Chris Wigglesworth

🚀 Allianz UK Personal Lines migrated from SQL Server, Oracle & SAS to Databricks SQL, cutting data refresh times to minutes and saving ~£80K/month in compute costs. Real-time insights, better governance, smarter decisions.

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𝐑𝐞𝐦𝐨𝐭𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐯𝐬 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐨𝐬𝐦𝐨𝐬𝐢𝐬 Sharon Austen’s comment on That Moment really resonated with me: “In those early days, actually being in and part of the team... is a really, really important part.” I see the same challenge in business intelligence teams. When people start remotely, they often lack the context that experienced colleagues absorb effortlessly — the informal exchanges, the subtle cues, the unspoken understanding of how things get done. That kind of learning doesn’t happen in scheduled calls. It happens through proximity — through osmosis. And in data-driven roles, this context can matter just as much as technical skill. The most effective model I’ve seen is simple: build a strong in-person foundation, then offer flexibility once competence is proven. 🎧 Listen to Sharon’s full perspective on That Moment — link in comments. #ThatMoment #RemoteWork #OrganizationalLearning #BusinessIntelligence #Leadership #TeamDevelopment

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Why don't more people have a "how to buy from us" page? Digital Modus Ltd have a simple page on their site that explains the routes you can use to buy their services. That includes the Salesforce App Exchange and some Crown Commercial Service frameworks. If you sell into government, being able to demonstrate that you've already qualified for a number of frameworks or purchasing systems makes sense. Are procurement teams rolling around the internet looking for companies on frameworks? No. But buyers will check your site and there's no harm in making it embarrassingly easy for them to choose a sales route that favours your company. Why am I pointing this out? Primarily because we're not as good as we should be on this (trust me, improvements are imminent) but also because it seems like such an easy change to make.

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🎥 New quick overview & demonstration video available 🎥 Checkout the latest video that provides a quick overview of the OpenStudyBuilder, what it is, what it's not and what it is evolving into. Furthermore, it gives a brief demonstration of the different functionalities showcasing the application along with the Word Add-In, Dashboards and API. Thank you Katja Glass and Team for the awesome work. https://lnkd.in/eRSivhPe #OpenStudyBuilder #Demonstration #DDF

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UK software platform inforcer has raised $35 million in Series B funding to power Managed Service Providers (MSPs) in Microsoft security and AI. Inforcer enables MSPs and Microsoft Partners to seamlessly implement, configure, and manage Microsoft products across their small and medium-sized business customers. The platform simplifies configuration, compliance, and AI deployment across Microsoft 365 tenants, solving complexity for partners serving a market of 350M users and unlocking the business case for them to service the Microsoft security and AI stack. The Series B round was led by Dawn Capital, with participation from existing investors Meritech Capital. The capital will be used to build on the company's impressive traction and expand its MSP community in 2025. Congratulations to co-founder and CEO Jamie Daum and the Inforcer team. Tech.eu: https://lnkd.in/dt7z_Qrp #SaaS #Cybersecurity #AI #MSP #Microsoft #SeriesB #Funding #UKTech

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What is the UK's role in global research? From international partnerships to real-world policy impact, the UK punches far above its weight. Over the past five years, UK researchers published 1.2M papers—with the highest citation impact in the world. And that’s not all: 👩‍🔬 41% of researchers are women, with above-average impact 🌍 1 in 2 UK papers involve international collaboration 💡 Industry partnerships are more than twice the global average 📜 UK research is cited in global policy more than any other country It’s a powerful reminder of what happens when research is open, collaborative, and focused on impact. Take a look at the full insights 👇 http://spkl.io/6042fqqHa #ResearchImpact #UKInnovation #SciencePolicy #Elsevier #SciVal

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For UK consumerbusinesses being hit by tariffs, I think network effects are part of the solution. While everyone is scrambling to reduce product costs, there isn’t much talk about increasing the profitibilty of the customers. This means acquiring customers faster, who spent more and spend for longer, without additional spend from the brand. And social network effects achieve just this. By focusing your acquisition strategy on “connected customers” your addressable market looks very different. It goes from a broad disconnect shot in the dark, to a super effective strategy to harvest current demand while being future demand. I’m calling this your nTAM networked Total Addressable Market. What does this look like in reality? It’s finding those areas where word-of-mouth and offline influence are supporting sales. These hotspots are just waiting for petrol to be poured on them. Those that understand network effects reap the rewards. Those that don’t, pay for it.

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Ever since Sadie St Lawrence and I connected years ago for some collaboration with Women In Data™️, I've always admired her passion and expertise for data science and AI, and it's been really inspiring to follow her journey. This is why I was so excited to see her publish the book "Becoming an AI Orchestrator" and as expected it was a great and insightful read for many reasons. As a fellow musician, I really enjoyed the music analogies of how knowledge workers need to shift from being a musician to be an orchestrator, and why being an "orchestrator" is more critical than being a "conductor" in todays times. Other highlights for me were: 👉 The overview of Gen AI application categories across creative tasks, analytical tasks and hybrid tasks 👉 The implications of different types of intelligence for our relationship and interactions with AI 👉 The concrete examples of applying AI in different business functions 👉 An iterative process for AI adoption that starts with identifying human tasks 👉 How to get started in defining the right AI guidelines and policies, including an important part about how to address Bias 👉 A playbook on how to thrive in the age of AI by following certain golden principles Across the entire book Sadie mentions lots of her experiences and stories of how she uses AI in her day to day, which together with other parts shows us a truth that I couldn't resonate more with: doing the right and valuable things with AI starts with every single individual. And reading this book will definitely help you do that. I highly recommend this book to anyone who wants to know how to use AI to enrich their life, their career and our collective future - which ideally should be everyone. #aistrategy #book #tiankaistuff

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We’re obsessed with speed. But if the data is wrong, it just means we’re making the wrong decisions faster. See, when dashboards can’t help with decision making or alerts miss trends, dips and spikes… Pipeline speed doesn’t mean much. Sure, it’s easier to blame it on performance, considering how stuff is built nowadays. We build streaming architectures incrementally. We consider components separately. - Deduplication is added after records arrive as a custom logic. - Idempotency is handled per consumer - Schema validation is a downstream job - Teams need to create workarounds So you need to reprocess the records or backfill them. And real-time is not real-time anymore. And all of this is quite expensive. But more speed just turns your pipeline into a more fragile system. Your engineers don’t want an increase in the number of events per time frame, or lower latency, or another streaming framework. They want fewer incidents, replays, and surprises. They want to be able to trust the output. Users need to trust the output. That’s why we at GlassFlow focus on predictable and reliable streaming architecture. We focus on trust. - GlassFlow guarantees exactly-once semantics as the core of the system, not a best effort. - Instead of temporary workarounds, it has built-in deduplication logic. - It gives high importance to possible schema changes. By doing this, changes don’t create accidents anymore. - It provides ClickHouse-native optimizations for analytical workloads. This approach helps teams fix issues in-flight along the way. There is no need to fix issues downstream. It decreases the number of on-call incidents and data quality alerts, so you could have fewer incident-related meetings. Don’t ask for a faster stream. Ask for a stream that behaves consistently under pressure. – ♻️Hi, I’m Armend and I’m a founder of GlassFlow, a tool that deduplicates, joins and transforms Kafka data streams for ClickHouse. Build pipelines you can trust from day one. DM me for a personalized demo or visit our website. #Kafka #ETL #Data

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