George Firican

💬 Founder of LightsOnData.com and LightsOnData YouTube Channel
Focused on providing informative content such as ONLINE COURSES, templates, guides, best practices, articles, white papers, and other useful resources to help you with your data governance and data management questions and challenges

💬 Creator of online courses that are engaging, new, and thorough. 
Courses: Building an Award-Winning Business Glossary, Data Governance Maturity Models, Data Governance Fundamentals, etc. - check them out here: https://www.lightsondata.com/courses/

💬 Providing LinkedIn content strategy for data-focused companies and products, as well as those with a focus on artificial intelligence (AI), business intelligence (BI, data science, data management, and data governance areas.
Connect with me today and ask how I can help you reach the data audience.

💬 Host of Lights on Data Show - a podcast and LinkedIn Live weekly show that provides insights into the data world and showcases people that help to shape it.

💬 Get some fun data merchandise here: https://shop.spreadshirt.com/lightsondata/all

💬 International key note speaker, conference speaker, and panelist (spoken at over 60 different conferences).

💬 I love being on camera, hiking, surfing, filming, and video editing
YouTube: @LightsOnData


🏛 My experience and specialties: 
• Expertise in data governance, information quality, business intelligence & data management
• Extensive background in web and application development with experience of the full life-cycle of a project
• Strong leadership capabilities, organizational and communication skills

Specialties: 
• Enterprise information management: Information quality, data governance and stewardship, master data management, business intelligence, business process improvement
• Development: Web and application development, relational database design and development
• Planning: Budget and resource planning, agile and waterfall project management, team development and leadership
• Tools and Applications: Collibra, Tableau, MS Visio, MS Project, Premiere, Photoshop

Director, Data Governance & Business Intelligence

George Firican 💡

Pst…there’s a raffle coming up for a chance to snag a cool grand prize!

Join me at Data & Analytics After Hours on Monday, March 9th, 5:00–6:30 PM in the Exhibitor Showcase at the Gartner Data & Analytics Summit! 

I’ll be there with the wonderful:

💡Kate Strachnyi 
💡SCOTT TAYLOR  
💡Ravit Jain 
💡Aditi Jain  
💡Andreas Welsch 

Let me know if you can join.

Still need to register? Use code DATA2 to save $450 off registration: https://lnkd.in/gZh6rfQC

#GartnerDA #DataCommunity #DataSummit

💡 Award Winning Data Governance Leader | Content Creator & Influencer | Founder of LightsOnData | Podcast Host: Lights On Data Show | LinkedIn Top Voice

How do you scale AI without increasing risk at the same time?
Well…

Many organizations are still trying to figure this out.

Moving AI into production isn’t just a technology challenge.
It’s an AI and data governance challenge.
A risk challenge.

And often a coordination challenge between data, data science, and risk teams.

If this question is on your mind, this session at the Gartner Data & Analytics Summit should be an interesting one to attend.

Join Ali Can Toprak (Enterprise Data Governance Manager at ExxonMobil) and Felix Van de Maele (CEO & Co-Founder of Collibra) as they discuss how data management is evolving into a unified AI governance discipline.

What you’ll learn:
✅ How to bridge the gap between data, data science, and risk teams
✅ The secret to building a shared semantic context to scale AI
✅ How ExxonMobil strengthens accountability across the enterprise

⏱️ 1:15-1:45 PM 
📍 Sun 4, Level 2

See you there!

#data #AI #datagovernance #partnerpost

Collibra Gartner 2026 George Firican Felix Van de Maele

There was a large exodus from ChatGPT lately.
So which is your go-to LLM?

Graphic Source: Amit Rawal  

#llm #AI

No alternative text description for this image

Italy is known for many things: culture, incredible food, beautiful landscapes.
But during my visit, I also discovered something else:

Innovation.

At the Italian Pavilion I met Donato De Ieso (Co-Founder and CEO of dillium), who showed me what they are building with spatial computing and the Apple Vision Pro.

One example that stood out: creating interactive 3D models from simple photos.
Imagine being able to:

✅ Take a photo of a product and instantly turn it into a 3D model
✅ Zoom in, rotate it, or even explore inside it
✅ Break it apart piece by piece to understand how it works

This has huge implications for training, maintenance, design, and product visualization. Instead of transporting large equipment or complex machinery, you can interact with it digitally in a shared spatial environment.

