Dan Brown

Often making the leap from Solution Architect (SA) to Enterprise Architect (EA) can be a step too far. On paper, it looks like the natural next step and is still the most common step into Enterprise Architecture 📰 But in practice, the skills and mindset needed are very different. This is why the skill gap analysis was created; to support SA's looking to transition into Enterprise Architect roles. It takes investment, time and effort to develop these skills 📋 Here are 5 reasons why some Solution Architects don't always make great Enterprise Architects ⤵️ P.S Lack of exposure to governance is one of the most common reasons I have noticed when speaking to SA applicants. 📌 #EnterpriseArchitecture #SolutionArchitecture #EA #SA #Communication #Strategy #Leadership #EnterpriseArchitect #SolutionArchitect #EITA

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The value of EA is rarely in the Architecture Review Board. And none of your stakeholders will ever use the term “alignment.” Both standards and alignment are your job. Not theirs. When you are “doing” Enterprise Architecture, don’t explain your activities. Explain the results. Explain what you *hope* they will do with the results. Work with them to figure out how to fit *their* response to your results into *their* work processes. If they cannot use your results, either you are talking to the wrong person, or you are producing something useless. Architect, be useful.

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𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗡𝗲𝗲𝗱𝘀 𝗮 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗲 𝗥𝗲𝗳𝗿𝗮𝗺𝗲 Enterprise architecture is still trapped in myths that hold back real change. It is time to rethink the role and the value. 𝗠𝘆𝘁𝗵𝘀 𝗵𝗼𝗹𝗱 𝘂𝘀 𝗯𝗮𝗰𝗸 ❌ The ivory tower architect: isolated, designing in a vacuum ❌ EA as documentation and reviews: paperwork and gates ❌ We're Agile - we don't need architects ❌ Control over collaboration: top-down mandates instead of enablement 𝗪𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝘄𝗵𝗲𝗻 𝗺𝘆𝘁𝗵𝘀 𝗿𝘂𝗻 𝘁𝗵𝗲 𝘀𝗵𝗼𝘄 • Failed transformations that never land • Millions wasted on misaligned initiatives • Activity without progress I have seen talented architects boxed in by these narratives while the very problems they could solve keep compounding. 𝗥𝗲𝗳𝗿𝗮𝗺𝗲: 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘀 𝗮𝘀 𝗖𝗵𝗮𝗻𝗴𝗲 𝗖𝗮𝘁𝗮𝗹𝘆𝘀𝘁𝘀 Stop seeing architects as gatekeepers. They are guardians of change and guides of innovation. That shift unlocks value through three practical pillars: 𝟭) 𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗼𝗻: 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗺𝗮𝗱𝗲 𝗲𝘅𝗲𝗰𝘂𝘁𝗮𝗯𝗹𝗲 Most strategies fail in translation, not intent. Architects convert vision into capabilities, choices, and plans that teams can build from. 𝙍𝙚𝙨𝙪𝙡𝙩𝙨: clear scope, faster decisions, less rework. 𝘘𝘶𝘪𝘤𝘬 𝘵𝘦𝘴𝘵: can an engineer explain the business outcome of the next sprint in 30 seconds? 𝟮) 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻: 𝗮𝗹𝗶𝗴𝗻𝗶𝗻𝗴 𝘄𝗼𝗿𝗱𝘀 𝘄𝗶𝘁𝗵 𝗮𝗰𝘁𝗶𝗼𝗻𝘀 Organizations are full of parallel efforts that drift. Architects create the connective tissue so what leaders say matches what teams do. 𝙍𝙚𝙨𝙪𝙡𝙩𝙨: traceable investments, fewer duplicates, shared language across business and tech. 𝘘𝘶𝘪𝘤𝘬 𝘵𝘦𝘴𝘵: can each initiative be traced to a capability and a customer metric? 𝟯) 𝗥𝗵𝘆𝘁𝗵𝗺: 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗶𝗻 𝗺𝗼𝘁𝗶𝗼𝗻 Great strategy lives in operating cadence. Architects embed intent into standups, sprint reviews, funding cycles, and architecture councils. 𝙍𝙚𝙨𝙪𝙡𝙩𝙨: continuous alignment, visible momentum, fewer big bang surprises. 𝘘𝘶𝘪𝘤𝘬 𝘵𝘦𝘴𝘵: if priorities shift, can teams adjust without chaos? 𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗼𝗻 𝗶𝗺𝗽𝗲𝗿𝗮𝘁𝗶𝘃𝗲 Organizations don't need more direction. They need better translation. Brilliant strategies are noise if no one sees how they change today’s work. Translation, connection, and rhythm turn intent into impact. 𝗬𝗼𝘂𝗿 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗦𝘂𝗽𝗲𝗿𝗽𝗼𝘄𝗲𝗿 It's not the diagram, it's the clarity you bring. • When you make outcomes legible to delivery, you translate. • When you surface misalignment, you connect. • When you weave intent into a weekly heartbeat, you create rhythm. 𝗪𝗵𝗶𝗰𝗵 𝗺𝘆𝘁𝗵 𝘀𝗵𝗼𝘄𝘀 𝘂𝗽 𝗶𝗻 𝘆𝗼𝘂𝗿 𝘄𝗼𝗿𝗹𝗱, 𝗮𝗻𝗱 𝘄𝗵𝗶𝗰𝗵 𝗽𝗶𝗹𝗹𝗮𝗿 𝘄𝗶𝗹𝗹 𝘆𝗼𝘂 𝘀𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝗲𝗻? --- ➕ Follow Kevin Donovan 🔔   ♻️ Repost | 💬 Comment | 👍 Like   🚀 Join 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐬’ 𝐇𝐮𝐛 - Join our newsletter and connect with community. https://lnkd.in/dgmQqfu2.

