BMW i Ventures’ Post

We are excited to be part of Athenic AI's $4.3 million seed round. Founded in 2022, Athenic AI transforms how companies utilize their data by serving as the “central nervous system” of an organization’s data, making analytics easier for everyone. "Athenic is built to be flexible and can work with companies to get its AI to understand company “tribal knowledge”, KPIs or internal terminology so that the AI has the needed context to run proper analytics." https://lnkd.in/gaS9emGg

As the world needs more and more reliable Data, why is it that still so many Data Projects fail? We can say it's clear, Big Tech companies don't like to share the data they have. As our vision is to build a single platform where all the Data is available in structured form, we strive to make Data available to everyone. According to the latest news 60%-85% of all Data driven Projects already fail before they launch, due to cost and a lack of usable data. If you want to dive deeper into the matter, we have a great article for you: https://lnkd.in/ehCYUgjN #AI #Datastartup #Bigdata #Startup #Datadriven #Datamatters

Today, I read the Appen state of AI report , and I had love to share some insights on what I learned about the challenges of managing unstructured data , data pipeline and GenAI. For those who have never heard about 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, think of them as systems that help move data through several steps like 𝐜𝐨𝐥𝐥𝐞𝐜𝐭𝐢𝐧𝐠 , 𝐜𝐥𝐞𝐚𝐧𝐢𝐧𝐠 𝐥𝐚𝐛𝐞𝐥𝐢𝐧𝐠 so that It will be ready for AI models to use. However , as companies move toward GenAI , new challenges arise because as you know those models needs unstructured data ( like 𝐭𝐞𝐱𝐭 , 𝐢𝐦𝐚𝐠𝐞𝐬 , 𝐯𝐢𝐝𝐞𝐨𝐬) instead of structured data ( like 𝐭𝐚𝐛𝐥𝐞𝐬 ). 𝐖𝐡𝐲 𝐝𝐨𝐞𝐬 𝐆𝐞𝐧𝐀𝐈 𝐢𝐧𝐜𝐫𝐞𝐚𝐬𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 ? Structured data is well organized making it easier for anyone to process and extract value from it. But for unstructured data ( also known as 𝐝𝐚𝐫𝐤 𝐝𝐚𝐭𝐚 ) needs way more advanced tools and models to extract the meaning. Since GenAI projects depend on unstructured data , many companies are facing new challenge because most of the traditional data pipelines aren't enough to support these projects. 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐰𝐢𝐭𝐡 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐢𝐧 𝐆𝐞𝐧𝐀𝐈: Appen's report shows companies are struggling with : ---->𝐂𝐨𝐥𝐥𝐞𝐜𝐭𝐢𝐧𝐠 and 𝐜𝐥𝐞𝐚𝐧𝐢𝐧𝐠 unstructured data. ----->𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐢𝐧𝐠 new pipelines that can handle unstructured data. ----->𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 the technical skills to manage these new workflows. 𝐒𝐨𝐦𝐞 𝐤𝐞𝐲 𝐬𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬 𝐟𝐫𝐨𝐦 𝐀𝐩𝐩𝐞𝐧'𝐬 𝐫𝐞𝐩𝐨𝐫𝐭: -->𝐃𝐚𝐭𝐚 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲 has 𝐝𝐫𝐨𝐩𝐩𝐞𝐝 by 𝟗% over the past four years. -->𝐃𝐚𝐭𝐚 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 issues have 𝐢𝐧𝐜𝐫𝐞𝐚𝐬𝐞𝐝 by 6% since 2023. -->𝐆𝐞𝐧𝐀𝐈  adoption 𝐠𝐫𝐞𝐰 𝐛𝐲 𝟏𝟕% in the past year, with 56% of surveyed companies implementing GenAI use cases. 𝐌𝐲 𝐢𝐧𝐬𝐢𝐠𝐡𝐭 : Since most of the companies are leaning to GenAi projects and traditional pipelines that handle structured data aren't enough for today's use cases. But does this mean we will stop working with structured data altogether ? or maybe new AI tools will emerge to automate the traditional data pipelines for easier integration ? Feel free to share your thoughts on the future of GenAI and how companies will evolve their pipelines! #AI #DataScience #GenAI #DataPipelines #DataManagement #UnstructuredData #DataEngineering #GenerativeAI #DataQuality #DigitalTransformation

BREAKING NEWS! Revefi Secures $20M to Revolutionize Data Engineering, Improve ROI with AI https://lnkd.in/gB8qBTjM #AI Revefi

