Michael Lavey

Anthropic launches a beta release of "Claude For Excel." Worksheet design, complex error tracing, formula proposals, what-if testing, and external data integration are just a few of the capabilities included. While only in beta testing at this point, Anthropic points the way forward for using AI to enhance human-driven creativity and problem solving in today's fast-paced finance environments. https://lnkd.in/ecGAhp4x

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Dynamic Visibility Control in Tableau is a tool you can use even without any RLS. It’s usually for things like drill-downs, like when you choose a country and a city chart appears, or just a simple "show/hide details" switcher. Hovewer for RLS, it solves a specific problem: Blank Spaces. Read more about it in my blog: https://lnkd.in/dTpnEAdX #Tableau #RLS #DynamicZoneVisibility #DataViz

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Modern Data Stack != Modern Data Culture You can buy all the tools, Snowflake, DBT, Fivetran, Looker, etc. But if your team doesn't trust the numbers, doesn't know who owns what, or doesn't feel confident using the data... What have you really solved? As data practitioners, we've all seen it: Beautiful dashboards built on top of broken and fragmented logic, pipelines that only one person understands, analysts spending half their time just looking for the right table. That's not a tooling issue. That's a culture issue. The truth is, the tools are the easy part. Culture is harder. Culture is: - Engineers owning what they build (and documenting it) - Analysts understanding how upstream changes affect their KPIs - Business folks feeling confident enough to explore without fear - Everyone treating data as something we share responsibility for, not something we "throw over the wall" At Taxwell, we're working hard on this. It's not perfect. But we're seeing progress when we treat data as a product, not a byproduct. * You can buy the stack. You have to build the culture. * What has helped shift data culture within your organization?

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Real transformation happens when we shift from building dashboards to solving real problems for real roles. From requests → to outcomes. From data delivery → to decision support. The future of data teams isn’t being a report factory. It’s becoming partners who deeply understand business personas, workflows, and moments that matter — and design solutions around them. This is the evolution data teams need: Less “dashboard concierge,” more “people-first problem solving.”

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Most analytics systems have a blind spot. We'll talk a lot about data quality and model accuracy -- but very little about the layer between forecasts and operations. That layer is where: - units quietly change - constraints are assumed instead of enforced - costs are treated as symmetric when they're not - outputs become "guidance" rather than decisions Nothing crashes. Dashboards still update. Models still score well. But decisions slowly drift out of alignment with reality. More to come.

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Data and Analytics teams aren't "the dashboard people." We're the kitchen. We run the restaurant. From planning the menu to reading the room mid-service. Clare said it perfectly: we are not a service desk for "a quick pull." We are operators and translators. We choose and source the ingredients. We clean, sort, store, and make sure nothing has expired. Sometimes we combine ingredients in new ways so new flavours appear. Other times we adapt the recipe mid-service as needed because we adapt to our stakeholders and business needs. Our job is getting the right plate to the right table at the right time for the right reason. Here is what we actually do: – Clean the chaos and turn it into numbers the business can trust. – Explain not just "what happened," but "why it happened," and "what you need to do next." – Run the full cycle end to end: brief → design → planning → testing → sign-off → align IT, Finance, Activation, Comms → programme launch → live tracking and course-correcting → post-evaluation and learnings. Dashboards can exist without me. Focus, decision-making and action can't. If you work in data: what's the one part of your job you could not remove without the business losing control? ♻️ Repost to help a data team be seen for what they are. 👋 I'm Olga Sakka. I take you from data to decisions. I'm happiest when the numbers click and the sales teams know exactly what to do next. I cook. I serve. You eat.

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