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🚨 Breaking News ISG Research Alert: Analytic Data Platforms ISG Buyers Guide™ 🚨 Proud to announce the release of ISG (Information Services Group)’s latest deep-software-dive into Analytic Data Platforms—led by our Software Research Director and industry expert Matt Aslett, and supported by our fantastic team: Mukesh Ranjan, KUMARI LISA, Sarida Khatun, Renae Christie, Ryan Swagerty Heather Howland Lindsay Johnston, PMP, PMI-ACP, CSM and AI and IT leader David Menninger. 👉ISG Research defines analytic data platforms as data platforms that run applications to analyze the business, including decision support, business intelligence, data science and AI and machine learning (ML). 💡 As organizations accelerate AI and data-driven transformation, the role of modern analytic data platforms has never been more critical. Our latest ISG Buyers Guide™ evaluates software providers capabilities across: ✅ Analytic workloads across lakes, lakehouse & warehouses ✅ Data persistence & processing ✅ Management & query capabilities ✅ Functionality for DBAs, developers, data engineers & architects The guide assesses the following 32 providers: Actian, Aiven, Alibaba Cloud, Amazon Web Services (AWS), Broadcom, Cloudera, Couchbase, Databricks, Dremio, EDB, Google Cloud, Huawei Cloud, IBM, Incorta, InterSystems, KX, MariaDB, Microsoft, Neo4j, OpenText, Oracle, Percona, TiDB, powered by PingCAP, Progress Software, Salesforce, SAP, SingleStore, Snowflake, Starburst, Tencent Cloud, Teradata and VAST Data. 🔗 Read and Listen: https://lnkd.in/graFsucj #ISGResearch #DataPlatforms #AI #Analytics #CloudData #SoftwareSelection #DataTower

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I’ve helped teams migrate to the cloud. The real challenge came after. Banks spent the last five years racing to the cloud. Now they’re facing a tougher question: Where’s the value? I’ve worked with teams that hit all their migration milestones, yet six months later, they were still fighting ballooning costs and unclear business impact. Boston Consulting Group (BCG) 2025 reports: 👉 “For Banks, the AI Reckoning Is Here” found that 60% of financial institutions still lack defined performance indicators to track cloud and AI ROI. McKinsey & Company adds weight in its 2023 report “In search of cloud value” by Chhavi Arora, Will Forrest, Mark Gu, and James Kaplan, revealing that most banks struggle not because of the technology, but because of three missing shifts: - Financial alignment - Product-mode thinking - Operational discipline The issue isn’t cloud. It’s treating cloud as a tech solution, instead of a strategic lever. With insights from Chhavi Arora, William Forrest, Mark Gu, James Kaplan, Stiene Riemer, Kirsten Rulf, Christian Schmid, Michael Strauss, and Saurabh Tripathi, I break down what I call Cloud Strategy 2.0. This is how one mid-sized Latin American bank eliminated $11 million in waste by shifting from migration goals to value goals, realigning architecture to measurable business outcomes. Cloud Strategy 2.0 isn’t about dashboards or cost tagging. It’s about making cloud work for the business, not just IT. Follow Friendly Neighborhood Gokul for insights at the intersection of IT, architecture, and enterprise platforms. #CloudStrategy #BankingTransformation #Techwithgokul #FriendlyNeighborhoodGokul

