LightsOnData

What's your favorite conference swag? Here are some that we picked up in London. 👇 Backpacks, pens, data-themed toys, and unique gadgets, culminating with a special giveaway from Acceldata and prize from Dell Technologies. Check out the full video for a fun look into the latest in big data conference swag!

I had the pleasure to talk to Lee Larter and Jay Limbasiya about what's new at Dell Technologies and their partnership with NVIDIA. We talked about: 💡 Dell's AI Factory, a reference architecture designed to drive business innovation across various industries by leveraging AI technologies. 💡 The factory's core component is its ability to ingest and manage data through an open Lakehouse architecture, enabling effective data utilization. 💡 The importance of making data accessible and rich for AI solutions ... and much more Checkout the full interview to learn more about the seamless integration of AI to transform data into actionable insights for optimized business outcomes. Until next time, let's keep putting the LightsOnData.

Thrilled to share my latest interview from IBM’s #ThinkToronto with Humza Teherany, Chief Strategy, and Innovation Officer at MLSE (Maple Leaf Sports & Entertainment Partnership). Discover how they're leveraging technology to enhance fan experiences and drive business growth.    Highlights include: ➡️ Fan-Centric Innovation: Bridging the gap between tradition and tech. ➡️ AI in Sports: Enhancing team engagement and athletic performance. ➡️ Tech-Enabled Events: Crafting unforgettable experiences at every game and concert. Tune in for insights on the intersection of sports, technology, and fan engagement! Let's keep putting the Lights On Data.   #IBMCanada

How learning to effectively implement Data Governance can potentially save millions by avoiding costly Data Governance mistakes Funding a data governance program is far less expensive than the penalties organizations can face for poor data quality and internal controls. For example, a typical enterprise data governance program costs between $2 to $4 million per year. Compare that to a bank that was fined $136 million for failing to fix long standing data issues, Totaling $536 Million since 2020, that could have been avoided by implementing an effective data governance program. I’m excited to share that I’ve recently completed the “Practical Data Governance Implementation https://lnkd.in/gku86nCG course from LightsOnData. This hands-on course covers all aspects of successfully implementing a data governance program, from basic concepts to practical tools and strategies. This course highlights exactly how to avoid such costly mistakes by guiding you through every step of establishing and managing a data governance framework. Here's a breakdown of the key insights: 1. Pre-Implementation Steps: Preparing for Success Before diving into program development, initial assessment is critical. The course outlines key steps such as understanding the business drivers for governance and conducting an ad-hoc assessment. You also need to map out data sources and flows within your organization—a task made easier with templates provided in the course. Another essential element is getting buy-in. Without organizational support, even the best-designed governance programs fail. This means creating a strong business case, highlighting the return on investment, and securing a high-level sponsor to champion the initiative. 2. Setting Up the Data Governance Program Once the groundwork is laid, the course guides you through the actual setup. Defining the scope of your program, establishing guiding principles, and designing an organizational framework are all crucial. The Data Governance Council plays a vital role here, ensuring decisions are made and communicated effectively across departments. Data stewards are identified and assigned, providing ownership and accountability to data-related processes. The program also highlights the importance of focusing on data domains and building a governance model aligned with business goals. 3. Metrics, Policies, and Tools A key takeaway from the course is the importance of developing metrics and KPIs that align with your governance goals. Measuring the effectiveness of your governance efforts is critical for continuous improvement. Additionally, policies, standards, and workflows are developed to ensure consistency in how data is handled. The course also touches on selecting and deploying the right tools to manage data governance effectively. Many thanks LightsOnData and George Firican for the wonderful course

I get asked this A LOT: "How do you measure success for Data Governance?" Well, there are 2 types of metrics that you need to track: 1️⃣ Progress metrics and 2️⃣ Impact metrics Checkout this white paper that offers some insight into the progress metrics. If you'd like to learn a lot more, enroll into my Practical Data Governance: Implementation course. It goes over in more detail and covers all these metrics, besides MANY other things. And guess what? It's also has TEMPLATES and a lot of practical takeaways. It doesn't get easier than that. Let's keep putting the LightsOnData. #datagovernance #data #datamanagement

I had a great chat at IBM’s #ThinkToronto with Dr. Gurpinder S. Dhillon, SVP of Data Management and AI at Dun & Bradstreet! Listen in as we dive into AI strategies, stakeholder alignment, and ethical considerations.    Check-out the full interview to gain insights into:   💡 Tackling data challenges 💡 Strategic AI implementation 💡 The future of Gen AI   Let's keep putting the Lights On Data!    #IBMCanada

I love that we don't always have to GO to an event in order to get the insights from interesting sessions. George Firican did a fantastic job at sharing the key takeaways from Max Zito's talk at Big Data LDN. My favorite part is at 01:41 into the video where we learn about the "Five Key Elements of GenBI Strategy" Thanks Pyramid Analytics for an insightful session! https://lnkd.in/d4hsHWHY

Did you know? The image here highlights the AI strategies of various countries. Many of these strategies were created around 2018, with some being 5-7 year plans. We’re on the cusp of seeing some major results and progress (though I also remain skeptical). Which country's strategy would you say that is the most comprehensive? Which one should be set as an example? Let’s keep putting the Lights On Data. —— Follow George Firican for more daily content geared to the data professional.