0 · Overview
From fragmented to semantic, structured, living data
A short story of how data.Flowers cleaned, structured, mapped data about a cluster of companies.
The result was living data; usable, visual, and searchable by everyone.
Follow our journey through a practical deployment...
1 · Spreadsheet
The initial spreadsheet
Data.Flowers received a list of companies across a few initial categories. Everyone knew that the data isn't complete, but that was what the client had. It doesn't matter - it's enough to get started.
Data is here, but not useful. It's fragmented, incomplete, and not shared.
2 · Database
Creating a structured database
We normalized the fields, enriched the data, deduplicate records, and create one source of truth. We proposed additional companies.
Result: we now have structured data, but it's hard to make sense of it.
3 · Taxonomy
Creating meaningful categories
Mapping tells you what you didn't know you didn't know, but search only tells you what you knew you didn't know.
We semi-automatically created categories and sub-categories that people (and agents) can understand and maintain.
Result: semantic taxonomy gives the ecosystem a shared language.
4 · Balcony View
Step back and see the whole ecosystem
See the structure of the market before inspecting any individual company. Finally viscerally understand how many we are!
Feature: a balcony view reveals density, gaps, and category shape.
5 · Map
Zoom into what you did not know you did not know
Move from the ecosystem view into categories, companies, and their capabilities. In the future, we'll support even deeper levels of zoom.
Feature: smoothly move between big picture overviews and small picture details.
6 · AI Search
Search for what you know you do not know
Find companies with specific capabilities within your ecosystem. Internet search won't give you precise control, and no other tool will give you such power of search. Your ecosystem finally has sovereignty.
Feature: sovereign ecosystem company capability search.