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Making the shift from a Cloud Architect role to leading an entire tech division was a big leap and one that came with its own set of challenges and learnings. Over the past year, I have had the chance to look at tech from a much wider lens: team building, roadmaps, tech strategy, delivery pipelines, and aligning engineering goals with business outcomes. Many friends and peers have asked me what the transition felt like. In short: it was intense, humbling, and incredibly rewarding. Here are 10 key lessons that stood out during this journey: ➜ Tech decisions are now business decisions: I started evaluating every architectural choice not just for scalability, but also for impact on cost, speed, and delivery. ➜ You don’t need to know everything but you need to know enough: The goal shifted from going deep on one solution to staying broad and sharp enough to guide multiple teams. ➜ People > Tech: Building a reliable, motivated team became far more valuable than writing perfect code. ➜ Delegation is a skill, not a weakness: Letting go was hard at first, but enabling others to lead and deliver became essential for scale. ➜ Tech and sales are not separate worlds: In a service company, I learned that being involved in pre-sales discussions, shaping proposals, and backing up sales with realistic timelines and delivery plans is a core part of the CTO role. You are not just building solutions, you are helping sell them too. ➜ You will need to make peace with trade-offs: Sometimes we had to go with “good enough” to keep momentum. Learning to balance ideal solutions with business urgency was a mindset shift. ➜ You become the bridge between tech and non-tech: Whether it’s sales calls or sprint reviews, I found myself explaining tech in simple terms and listening to non-tech feedback more deeply. ➜ Your team’s growth is your growth: The best wins weren’t shipping features, they were seeing team members step up and thrive. ➜ Burnout is real and it starts at the top: It took conscious effort to not carry everything. Learning to build systems, not just chase tasks, helped. ➜ You are still learning A new title doesn’t mean you stop growing. I am still learning every week, through mistakes, feedback, and the amazing people I get to work with. If you are on a similar path or thinking of making the jump to tech leadership, I hope some of these reflections help. Happy to connect and share more if you are curious about the journey. #techleadership #careertransition #cloudarchitecture #startuplife #growthmindset

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After 20 years of legacy modernisation projects at Scott Logic; we've developed some strong opinions that run counter to many in the industry. The conversation about legacy systems has become dominated by what we might charitably call "vendor-driven oversimplification." Many will know Gartner's Five Rs and the Strangler Fig pattern - but at times these frameworks have become substitutes for thinking rather than tools to support it. "The goal isn’t to modernise everything or to modernise nothing; it’s to modernise strategically. This means acknowledging both the value that legacy systems continue to deliver and the genuine costs of indefinite postponement." As many organisations rush to replace legacy systems 'for AI' - often focussing on the wrong thing entirely. Poor data quality and weak governance will sink AI initiatives regardless of underlying system age. Our latest piece explores what the frameworks don't tell you: the "archaeological problem" of undocumented systems, the maintenance contract trap, and why the organisations most needing modernisation are often least equipped to execute it. Legacy Systems: Beyond the Modernisation Hype: https://lnkd.in/eWDVSYA4 Massive thanks to Suzanne Angell, Mari McMahon James Moore for their insights and many other colleagues for their input and review (including Colin Eberhardt, Paul Dykes, Marghaid Jones). If this resonates - or if you've seen legacy modernisation approaches that actually work in practice - do get in touch. We're exploring a follow-up on AI modernisation specifically - seeing some interesting initiatives in this space. #LegacyModernisation #EnterpriseArchitecture #AITransformation #ArchitectTomorrow

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For anyone who has been following me for some time, you would know that I absolutely love the role of a Solutions Architect because of the flexibility we have in choosing the activities we would like to focus on. In one of my previous article, "The role of a Solutions Architect and how they spend their time," I broke down the different hats we wear and how time allocation shifts based on seniority level. In this week article, I dive deep into what I consider the most impactful activity Field Solutions Architects engage in - partnering strategically with Product teams to drive successful product launches and seamless customer implementations. While it's true that Solutions Architect is fundamentally a customer-facing role where we spend the majority of our time with customers, the most successful solutions architects I know understand a critical truth: significant time investment with product teams is what separates good from exceptional. In fact, when I was promoted to principal solutions architect, the centerpiece of my promotion document wasn't just customer wins - it was the strategic partnerships I built with service teams that directly contributed to launching multiple products. Read the full article here - https://lnkd.in/eqhHBRdG

