data.world

Design thinking meets Generative AI! 🚀 Dive into our article in ITPro Today from data.world's very own, Jason Guarracino on how design thinking can transform the development of Generative AI products. Read on: https://hubs.li/Q02H8pxj0

Juan Sequeda's session at #CDOIQ2024 yesterday was a hit! ⭐ A big thank you to Juan and all the attendees for an engaging session and discussion. We’d love to hear your thoughts and key takeaways—share in the comments below! If you attended the session and want to dive deeper into what data.world has to offer, learn more here: https://hubs.li/Q02H6-hX0

A fantastic #HonestNoBS Dinner in Boston during CDOIQ. The takeaways: 👍 What’s working  - Easy to get ideas of new ways to drive value with data  - Knowing the business of the business  - AI hype is helping because it can be seen as a catalyst to focus on data and focus on the stuff we care about. But also a distraction  - In addition to Business Reviews, let’s have Business Forwards. Need to talk about what’s going forward - OODA loop: Observe Orient Decide Act  - Make the execs look better. But how do we find that out faster?  - Executives being specific about what they care about. Sometimes it happens if they get into an embarrassing situation because they lacked specific information - Asking: What do you know and don’t know about X? What can you know?  - Never waste a crisis. Something goes wrong. Take advantage - Investing in metadata, protocols, standards within an industry. Describe how to exchange the data that is generated automatically.  Why? Cost reduction. Also if you share bad data, then you look bad - Have the data workshop during the executive planning. Not just OKRs but also art of the possible and the hypothesis we want to test  - Focus on data processing, shift left. Analytics is post processing. However, native tech companies' learnings are not always applicable to everyone - Let business build their own thing, and have them follow a process - Data lineage 👎 What’s not working.  - Activating and executing the ideas to drive value - Change is hard. Are people afraid of change because of accountability? No one wants to be responsible if it goes bad  - Culture is hard. Divide between tech and biz - Buy in is hard, even if the ideas are good and show apparent value  - People are scared. The data they have today is the constant. People who can’t reproduce the number twice, are accountable - There is no clear vision/north star. Where do we want to go? “Our direction was directionless” - Data strategy lacking visibility of business strategy “We have a new strategy. It includes AI. But not data”  - A culture of “print the dashboard”/“report as pdf”. We should understand why that ask? Lack of trust. Want it printed because they want the evidence in case the numbers change. Need to meet people where they are.  - Clear high level mission of the organizations but it may not connect with the “rank and file” - People don’t know what they are looking for - Not being open minded. On metrics: I don’t care if it’s wrong. I want a discussion.  - Defining what X means - One mistake now the perception is that all data is bad - Hide behind industry norms "No one does this well" so why do you want to be in second place? - Implement transaction systems and the biz doesn’t even know what’s in the system - Putting tech in before identifying the problem - Blueprints aren't valuable until the bridges fall down, and you don’t want to be on the bridge when it falls down. Favorite quote: “Sometimes buying in requires letting go”

What a great start to the day at #CDOIQ2024! 🎉 Our session, "From Data to Governed Decisions with AI," was a success thanks to our amazing speakers Patrick McGarry (data.world), Justin Magruder (SAIC), Ren Essene (Consumer Financial Protection Bureau), and Dessa Glasser (Global Legal Entity Identifier Foundation (GLEIF)). Don’t miss this afternoon's session with Juan Sequeda (data.world) on "Knowledge Graphs as a Requirement for AI Ready Data and LLM Accuracy." It's a must attend—make sure to add it to your calendar! 📅 View session details and add it to your schedule: https://hubs.li/Q02GYw-R0

Excited to be back CDOIQ again. I'm giving a talk on Wednesday and the takeaway is: Invest and treat knowledge as a first class citizen (the WHAT) But Why? 1. Because we are doing the same thing over and over again (more data, more tech) and expecting different results. That's Einstein's definition of insanity.  2. We need to find a balance between efficiency and resilience in order to address the known use cases of today (efficiency) and the unknown uses cases of tomorrow (resilience)  3. Operational Efficiency: by being efficient and resilient, we can reduce cost, improve productivity, be agile and flexible to deal with those unknown use cases, optimize resources But haven't we been already been investing in knowledge? 1. Yes, but by chance: we find issues when folks complain 2. Yes, but in an ad-hoc manner: it's not someones dedicated task  3. Yes, but inconsistent investment: ups and downs to deal with data quality But why NOW?  Simple: (Gen)AI! This is an opportunity to ride the hype, in order to address the pains we've been constantly been complaining about. If it's not now, then when??? How do you address the trust issues for AI: Accuracy, Explainability and Governance? By investing in Knowledge! How to treat knowledge as a first class citizen? People, Process and Technology, of course :) - Tech: Knowledge Graphs! Your first knowledge graph is your data catalog which brings together the technical and business metadata, building the brain of your organization. Our lab has been pioneering the research on studying how to use Knowledge Graphs to increase LLM accuracy, specifically for structured data. So if the "why now" is (Gen)AI, then this is the motivator to invest in knowledge graphs which provides the context of your organization.   - Process: Follow a methodology. Success is defined by business questions, not technical questions. I'll be talking about our Pay as you go methodology and Iron thread approach.  - People: Have the right people in the room: Business, Data and .. Knowledge Engineers! I'm also excited to host another #HonestNoBS dinner Wednesday night. It's going to be 6 months since we did the last one so it will be great to see how the data world has changed in the last half year. If you are not aware of these dinners, check out the report I wrote about the dinners I hosted in 2023. We can possibly squeeze a few more folks in, so if you are a data leader/executive and want a dinner under chatham house rules, comment below or ping me directly. Links in comments

Unlock the power of decentralized data management with data mesh implementation. This innovative approach breaks down data silos, boosts data access, and accelerates decision-making across your organization. Here's how to get started: https://hubs.li/Q02GNtgW0 Author: Liz Elfman

Join us at #CDOIQ2024 on Wednesday for a deep dive into agile data governance and GenAI! 🚀 In Session 9-A: "From Data to Governed Decisions with AI," you'll learn from industry experts Patrick McGarry (data.world), Ren Essene (Consumer Financial Protection Bureau), Dessa Glasser (Global Legal Entity Identifier Foundation (GLEIF) and Justin Magruder (SAIC) about: 👉 Maintaining data quality 👉 Meeting regulatory standards 👉 Reducing bias in AI 👉 Ensuring security in AI outcomes 🗓️ Wednesday, July 17 | 8:30 am – 9:15 am Don’t miss this essential discussion. Add the session to your calendar here: https://hubs.li/Q02GzN7M0

Exciting to see that folks are speaking our language! Thanks for the mention Neo4j 🚀 Check out our recent benchmark study cited in the blog post: https://lnkd.in/epJMkBQa

In the dynamic realm of content creation, where AI meets human ingenuity, it's still the human collaboration that helps spin raw thoughts into gold and bring words to vivid life. The process of creation involves blending human intuition with AI innovation to create something truly magical. Read on: https://hubs.li/Q02GnSBR0 Author: Jason Guarracino

🚀 Transform your public sector AI! Join data.world and Hakkōda on July 31st for an exclusive webinar. Hear from Patrick McGarry, GM Federal at data.world, and Eric Barton, Director of Data Enablement at Hakkōda, as they cover: 🔹 Improving data governance strategies 🔹 Optimizing your data infrastructure 🔹 Enhancing data quality and enrichment 🔹 Advancing your AI initiatives, even if you haven't started Don't miss this chance to learn from the best in the industry. Register now! 🗓️ July 31st 📍 Register here: https://hubs.li/Q02GdB6w0