datagusto

🚀 We were thrilled to attend the Plug and Play Japan event! It was an incredible opportunity for Datagusto to pitch our vision and connect with such a diverse, dynamic audience. Engaging with fellow innovators, industry leaders, and professionals from all backgrounds made it an inspiring experience. The day was filled with invaluable insights from those who have walked the journey—hearing speakers openly share both the triumphs and challenges they’ve faced was a great reminder of the grit and resilience behind every successful venture. A huge thank you to Plug and Play Japan for hosting such a fantastic event. We’re energised and excited to keep pushing forward with new connections and fresh perspectives! #PlugAndPlayJapan #Datagusto #Innovation #Data #Networking #Inspiration

🚀 Exciting News from Datagusto! 🚀 We’re thrilled to share that we’ve just published a new blog post exploring the future of Datagusto’s Data Catalogue—our latest innovation in data management! 🌐📊 The Datagusto Data Catalogue is more than just a collection of data—it’s an intelligent system designed to help you manage, monitor, and gain valuable insights from your data, all in one place. Key features include: ✅ AI-powered business metadata generation ✅ Real-time data quality monitoring ✅ Proactive issue identification and resolution While it’s still evolving, Datagusto's Data Catalogue is on track to become an indispensable tool for data-driven businesses. Check out the blog to learn more about its current capabilities, limitations, and future prospects! 👉 Read the full blog here: https://lnkd.in/e_xwASYx We’d love to hear your thoughts! Comment below and let us know how this innovation could help your business. 💬

Confessions of a Data Startup Founder: 𝗧𝗵𝗲 𝗦𝗰𝗵𝗲𝗺𝗮 𝗦𝗵𝗶𝗳𝘁 𝗡𝗶𝗴𝗵𝘁𝗺𝗮𝗿𝗲 Late nights, endless coffee, and the constant fear of waking up to broken pipelines. Sound familiar? You're not alone. As I shared my fear of broken pipelines with our Technical Advisory Board about our latest data pipeline meltdown, I realized something: This isn't just our problem. It's an epidemic. The Schema Shift Saga: A Startup's Silent Killer 1. The Shocking 6%: We discovered that 6% of data pipelines break regularly due to third-party vendors changing schemas without warning. That's 1 in 17 pipelines crashing because someone, somewhere, decided to tweak their data structure. 2. Validation in Numbers: We reached out to our network, desperately seeking answers. The response? A chorus of "Us too!" Third-party vendor changes are the bane of our collective existence. https://lnkd.in/e858HNzY 3. Reddit Therapy Sessions: Late-night scrolling through Reddit threads felt like group therapy. Data engineers worldwide are in the same boat, battling the unpredictable tide of schema changes. https://lnkd.in/epx2zWhv 4. You Are Not Alone: To every founder/ engineer/ architect (you all know you are) who's felt that pit in their stomach when a critical pipeline fails - we feel you. This isn't a "you" problem. It's an "us" problem. 5. The Name of Our Nemesis: We've dubbed it "schema drift" or "schema shift". Giving it a name somehow makes it feel less insurmountable. A Call to Arms: Fellow data/ startup warriors, it's time we talked about this. How many sleepless nights have you had because of schema drift? How has it impacted your growth, your customer relationships, your sanity? Share Your Battle Scars: We're building a community of resilience. Drop a comment with your schema shift story. Let's turn our collective frustrations into fuel for innovation. Remember, in the world of data startups, you're not just building pipelines. You're building the future. And you're not doing it alone. Let's follow up tomorrow! #StartupStruggle #SchemaDriftSurvivors #DataPipelineProblems #YouAreNotAlone #datagusto #data #pipelines #dataengineer #developer #dataarchitect #datascientists #analysts

Confessions of a Data Startup Founder: 𝗧𝗵𝗲 𝗦𝗰𝗵𝗲𝗺𝗮 𝗦𝗵𝗶𝗳𝘁 𝗡𝗶𝗴𝗵𝘁𝗺𝗮𝗿𝗲 Late nights, endless coffee, and the constant fear of waking up to broken pipelines. Sound familiar? You're not alone. As I shared my fear of broken pipelines with our Technical Advisory Board about our latest data pipeline meltdown, I realized something: This isn't just our problem. It's an epidemic. The Schema Shift Saga: A Startup's Silent Killer 1. The Shocking 6%: We discovered that 6% of data pipelines break regularly due to third-party vendors changing schemas without warning. That's 1 in 17 pipelines crashing because someone, somewhere, decided to tweak their data structure. 2. Validation in Numbers: We reached out to our network, desperately seeking answers. The response? A chorus of "Us too!" Third-party vendor changes are the bane of our collective existence. https://lnkd.in/e858HNzY 3. Reddit Therapy Sessions: Late-night scrolling through Reddit threads felt like group therapy. Data engineers worldwide are in the same boat, battling the unpredictable tide of schema changes. https://lnkd.in/epx2zWhv 4. You Are Not Alone: To every founder/ engineer/ architect (you all know you are) who's felt that pit in their stomach when a critical pipeline fails - we feel you. This isn't a "you" problem. It's an "us" problem. 5. The Name of Our Nemesis: We've dubbed it "schema drift" or "schema shift". Giving it a name somehow makes it feel less insurmountable. A Call to Arms: Fellow data/ startup warriors, it's time we talked about this. How many sleepless nights have you had because of schema drift? How has it impacted your growth, your customer relationships, your sanity? Share Your Battle Scars: We're building a community of resilience. Drop a comment with your schema shift story. Let's turn our collective frustrations into fuel for innovation. Remember, in the world of data startups, you're not just building pipelines. You're building the future. And you're not doing it alone. Let's follow up tomorrow! #StartupStruggle #SchemaDriftSurvivors #DataPipelineProblems #YouAreNotAlone #datagusto #data #pipelines #dataengineer #developer #dataarchitect #datascientists #analysts

We are in!!! 🥳 We are honoured and very grateful to have been selected for this amazing opportunity to be a part of the Austin Texas Cohort, Beyond Japan 2024! We look forward to meeting and connecting with everyone in Austin! 🎉🎊

Happy Friday All! Data Engineering: What we think matters VS. What really matters Many data teams get lost in complex ETL processes and fancy tools. But the real challenges are keeping your pipelines running and your data reliable. So, focus on just two things: 1️⃣ Schema Stability: Track how often your pipelines break due to unexpected schema changes 2️⃣ Data Trust Score: Measure % of users who would be "very confident" in making decisions based on your data Got a schema stability >95% or a data trust score >80%? Congratulations, you're building a solid data foundation! The truth is, fancy tools won't save you if your basics aren't solid. Here's what really matters: - Detecting schema changes before they break your pipelines - Understanding data lineage across your entire ecosystem - Balancing automation with human oversight Remember, it's not about having the most advanced tools. It's about having reliable data that your team can trust and use. 𝗪𝗵𝗮𝘁'𝘀 𝘆𝗼𝘂𝗿 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗱𝗮𝘁𝗮 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲? Share in the comments! #DataEngineering #SchemaManagement #DataQuality

AI-Driven Schema Evolution: Adapting to Change in Real-Time As AI models evolve, so do the data schemas that feed them. Traditional rigid data pipelines often break under the strain of frequent schema changes, hampering AI development. Enter AI-driven schema evolution - a game-changer in data management. By leveraging machine learning to predict and adapt to schema changes, we can create resilient data pipelines that evolve with our AI models. This approach not only reduces downtime but also accelerates the AI development cycle. Embracing AI-driven schema evolution is key to staying agile in the fast-paced world of artificial intelligence.