. DM me or check out https://lnkd.in/eQN6vn8x Jacquelyn Clark #datamesh

During the last few months of my recent 4+ years of experience in leading a team to setup an enterprise-wide, cloud-based data lake platform, the concept of a data mesh started to gain traction in discussions within some of the use cases utilising the platform. I found this concept intriguing, as my initial understanding suggested that the data mesh approach contradicted the conventional centralised data lake model typical of enterprise-wide setups. However, during that period, I lacked the time and resources required to delve deeper into this novel and seemingly revolutionary concept. I decided to devote time to the topic during the last few weeks. I went deep into the topic, and so was motivated to write a book review on Medium 😊 Loïc Giraud, Ramesh Rajamani, Praveen Kumar, Sreedhar Desineni, Omar Pennacchio, Andrea Splendiani, Adrian Heim, Pascal BOUQUET, Tim O'Sullivan, Sampath Srinivasan, Vikas Sindwani, Fang Deng, Marcel Grossert, Omar Khawaja, Reda Berrada, Stephanie McCracken https://lnkd.in/giAz9Dja