Chief Roadblock Remover and Learning Enabler | Software Development Expert | Leadership & Career Coach | Speaker | Author | Building great products, building great teams!

🎯 I'm a result-driven 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗟𝗲𝗮𝗱𝗲𝗿, 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗘𝘅𝗽𝗲𝗿𝘁, 𝗖𝗼𝗮𝗰𝗵, 𝗧𝗿𝗮𝗶𝗻𝗲𝗿 𝗮𝗻𝗱 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝗻𝘁 with 20 years of professional experience in different domains, including the 𝗳𝗶𝗻𝗮𝗻𝗰𝗲 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆, 𝗯𝗮𝗻𝗸𝗶𝗻𝗴, 𝗲𝗻𝗲𝗿𝗴𝘆 𝘀𝗲𝗰𝘁𝗼𝗿, 𝘁𝗿𝗮𝗻𝘀𝗽𝗼𝗿𝘁𝗮𝘁𝗶𝗼𝗻, 𝗶𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝘁𝗲𝗹𝗰𝗼. 

🚀 My mission is to provide 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗲𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲 focused on architecture, the best agile practices, passionately 𝗯𝘂𝗶𝗹𝗱 𝗵𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀 𝗮𝗻𝗱 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 to deliver innovative, 𝗵𝗶𝗴𝗵-𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀, working closely with customers and developing software products on different platforms.

🎓 As a 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿, I published 20+ papers and book chapters in international conferences and journals (having more than 440+ citations and h-index 11 on Google Scholar), obtaining 𝗣𝗵.𝗗. 𝗶𝗻 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝗰𝗲𝘀. Also, I have been involved as a 𝗿𝗲𝘃𝗶𝗲𝘄𝗲𝗿 𝗮𝗻𝗱 𝗽𝗿𝗼𝗴𝗿𝗮𝗺 𝗰𝗼𝗺𝗺𝗶𝘁𝘁𝗲𝗲 𝗺𝗲𝗺𝗯𝗲𝗿—member of ACM, the IEEE Computer Society, and GOAI Research group. 

🧑‍💼 I work as a professional 𝗛𝗶𝗴𝗵-𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗖𝗮𝗿𝗲𝗲𝗿 𝗰𝗼𝗮𝗰𝗵 for people in engineering leadership positions.

✍🏻 Additionally, I am a 𝗽𝗮𝘀𝘀𝗶𝗼𝗻𝗮𝘁𝗲 𝗮𝘂𝘁𝗵𝗼𝗿, who helps more than 400,000 engineers, managers, and architects to build great careers, products, and teams through various platforms and channels.

𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲:

📌 Leadership
📌 Team building
📌 Making things efficient
📌 Creating self-contained systems
📌 Be highly organized and make others too
📌 Focus on strategy/goals
📌 Make things happen
📌 Career Coaching
📌 Mentoring
📌 Line management
📌 Effective client communication
📌 Software Architecture
📌 DevOps mindset
📌 Cloud (Azure)
📌 .NET/C# (ASP.NET/WPF)
📌 SQL Server/NoSQL
📌 Agile methods (Scrum, Kanban, SAFe)
📌 Product/project management

📲 Feel free to contact me here via LinkedIn (DM)!

Dr Milan Milanović

Developers don't like legacy projects

But, in software, legacy means it makes money

'Greenfield' means 'no revenue' (yet)

Legacy code is messy because it has survived user contact

Greenfield is clean because nobody's tried to break it

The code you hate is funding your salary

The code you want to write isn't

Chief Roadblock Remover and Learning Enabler | Helping 400K+ engineers and leaders grow through better software, teams & careers | Author | Speaker | Leadership & Career Coach

The best engineers I know delete more code than they write

Junior engineers add features. Senior engineers remove complexity

Every line of code you write is a liability. It needs to be maintained. It can break. It adds cognitive load to anyone who reads it later

The best pull requests I've seen in the last year? Half of them deleted more than they added. Someone refactored three classes into one. Someone replaced 200 lines of custom logic with a library function. Someone removed an entire abstraction layer that wasn't pulling its weight

Deletion is a skill. You have to know what's safe to remove. You have to understand the system well enough to see what's redundant, over-engineered, or just wrong

Next time you open a file, ask: What can I remove?

The best code is the code you don't write

𝗗𝗼 𝗻𝗼𝘁 𝗹𝗲𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗵𝗶𝗻𝗸 𝘆𝗼𝘂 𝗱𝗼𝗻’𝘁 𝗯𝗲𝗹𝗼𝗻𝗴

As former President Obama said in the podcast, when you sit with people at fancy places (Harvard, US Senate, etc.) with people with fancy titles and talk to them, you will learn one thing...