It felt a bit like stepping into a "Tony Stark style" interface.

What I find fascinating is how technologies like spatial computing move us from just looking at data and models on a screen to actually interacting with them.

And that opens the door to entirely new ways of learning, collaborating, and making decisions.

Sometimes innovation shows up in the places you least expect it. Even between a cafe latte and a plate of pasta in Italy.

What industries do you think will benefit the most from spatial computing?

#innovation #VR #technology

Would you like one of these modular phones/ gadgets?

Why do you think these aren’t taking off?

Note: video not mine

#technology #tech #gadget

One of the most valuable things you get from the Gartner Data & Analytics Summit is perspective.

Not just from the sessions.
From the people.

At this summit there are hundreds of conversations happening between data leaders, architects, analysts, and governance professionals.

Some will be about AI.
Some about data platforms.
Some about governance and trust.

But many of the most interesting insights is also happening in the hallways, between sessions, and during those spontaneous meetups with people who care about the same challenges you do.

These are the conversations that spark ideas.
The ones that turn into collaborations months later.
The ones that remind you how strong and passionate this data community really is.

Looking forward to reconnecting with friends and meeting new people over the next few days.

If you are here as well, come say hello.

What is one topic you are most excited to discuss or learn about this week?

#Data #AI #GartnerDA

When at Gartner Data & Analytics Summit…

You do many things:

✅ Get data-driven insights
✅ Validate your strategy from their on-site data , analytics, and AI experts
✅ Learn what’s new in the vendor space

And of course NETWORKING!

Hope to see you there. I’ll be on the floor covering the event and conducting some interviews.

Use my discount code: DATA2 to get $450 off your registration.
https://lnkd.in/gZh6rfQC

#data #AI #GartnerDA
Note: Proud to be an official sponsor of the Gartner Data & Analytics Summit

At the Zoho Analytics booth, we had a really interesting discussion about where analytics is heading across industries and…

…what it takes to turn data into decisions that actually shape how organizations operate.

And of course, there was a live demo.
It’s always fascinating to see how it approaches the journey from data → agentic insight → decision.

I also had the chance to sit down with Sailas Sundaram, Head of Product Strategy at Zoho Analytics, for a conversation about the evolving role of analytics and what teams should be thinking about as AI becomes more embedded in how we work with data.

(The full interview will be coming next week so watch out this space.)

I’m curious:
“What do you most want to see when a vendor gives an analytics demo at a conference?”

#data #analytics #AI

How many of you have run into these problems when trying to move AI into production?

⚠️ Governance and access issues
⚠️ Missing business context
⚠️ Data that can’t be trusted

This is where many promising AI initiatives stall.
The model works. The pilot looks great.

But connecting AI to real enterprise production data turns out to be the hard part.

If you’re here at Gartner D & A Summit 2026, this session tackles that exact challenge:
“AI Has a Production Data Problem. Here’s How Teams Are Solving It”

⏱️ Monday, March 9 | 1:40 - 2:00 PM
📍 Theater 1, Exhibit Showcase

The session explores how organizations are moving AI into production with Simba Intelligence, giving AI governed access to enterprise data without copying data, breaking pipelines, or losing control.

If you're curious how teams are solving this, it’s worth attending.

And if you'd like to start or continue the conversation, visit Simba Intelligence from insightsoftware at Booth 329.

#data #artificialintelligence #AI #partnerpost

Did you know the Inca civilization managed one of the largest empires in the Americas without a written language?

Instead, they used quipu. A system of knotted cords that allowed them to record numbers, track resources, and manage logistics across thousands of miles of roads.

All of that… centuries before spreadsheets, databases, or dashboards.

Sipping a cafe latte in an old Inca town made me think about how humans have always tried to bring order to information. Whether through knots in rope or modern data platforms, the goal has not changed much.

Understand what you have.
Organize it well.
Use it to make better decisions.

Different tools. Same mission.

Sometimes data history goes back further than we think.

Let’s keep putting the LightsOnData.
-George Firican 

#data #history

At conferences, I usually ask vendors one question:
“How does this help shape a decision?”

Not a prettier or quicker dashboard. A decision.

This year, I’m curious how analytics platforms are handling the shift toward AI-assisted and agentic experiences.