𝗗𝗮𝘁𝗮 𝗗𝗲𝗺𝗼𝗰𝗿𝗮𝘁𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝘁𝗵𝗲 𝗮𝗴𝗲 𝗼𝗳 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 I've long been convinced that there's an untapped opportunity to dramatically increase the ease of access and speed to high-quality data insights across the organization. With the advancement of LLMs there's a clear 𝘞𝘩𝘺 𝘕𝘰𝘸, and we’ve met many founders over the past 18 months rushing to build and innovate in this space. There are clear opportunities that have emerged with the technology, to name a few: 𝟭. 𝗡𝗮𝘁𝘂𝗿𝗮𝗹 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲𝘀: Simplifies data interaction, making insights accessible without technical knowledge. 𝟮. 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗦𝗰𝗵𝗲𝗺𝗮 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴: Leverages unstructured data for better schema comprehension and documentation. 𝟯. 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲𝘀: AI-driven dialogues help refine data queries for non-technical users. This might be predictable, but IMO some of the biggest challenges are GTM and organizational behavior related: 𝟭. 𝗚𝗧𝗠 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Balancing between supplementing and replacing data teams. 𝟮. 𝗣𝗮𝗶𝗻 𝘃𝘀. 𝗕𝘂𝗱𝗴𝗲𝘁 𝗔𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁: Identifying the right stakeholders and budget sources. 𝟯. 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗼𝗳 𝗗𝗮𝘁𝗮 𝗦𝗰𝗵𝗲𝗺𝗮𝘀: Achieving accurate schema mapping. 𝟰. 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗖𝗵𝗮𝗻𝗴𝗲: Encouraging users to adopt new AI-driven methods over traditional ones.  Founders and builders exploring in this space - what you're seeing and experiencing? Full post here: https://lnkd.in/gEdQPciw #data #LLM #genAI #GenerativeAI

Whether you’re a student, entrepreneur, or data enthusiast, #LumenoreGrow makes data insights accessible to all. Our enterprise-grade platform, trusted by thousands, is now available at #zerocost — packed with AI, ML, and GenAI tools to turn your questions into actionable insights. No complex setup, just connect your data, ask questions, and start making smarter decisions. Learn more about Lumenore Grow in this blog: https://lnkd.in/dxKEJbBt #startforfree #Signup #FreeSignup #FreeTrial #LumenoreAnalytics #Lumenore #AdvancedAnalytics #DataInsights

🌟 Highlights from the Evanta CDAO Town Halls! 🌟 🔍 "How do I get my data AI-ready?" was the burning question. Here are five quick takeaways: - Governance is Crucial for AI success. -  Define AI Use Cases to align tech with business needs. - Ease POC to Production transitions to scale solutions. - Shift Culture around data governance from roadblock to enabler. - Prioritize Continuous Learning to keep pace with evolving AI technologies. 🚀 Transforming your organization for AI readiness requires clean, governed, and actionable data. Ready to deep dive into these insights? Check out our full blog. #AI #DataGovernance #EvantaCDAO #DataStrategy #BusinessIntelligence

🌟 Highlights from the Evanta CDAO Town Halls! 🌟 🔍 "How do I get my data AI-ready?" was the burning question. Here are five quick takeaways: - Governance is Crucial for AI success. -  Define AI Use Cases to align tech with business needs. - Ease POC to Production transitions to scale solutions. - Shift Culture around data governance from roadblock to enabler. - Prioritize Continuous Learning to keep pace with evolving AI technologies. 🚀 Transforming your organization for AI readiness requires clean, governed, and actionable data. Ready to deep dive into these insights? Check out our full blog. #AI #DataGovernance #EvantaCDAO #DataStrategy #BusinessIntelligence

🌟 Highlights from the Evanta CDAO Town Halls! 🌟 🔍 "How do I get my data AI-ready?" was the burning question. Here are five quick takeaways: - Governance is Crucial for AI success. -  Define AI Use Cases to align tech with business needs. - Ease POC to Production transitions to scale solutions. - Shift Culture around data governance from roadblock to enabler. - Prioritize Continuous Learning to keep pace with evolving AI technologies. 🚀 Transforming your organization for AI readiness requires clean, governed, and actionable data. Ready to deep dive into these insights? Check out our full blog. #AI #DataGovernance #EvantaCDAO #DataStrategy #BusinessIntelligence

🌟 Highlights from the Evanta CDAO Town Halls! 🌟 🔍 "How do I get my data AI-ready?" was the burning question. Here are five quick takeaways: - Governance is Crucial for AI success. -  Define AI Use Cases to align tech with business needs. - Ease POC to Production transitions to scale solutions. - Shift Culture around data governance from roadblock to enabler. - Prioritize Continuous Learning to keep pace with evolving AI technologies. 🚀 Transforming your organization for AI readiness requires clean, governed, and actionable data. Ready to deep dive into these insights? Check out our full blog. #AI #DataGovernance #EvantaCDAO #DataStrategy #BusinessIntelligence