They are nothing special; they are just a normal person like you.

They just have confidence that they belong to something.

Give that confidence to yourself and sit at that table.

And when you get a seat at the table, make room for someone else who has never had a seat.

I wish you a great week ahead 👋!

Video: Pivot Podcast.

#management #personaldevelopment #success #career #leadership

If you're a developer who ships code daily, remember these:

- First, make it work; nobody cares how elegant broken code is
- Then make it fast, slow code that works still frustrates users
- After that, make it pretty, so that your teammates read code more than they write it
- Add tests that actually catch bugs, not just boost coverage metrics
- Refactor when you finally understand what you're building (usually the second time through)

Perfect code on the first try is a myth. 

Fast iteration beats slow perfection every time

If you're a senior software engineer, here is an incomplete list of engineering practices you must know:

- Source control / GIT
- Tests (check Test Pyramid)
- Clean code
- Pair / Mob programming
- Design Patterns
- Refactoring
- TDD / BDD
- YAGNI, DRY, KISS, SOLID
- Automatic code analysis
- Code reviews
- Documenting

Anything else to add?

𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 𝘃𝘀 𝗟𝗼𝗮𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗲𝗿 𝘃𝘀 𝗥𝗲𝘃𝗲𝗿𝘀𝗲 𝗣𝗿𝗼𝘅𝘆

Regarding a system design, we often need clarification about the roles of a Load Balancer and an API Gateway. Most of our resources are about their implementation rather than real-life use cases.

𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 

It sits between a client and a group of backend services. It serves as a reverse proxy, accepting all application programming interface (API) calls, aggregating the services needed to fulfill them, and returning the appropriate results. 

User authentication, rate limits, and statistics are typical duties that API gateways handle on behalf of an API service system. Also, the API gateway can handle faults (circuit breakers), logging, and monitoring.

𝗟𝗼𝗮𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗲𝗿 

It is a service that distributes incoming traffic across many servers or resources. Usually, we have two or more web servers on the backend, and it 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝘀 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝘁𝗵𝗲𝗺. 

Its primary purpose is to use resources optimally. A more equal task allocation and increased capacity can enhance the system's responsiveness and reliability. 

There are three load balancers at a high level: hardware-based, cloud-based, and software-based.

𝗥𝗲𝘃𝗲𝗿𝘀𝗲 𝗣𝗿𝗼𝘅𝘆 

A server sits in front of backend servers and forwards client requests to them. Reverse proxies are typically used to enhance security, performance, and reliability. 

A reverse proxy receives a request from a client, forwards it to another server, and returns the response to the client, giving the impression that the first proxy server handled the request. These proxies ensure that users don't access the origin server directly, giving the web server anonymity. 

They are usually used for Load balancing, where we need to handle incoming traffic and distribute it across multiple backend servers, or for caching.

So, the main thing that differs these two is that an 𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 𝗶𝘀 𝗳𝗼𝗰𝘂𝘀𝗲𝗱 𝗼𝗻 𝗿𝗼𝘂𝘁𝗶𝗻𝗴 𝗿𝗲𝗾𝘂𝗲𝘀𝘁𝘀 to the appropriate service and it handles requests for APIs, while a 𝗟𝗼𝗮𝗱 𝗯𝗮𝗹𝗮𝗻𝗰𝗲𝗿 𝗶𝘀 𝗳𝗼𝗰𝘂𝘀𝗲𝗱 𝗼𝗻 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗻𝗴 𝗿𝗲𝗾𝘂𝗲𝘀𝘁𝘀 𝗲𝘃𝗲𝗻𝗹𝘆 between a group of servers and handles requests that are sent to a single IP address, which works at protocol or socket level (TCP, HTTP).

Some 𝗲𝘅𝗮𝗺𝗽𝗹𝗲𝘀 of API Gateways are Amazon API Gateway, Ocelot (.NET-based), Tyk, or Apache APISIX, while Load Balancers are Azure Load Balancer, HAProxy, or Seesaw.

An example of reverse proxy services is 𝗔𝗽𝗮𝗰𝗵𝗲 𝗣𝗿𝗼𝘅𝘆, 𝗡𝗴𝗶𝗻𝘅 𝗼𝗿 𝗜𝗜𝗦 with additional modules (Url Rewrite).

Onyx Data

Built and scaled a Microsoft Data & AI consultancy serving enterprise and public sector clients across the UK, UAE, and US.