When a platform talks about AI-assisted or agentic analytics, I’m especially interested in:
✅ How it sits on top of a real data foundation
✅ How the semantic layer holds up
✅ How it helps shape decisions in practice 

That’s the lens I’m bringing to the Gartner floor this year.

Zoho Analytics is at Booth 428 and offering on-site demos, so if you’re evaluating BI or analytics platforms, it’s a chance to explore how they’re approaching this shift.

You can book a demo slot here:
https://lnkd.in/ekEpps8g 
Now I’m genuinely curious:

When you visit analytics booths at Gartner, what do you actually want to see demonstrated?

#data #analytics #partnerpost

Turning retail data into real business results can be a tough problem, but the solution isn’t more tech. It starts with grounding your data strategy in business outcomes and building from there.

In this article, I break down how retail teams can move from disconnected dashboards and siloed analytics to a practical, value-focused data strategy. 

Key lessons include: 
1️⃣ Start with the business problem not the tools + Clarify the goal first (like reducing churn or improving customer experience)
2️⃣ Empower better questions across teams so insights actually lead to action
3️⃣ Put data governance in place early to build trust in your numbers
4️⃣ Balance pace with capacity so you deliver wins without burning out
5️⃣ Build data literacy and ownership so everyone speaks the same language 

I also cover where the retail data push usually starts, how AI fits in practically (not hype), and what future trends are shaping smarter operations. 

If you work in retail or data and want strategies that actually move the needle, I hope this will help you:
https://lnkd.in/gEubetHW

Why does FSA/ MEBS represent a step-change in enterprise modeling?

Checkout this latest article from Robert Vane as he goes over:
✅ Why We Keep Failing at “Enterprise Modeling”
✅ The Insight: Business Behaviour Is Largely Deterministic
✅ A New Foundation for Deterministic Enterprise Modeling
✅ Why This Matters for Today’s Data & EA Community
✅ Why This Work Is Gaining Momentum

and much more:
https://lnkd.in/gyqdgvBW

#datamodel #dataarchitecture #data

Microsoft MVP | AI & Fabric Specialist for Business Transformation | Helping Enterprises Unlock ROI with Azure, Copilot & Power BI | Forbes Tech | Keynote Speaker | CEO, Onyx Data

Strategic Data & AI Leader | Microsoft MVP | Oxford AI Strategist 

I bridge the gap between technical complexity and Board-level strategy. With nearly 15 years of experience, I have delivered over £93M in revenue growth for global enterprises by transforming data estates into high-velocity strategic assets.

Global Authority & Scalable Insight: 

LinkedIn Learning Instructor: Author of "How to Build and Execute a Successful Data Strategy," an industry-standard framework used by 10,000+ global learners (4.5/5 rating). 
Industry Recognition: Microsoft Data Platform MVP, Forbes Technology Council member, and Gartner Community Ambassador. 
Academic Rigor: Currently calibrating enterprise AI risk and leadership at the University of Oxford (Saïd Business School).

The "Onyx Methodology" in Action:  I help organisations move past "AI Hype" to achieve Operational Utility. Whether leading a global practice of 60+ consultants or advising the C-suite on £200TB+ migrations, my focus is on de-risking technology investments to drive EBITDA.

Core Specialisms:  AI Strategy & Governance (Purview) | Microsoft Fabric & Databricks Architecture | Data Monetisation | High-Performance Team Scaling.

Let’s connect,  I’m focused on the intersection of AI Ethics, Enterprise Strategy, and high-stakes Data Leadership. Always open to discussing the future of our industry with fellow Partners and Architects.

Leon Gordon

Turning 40 today.

Things I've learned:
→ The data is never clean
→ The deadline is always Monday
→ Nobody reads the documentation
→ The meeting could have been an email
→ I still Google VLOOKUP syntax

Normal service resumes next week.

Power Query just became a programmable compute engine inside Microsoft Fabric.
Not a refresh. Not a dataflow. A fully callable API.

You can now invoke M transformation scripts on demand, from notebooks, pipelines, or any HTTP client — and receive results as Spark or Pandas DataFrames via Apache Arrow streams.

