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evidence
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evidence
@evidence_dev
https://t.co/Gn735YnbMP is an open source framework for building data products with SQL and markdown
शामिल हुए Mayıs 2021
308 फ़ॉलोइंग2.3K फ़ॉलोवर्स
evidence रीट्वीट किया
evidence रीट्वीट किया
evidence रीट्वीट किया
evidence रीट्वीट किया

Dense tables are sometimes overlooked in favour of charts, but they’re often the fastest way to understand complex data.
We put a lot of effort into making our tables feel publication-quality and easy to scan. One small but high-impact thing we just shipped is column groups.
You can now group related columns under a shared header (like Revenue or Volume in this example), which makes wide tables much easier to read at a glance. Adding a column to a group is intentionally simple and doesn’t require any extra layout work.
It’s a small feature, but it makes dense data feel way more approachable when you’re actually reading it.

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evidence रीट्वीट किया

We’ve been working on a cleaner way to make reports interactive, and added variables you can insert anywhere in @evidence_dev.
Inputs like sliders or dropdowns generate a variable you can reference in SQL, charts, or even plain markdown.
Change an input, and anything using that
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evidence रीट्वीट किया
evidence रीट्वीट किया

RT @seanhughes92: Logos instantly make reports feel more polished.
We just shipped a super simple way to add company logos to tables and m…
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evidence रीट्वीट किया
evidence रीट्वीट किया

Most BI and analytics tools struggle with something I think about a lot: use case frequency.
They give you tons of controls, but it’s hard to make even basic dashboards that look good and perform well. Often because the tools treat every possible action as equally important.
In reality, reporting isn’t evenly distributed. Something like 90% of reports are built from the same small set of ingredients.
It’s easy to assign the wrong weight to features when the people building the product haven’t spent much time building reports themselves. Without that experience, it’s hard to know what’s common, what’s rare, or what the default behaviour should be.
At Evidence, the product is built by a team of ex-analysts and data leaders, and we actively use Evidence ourselves. That gives us strong opinions about the right user experience, and a shared understanding of which patterns show up constantly versus occasionally.
We bake that directly into our product development process.
When we discuss feature ideas internally, we’ll say things like "this is a 95% use case" or "this is a 2% use case". That framing drives a lot:
- How much priority it gets
- Whether it becomes a default or an advanced option
- How much surface area it earns in the product and in docs
High-frequency use cases become obvious and opinionated.
Low-frequency ones stay possible, but intentionally out of the way.
The goal is that by default, anyone using Evidence can produce the same outputs a top-tier analyst would - because the right choices and trade-offs are already baked into the product.
We get there by designing explicitly around use case frequency.
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evidence रीट्वीट किया

We're getting ready to release some major updates to our maps in Evidence Studio. I can't wait to share, so I'm just going to post some examples this week so you can see what we've built.
First up we've got a point map including a size scale and customizable shape.
Code for this example in the comments

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evidence रीट्वीट किया
evidence रीट्वीट किया

Shipping some early Christmas gifts to @evidence_dev customers this week - like this map that lets you zoom in to see more granular areas
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evidence रीट्वीट किया








