We are a startup that wants to build a more thoughtful world. There is a lot of buzz around data but we are skeptical that data in of itself is valuable, or data is sentient like "the data will tell us"- instead, we, as users, need to shape, reshape and contextualize data for our use cases.
As data volume, users and use cases grow, there is a movement to democratize data - "data for everyone" (pretty hard to argue against democracy!) but an un-governed self-serve model pushes the responsibility to the end user - the data consumers now tussle with data day in and day out, often repeat the work of others, with higher potential for inconsistencies and errors. But, concentrating data generation in a select few producers to improve governance is either unworkable or creates bottlenecks.
We believe there is a new, different way to provide structure over data that yields enormous leverage for organizations - a way to define the key business entities, events, metrics, attributes, and their relationships that enables both governance and flexibility - a modern metrics platform for data-led cultures. Both data producers and consumers can participate and thrive in this production-grade platform where workflows and contracts are made explicit.
for Data Practitioners
As typical producers of data assets valuable to the business, we want to help the analyst engineers, analysts and data scientists, who toil in a swamp of tables, code, pipelines, tests, dashboards - and are pushed to doing heavy engineering maintenance while doing their main jobs. It is a drain on their productivity to wrestle with infrastructure, code editors, CLI, unit tests to manage the code and data sprawl that the current generation of tools create. We are building a user friendly metrics-focused configuration environment backed by a version controlled, review and governance workflow. We want to expand who participates in definitions of metrics and attribute drivers beyond data scientists to domain-aware operators.
for Data Consumers
For data consumers, we provide a variety of options from APIs to a clean, graphical interface to navigate metrics and compose new types of calculations for use cases (see below). Because the producers have their definitions certified, we can now balance the perpetual tension between flexibility ("want more data shapes for use cases") and governance ("but accurately and reliably") - this expands who can be an effective data consumer.
We want this virtuous loop: more producers → more consumers → more producers
Our growing list of supported use cases span metric cubes that feed into BI tools like Tableau, reliable and speedy experiment metric calculations (A/B and quasi-experiments), metric diagnostics (what happened, why, weekly/monthly performance reviews), and operational use cases within domains like sales & marketing, product, operations and finance.