Here's why this is a bigger deal than the announcement suggests:

→ 100+ connectors. Programmatically accessible.
→ On-premises and private network sources via gateway. No cloud-only limitation.
→ Billed through your existing Dataflow Gen2 meter. No surprise costs.

For data  analysts through to architects, this collapses a layer of complexity that's existed for years. 
The transformation logic you've already built in Power Query? 
It's now reusable infrastructure, not a locked-in dataflow artefact.

Read the full breakdown in this week's Microsoft AI & Data newsletter.

Power Query just became a programmable compute engine. If you're still treating it as a point-and-click transformation tool, you're already behind. TH

Open article: Unleashing Power Query: Programmatic Execution in Fabric by Leon Gordon • 2 min read

Unleashing Power Query: Programmatic Execution in Fabric

Boards have stopped asking "How do we build an LLM?"

The question now is "How do we protect the enterprise from the commercial and legal risks of a black-box AI rollout?"

That shift has changed what organisations actually need from their most senior AI hires. The era of the AI project manager is ending. What's replacing it is something closer to stewardship, someone accountable for making AI governance, architecture, and commercial outcomes work together at board level.

I've spent the last 12 months doing exactly this. Architecting sovereign infrastructure across 200TB+ data estates, calibrating my methodology through Oxford Saïd Business School, and helping enterprises move from proof of concept to production-scale impact.

I'm now opening conversations for Q2/Q3.

Specifically, I'm looking for a Principal AI Architecture or Head of Practice role with a global enterprise or Tier 1 consultancy that's ready to move past the hype phase into governed, scalable AI delivery.

The kind of mandate where:

→ POCs actually reach production and hit EBITDA targets
→ Agentic systems are architected for complex, regulated data estates
→ The gap between technical AI delivery and board-level risk is someone's actual job

If that sounds like a conversation worth having, message me directly.

#AIStrategy #EnterpriseAI #DataArchitecture #MicrosoftFabric #OxfordAI

96% of executives expect a rise in AI investment over the next five years.

Only 1% of organisations report mature deployment.

That gap isn't a technology problem. It's an architecture problem.

I wrote about this for Forbes Technology Council.

The pattern I keep seeing across enterprise implementations, teams racing to ship AI agents, copilots, and predictive features, then getting stuck in pilot purgatory. Dozens of proofs of concept. Few scaled solutions. No measurable productivity impact.

The root cause is almost always the same. AI gets deployed as a series of disconnected tools rather than being anchored in a coherent, governed architecture.

The organisations pulling ahead have flipped the sequence. Architecture first, then AI. Four layers:

→ Data & Integration (governed data products, event streams)
→ Control & Governance (security, lineage, policy enforcement)
→ AI Services (shared decisioning, agents, scoring models via APIs)
→ Experience (where AI actually meets customers and employees)

The result: deployment cycles compressed from 4-6 months to around 5 weeks. Each new use case reuses existing components. Incremental cost drops. Speed compounds.

Competitors can copy a use case. They can't copy the speed and confidence with which you ship the 10th or 20th.

That's the compounding advantage of intelligent architecture.

Is your AI strategy architecture-led, or are you still shipping first and governing later?

🔗 Full article in the comments.

#AI #DataArchitecture #EnterpriseAI #ForbesTechCouncil #MicrosoftFabric

Only 1% of organisations report mature AI deployment.

96% are increasing AI investment.

The gap between those two numbers isn't a technology problem. It's a governance problem.

The pattern I keep seeing across enterprise implementations: teams ship a model into production without mapping lineage from source to inference. The model misbehaves. The diagnostic process starts from zero. Weeks of rework that proper governance would have eliminated before the first deployment.

That's not moving fast. That's iterating blind.

The uncomfortable truth most AI strategies ignore: governance isn't the brake on innovation. It's the prerequisite for sustainable speed.

Without it, every new use case is built from scratch. With it, your 10th deployment is faster than your 2nd, because the foundation compounds.

The organisations winning at AI aren't shipping fastest. They're shipping what they can operationalise, monitor, and iterate on without rebuilding the foundation every quarter.

That's not compliance. That's architecture.

#AIStrategy #AIGovernance #EnterpriseAI #DataArchitecture #MicrosoftFabric

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George Firican 💡

Leon Gordon

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The Battle

George Firican 💡

Leon Gordon

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}George Firican 💡's LinkedIn Performance

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