Highlights:
Microsoft Fabric Featured Partner & Microsoft MVP (5x)
Delivered Azure AI-powered solutions across finance, education, and government
Launched FabOps – a Microsoft co-sell solution for Fabric observability
Enabled 3 enterprise clients to scale Fabric & Copilot across departments
Regularly featured at Microsoft Build, FabCon, and global MVP events

Founder / Chief Executive Officer

Forbes Technology Council

Thought Leader

LinkedIn

As a LinkedIn Learning Instructor specialising in Data and Artificial Intelligence (AI), I am dedicated to creating and delivering high-quality educational content that empowers learners to advance their careers in data and AI. My role involves developing comprehensive courses, engaging with the learner community, and continuously updating course materials to reflect the latest industry trends.

Key Achievements:

- Expert Content Development: Created and delivered high-impact courses that received positive feedback and high engagement from learners.

- Curriculum Innovation: Developed innovative and comprehensive curriculam that facilitated structured learning paths for students, enhancing their understanding and application of data and AI concepts.

- Effective Knowledge Transfer: Simplified complex technical concepts, making them accessible and engaging for a diverse learner base, resulting in improved learner outcomes.

- Community Building: Fostered an active and supportive learning community through regular engagement in user groups, helping learners overcome challenges and succeed in their educational journeys.

- Continual Improvement: Actively sought and integrated learner feedback, leading to continuous improvement of course content and instructional methods.

LinkedIn Learning Instructor

The AI Journal

Contributor

AI4C

The key aim of the AI4C is to help charities embarking on AI/ML deployments with pro bono insights/advice - all in a confidential, collaborative sales-free, vendor neutral environment. 

Over 30 charities have joined and gained value with their strategic thinking, user stories, design, deployment and operations. 

AI 4 Good / Tech 4 Good 

If you are a charity leader looking to get the most for the people you serve, feel free to contact the AI4C Chair Paul Excell paul.excell@member.wcit.org.uk

Member

Global AI Hub

Brainz Magazine Official

Executive Contributor

Pomerol Partners

Partner

Reassured

Head Of Data And Insight (Freelance)

Redkite

Principal Power BI Consultant (Freelance) 

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

Your data shouldn't just inform decisions, it should transform your business.

I’m Leon Gordon a Microsoft MVP, keynote speaker, and founder of Onyx Data, where we help enterprises turn Microsoft Fabric, Azure AI, Power BI and Copilot into measurable ROI.

I’ve spent the past 13 years leading enterprise data and AI transformations. From being a hands-on technologist to now heading up a global team, I’ve seen how the right data strategy, aligned with business goals, drives massive ROI.

Clients turn to Onyx Data when they need:
• End-to-end Microsoft Fabric & Copilot implementations
• AI strategy and deployment with Azure OpenAI
• Power BI governance, optimisation & adoption frameworks
• Executive training to build data culture from the top down

Real-world outcomes we’ve delivered:
• £3M in new revenue from insight-driven selling
• 187.1% reduction in data latency
• 35% increase in data accuracy
• 50%+ boost in data literacy
• Featured by Microsoft at Build, FabCon, and global case studies

Recognitions:
• 5x Microsoft MVP
• Microsoft Data & AI Solutions Partner
• Microsoft Digital & App Innovation Partner
• Microsoft Fabric & Real-Time Intelligence Featured Partner
• Microsoft Training Services Partner
• LinkedIn Top Voice
• Founder of #DataDNA – global monthly analytics challenge

Featured by Microsoft at Build, FabCon, and global case studies. Speaker at top industry events across the UK, US, and Middle East.

Latest launch - FabOps – our co-sell-ready Fabric observability solution designed for enterprise-scale efficiency and impact → https://fabops.ai

👉 Ready to move beyond insights and into action?
→ Book a strategy call → https://bit.ly/46MgPHM
→ Try FabOps free → www.fabops.ai
→ Join 28,000+ global pros in #DataDNA → https://www.linkedin.com/groups/9075495/
→ Subscribe to my weekly AI and Data insights → https://www.linkedin.com/newsletters/ai-and-data-tech-trends-6933659594284023808?lipi=urn%3Ali%3Apage%3Ad_flagship3_profile_view_base%3BxNISbSHFTkGWI32ogCOB4Q%3D%3D

Leon Gordon

For years, our data architecture looked like a complex web of disconnected services. We spent more time moving data than actually using it. 

This "engineering teardown" of Microsoft Fabric brilliantly visualises the end of that era.

Look at the foundation (Block #1). That’s OneLake.

Notice how the different compute engines, Data Engineering (#2), Data Science (#3), Warehousing (#4), and Real-Time (#5), aren't siloed in separate buildings? They are distinct modules sitting on the same foundation.

No copying. No movement. Just different lenses on the same data, governed by Purview (#8) and served up via Power BI (#7).