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𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞'𝐬 𝐑𝐨𝐥𝐞 𝐢𝐧 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐚𝐧𝐝 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 🎯 Too often, we get lost in the layers and boxes of a traditional Enterprise Architecture diagram. But this one? This is a different kind of blueprint. It's the 𝐜𝐞𝐧𝐭𝐫𝐚𝐥 𝐧𝐞𝐫𝐯𝐨𝐮𝐬 𝐬𝐲𝐬𝐭𝐞𝐦 of the modern enterprise, showing how EA is the vital link between strategy and every critical business function. This isn't a static model; it’s a living hub, actively engaged with the entire organization. Look at the interconnected spokes: 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 🚀: EA doesn't just receive strategy; it architects it. It takes a 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐎𝐮𝐭𝐜𝐨𝐦𝐞 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭 and transforms it into a tangible, executable plan, ensuring that our vision is built on a solid foundation. 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠 & 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 🛠️: From 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐲-𝐛𝐚𝐬𝐞𝐝 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠 to 𝐏𝐨𝐫𝐭𝐟𝐨𝐥𝐢𝐨 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭, EA provides the crucial architectural guardrails. It ensures every project, every program, and every investment is a deliberate step toward our strategic goals, not a siloed, reactive measure. 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧 & 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 📦: This is where theory meets reality. EA enables 𝐏𝐫𝐨𝐠𝐫𝐚𝐦/𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 and 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 (𝐃𝐞𝐯𝐎𝐩𝐬). It's the architect behind the scenes, designing an ecosystem that allows for both rapid innovation and reliable, seamless execution. 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 📊: After delivery, EA’s work continues. It designs the backbone for 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧t, ensuring our processes are efficient and our operations are smooth. It’s also the key to effective 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞, 𝐑𝐢𝐬𝐤 𝐂𝐨𝐧𝐭𝐫𝐨𝐥, 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲, 𝐚𝐧𝐝 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞, embedding these non-negotiables into the very design of the enterprise. 𝐓𝐡𝐞 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐃𝐚𝐭𝐚 & 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬 🧱: EA provides the framework for managing 𝐏𝐫𝐨𝐜𝐞𝐬𝐬, 𝐑𝐮𝐥𝐞𝐬, 𝐚𝐧𝐝 𝐃𝐚𝐭𝐚. It's the discipline that standardizes these core components, turning chaos into order and enabling consistent, predictable outcomes. This diagram proves that Enterprise Architecture is not a department you go to; it's the intelligence embedded throughout the organization, empowering every function to operate with a unified purpose. It’s the engine of 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧. What part of this interconnected hub do you find most critical for your organization's success? Let's discuss! 👇 ➕ Follow Sumeet Goenka 🔔 ♻️ Repost | 💬 Comment | 👍 Like 🚀 Visit Yallo and stay connected for more insights 👉 https://vist.ly/48ygj Credit: Intel #EnterpriseArchitecture #DigitalTransformation #StrategyExecution #BusinessAgility #Governance #ITStrategy #DevOps

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Often making the leap from Solution Architect (SA) to Enterprise Architect (EA) can be a step too far. On paper, it looks like the natural next step and is still the most common step into Enterprise Architecture 📰 But in practice, the skills and mindset needed are very different. This is why the skill gap analysis was created; to support SA's looking to transition into Enterprise Architect roles. It takes investment, time and effort to develop these skills 📋 Here are 5 reasons why some Solution Architects don't always make great Enterprise Architects ⤵️ P.S Lack of exposure to governance is one of the most common reasons I have noticed when speaking to SA applicants. 📌

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The Fundamental Challenges with EA There are lots of articles and posts about EA challenges and how to deal with them, both internal challenges caused by the EA team themselves, and external challenges posed to the EA team by leadership or by other teams. But fundamentally there are 3 challenges which are inherent in EA, which are the root cause of all the other issues. 1. EA is extremely broad EA covers a ridiculously broad range of topics and areas and so everyone is often confused or at odds about what EA should actually do. 2. EA is extremely intangible EA doesn't develop software. They don't procure contracts. They don't install servers. They don't operate a help desk. So what do they do? They think, they envision, they plan, they analyze, they align. All good stuff, but very intangible compared to other teams and also much harder to directly see benefits, especially in the short term. 3. EA gets in everybody else's business EA can't operate in a vacuum, and their space is everybody else. They get into (or in the way of) everybody else's business - strategy, app dev, infra, end user. You name it, EA potentially has an interest and an opinion on it. There's almost nothing EA does which doesn't involve or impact another team, and often by definition it's not a win win. These three challenges are fundamental to EA. You can maybe mitigate them but you can't avoid them.

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🚀 Over the past year, I’ve had the privilege of partnering with Microsoft and some of the world’s largest organizations to tackle one of the toughest challenges in enterprise IT: making sense of unstructured data. Through those conversations and learnings, one thing became clear: Organizations are asking three critical questions: 1️⃣ What data do we actually have? 2️⃣ What’s hiding inside our files? (Because metadata alone isn’t enough.) 3️⃣ How do we connect it all to upstream AI services like Microsoft 365 Copilot? 💡 The result is NetApp Neo — a scalable, enterprise-class platform built to bring structure to unstructured data and unlock its full potential for AI and beyond. This is more than just a technology milestone; it’s the outcome of a year of co-creation and problem-solving alongside forward-thinking customers. 👉 I’d love to hear your thoughts: How is your organization approaching the challenge of unstructured data in the age of AI? 👁️ Want to learn more? Checkout the Microsoft blog about Neo here: https://lnkd.in/eceauu4F

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