This isn't just a platform update, it's a fundamental shift in how we build data estates.

Is your organisation ready for the OneLake approach, or are you still managing silos?

#MicrosoftFabric #DataEngineering #OneLake #DataArchitecture #Synapse #PowerBI

Turn Microsoft Fabric, Copilot & Azure AI into safe, real‑time business value in weeks, not months | Data & AI Transformation Leader @ Onyx Data | Microsoft MVP | Global Speaker | Forbes Tech Council

No alternative text description for this image

The client: "Can you just quickly throw together a report by EOD?"

The reality beneath the surface: 🛠️⚙️👇

It’s easy to forget that a seamless Power BI report isn't just drag-and-drop magic. It's a finely tuned engine of interconnected components.

This "engineering teardown" perfectly visualises the ecosystem we build daily.

1️⃣ It starts with raw materials (Connectors)
2️⃣ Gets processed in the factory (Power Query)
3️⃣ Is structured into a robust foundation (Data Model)
4️⃣ And finally, shipped out for consumption (Service, Mobile, Embedded)

If your "quick report" is slow, chances are the engine block (The Data Model) needs a tune-up.

Which part of this machine do you spend the most time wrenching on? Let me know in the comments. 👇

#PowerBI #DataEngineering #Analytics #Microsoft #BusinessIntelligence #DataViz

Hardcoding Secrets? Stop It. 🛑

It is the #1 rule of secure data engineering... 𝗡𝗲𝘃𝗲𝗿 𝗵𝗮𝗿𝗱𝗰𝗼𝗱𝗲 𝘆𝗼𝘂𝗿 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻.

If your Fabric notebooks or functions contain lines like schema = "dev_db" or exposed API keys, you are creating a security risk and a deployment nightmare.

Microsoft Fabric just released Variable Libraries for User Data Functions, and it is the fix we've been waiting for.
- 𝗗𝗲𝗰𝗼𝘂𝗽𝗹𝗲 𝗖𝗼𝗱𝗲 𝗳𝗿𝗼𝗺 𝗖𝗼𝗻𝗳𝗶𝗴: Keep your logic clean and environment-agnostic.
- 𝗘𝗻𝗵𝗮𝗻𝗰𝗲 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Reference secrets securely without exposing them in source control.
- 𝗦𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲 𝗖𝗜/𝗖𝗗: Swap values automatically as you deploy from Dev -> Test -> Prod.
- It’s time to mature your pipelines.

𝗖𝗹𝗶𝗰𝗸 𝘁𝗼 𝗿𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿 𝗼𝗻 𝗵𝗼𝘄 𝘁𝗼 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗩𝗮𝗿𝗶𝗮𝗯𝗹𝗲 𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀 𝘁𝗼𝗱𝗮𝘆.

#MicrosoftFabric #DataEngineering #DevOps #DataSecurity #Python

No more hardcoded secrets in your Fabric code. Preheader: Manage environment configurations securely with the new Variable Libraries for User Data Fun

Open article: Goodbye, Hardcoded Secrets - Variable Libraries for Fabric User Data Functions by Leon Gordon • 2 min read

Goodbye, Hardcoded Secrets - Variable Libraries for Fabric User Data Functions

𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 𝗜𝗴𝗻𝗶𝘁𝗲 𝗔𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗺𝗲𝗻𝘁𝘀 𝗰𝗮𝗻 𝗯𝗲 𝗰𝗼𝗻𝗳𝘂𝘀𝗶𝗻𝗴.

There are so many features to focus on.

- Agent mode
- App builders
- AI video creation
- Cross-app workflows
- Pricing tiers

There are definitely some features that matter more than others.

Here are my 5 key Copilot Microsoft Ignite announcements so far this week.

1. Agent capabilities that replace manual work - Excel agents now build full dashboards with one prompt. No sidebar tools needed. Charts, formulas, and insights appear automatically.

2. Seamless data flow between applications - Excel data becomes Word reports, then PowerPoint presentations. Three apps working as one workflow without exports or copying.

3. No-code app building that actually works - App Builder created a complete team ideas app in minutes. Changes happen through simple requests, not coding.

4. AI video generation with transparency - Sora 2 creates professional videos in seconds. Every output shows clear AI labels, keeping content honest.

5. Accessible pricing for small teams - At $21 per month for teams under 300, Copilot is finally within reach for businesses that couldn't afford the $30 tier.

And it is working for me.

The future of productivity isn't about learning every feature.

It's about knowing which ones actually change how you work.

If you’re planning how to roll this out responsibly, I’ve built a 2-week Copilot adoption playbook, complete with use cases, guardrails, and adoption steps.

👉 Comment “Copilot” and I’ll send it straight over.

Have you been keeping up with the Microsoft Fabric November updates?

Ignite happened this week and honestly, the pace of innovation is incredible.

I've just watched the latest update and there's a wave of features rolling out across the platform, from data engineering to Power BI and Copilot.

Here's what caught my attention:

1. Mirroring support for SQL Server, PostgreSQL, and Cosmos DB - bringing all your data straight into OneLake
2. Warehouse snapshots - giving analysts a consistent source of truth while ETL jobs are running
3. Data clustering in Fabric Data Warehouse - cutting query times from 40 seconds down to just 1 second
4. Read/write permissions in OneLake - enabling real collaboration without compromising governance
5. Copilot getting smarter - now identifying anti-patterns in your code and suggesting optimisations

The warehouse snapshots feature is particularly interesting. Imagine running hourly ETL jobs while your analysts query data without worrying about inconsistencies. The data engineer creates a snapshot, analysts query against it, and once ETL completes, the snapshot rolls forward seamlessly.

And the data clustering demo was impressive. same query, same data, but 97% less data scanned and a fraction of the CPU time used.

What strikes me most is how Microsoft is making Fabric more accessible without sacrificing governance or performance. Features like customer-managed keys at the workspace level and enhanced Copilot capabilities show they're thinking about both security and developer experience.

If you're working with data at scale, these updates are worth exploring.

Question - which of these November features are you most excited to try out?

Join our Microsoft Fabric - UK User Group for our latest webinar.

This session we are excited to announce our host Microsoft MVP Leon Gordon and co-host Microsoft MVP Pragati Jain will be introducing Microsoft MVP Andy Cutler.

Join the Microsoft Fabric UK - User Group on -

Microsoft Community - https://lnkd.in/dtrfGvy

LinkedIn - https://lnkd.in/dX_Ziaz

MeetUp - https://lnkd.in/d6wteZBn

Session Abstract -

Materialized Lake Views (MLVs) in Microsoft Fabric Lakehouses offer a declarative approach to building data loading and data materialization pipelines. This session introduces how MLVs simplify data loading piplines, automate refreshes, and visualize data loading lineage across the process. Attendees will learn how MLVs support integrated data quality rules, enabling trend analysis and alerting for violations, all without manual pipeline orchestration. We'll also cover current limitations and the roadmap for new feature support.

Biography

Andy Cutler is a Microsoft Azure Cloud & Fabric consultant, Data Platform MVP, and runs a UK consultancy Datahai. With over 20 years experience in Microsoft data technologies, Andy has worked with SQL Server, Azure Data Platform, Synapse Analytics Power BI, and Fabric.

Andy’s consultancy Datahai offers a range of services including assessments and reviews, architecture guidance, end-to-end data platform solutions, bespoke projects, training, & helps clients leverage existing technology investments, optimize costs and maximize the value of Azure, Fabric, & Power BI.

Social Media / Website Links

https://lnkd.in/eW69uSs9

Can Fabric Materialized Lake Views Deliver Low Effort Data Engineering?

Most data teams aren’t struggling because of skill.

They’re struggling because of complexity.

Pipelines with too many moving parts.
Manual fixes that eat entire mornings.
That constant feeling of: “We’re one error away from another fire drill.”

If you’re leading a data team, you’ve lived this:

- Late-night messages when a job fails
- “Quick requests” that are anything but
- Pressure to deliver faster with zero tolerance for mistakes

Here’s the part we rarely say out loud:

It’s not the work that’s breaking teams.
It’s the invisible steps, dependencies, and rework behind the scenes.

That’s where Copilot for Data Factory actually matters.

Not because it magically “automates everything”…
but because it strips away the friction that slows everyone down.

When complexity drops, your team finally gets space to:

- Think instead of react
- Design instead of patch
- Deliver outcomes instead of chasing errors

This isn’t about replacing people.
It’s about giving them their bandwidth back.

If your team could use more clarity in how they build and run pipelines, comment “CLARITY” — I’ll share examples, frameworks, and real-world Copilot for Data Factory workflows that actually help.

#DataLeadership #DataTeams #AIinData #MicrosoftCopilot #DataFactory #DataEngineering

taplio

The Battle

Dr Milan Milanović

Leon Gordon

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Performance ScoreDr Milan Milanović's LinkedIn Performance

Performance ScoreLeon Gordon's LinkedIn Performance

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taplio

The Battle

Dr Milan Milanović

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);}Dr Milan Milanović's LinkedIn Performance

Performance ScoreLeon Gordon's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreDr Milan Milanović's LinkedIn Performance