Thread by @josephmoon_ai

There is an industry-defining unbundling of BI happening right now. The BI app is unbundling into two composable parts - the metrics layer and the consumption layer. A 🧵👇:

Firstly, WHY is this happening? A massive tailwind propelled by @SnowflakeDB and @getdbt. In particular, a well engineered, infinitely scaleable analytics warehouse and a transformation and modeling layer that extends into the metrics layer.

"Accessories" to the data warehouse help tremendously as well: @fivetran, @AirbyteHQ, @getcensus, and @HightouchData for forward and reverse ELT (piping data to and from operational tools - e.g. @salesforce - the data warehouse) are the must-haves.

.@LookerData had massive success in capitalizing on the shift of BI to the cloud. Its main value proposition is LookML, a modeling and metrics engine. But its reign is ending.

.@getdbt is the best positioned product to dethrone LookML as a metrics engine. And if they execute well, they will be the dominant metrics product in the next 5 years. Other smart players in the space include @supergraindata and @transformio. Time will tell.

There is, however, a gap in the market to enable the consumption and delivery of these metrics and processed data inside the data warehouse. Traditional dashboarding solutions such as @tableau just don't cut it due to the inflexible UX and lack of metadata integration.

UX: software users now expect real-time collaboration, flexible and web-native collaborative interfaces (think @NotionHQ and @coda_hq) and workflow capabilities (think @asana and @clickup) built into a consumer-grade tool.

UX: dashboards alone do not cover the vast consumption use-cases of BI. Read:

https://twitter.com/josephmoon_ai/status/1460468073522106369?s=20

Metadata: a great consumption tool must talk to other parts of the data stack via metadata integration. This means native metadata integration between @SnowflakeDB, @getdbt, @AirbyteHQ, and more.

Armed with this strong thesis, we started @hyperquery to address this gap in the market. We built @hyperquery to be the single, standard consumption interface for the modern analytics stack. We've invented a new category of software: Collaborative Analytics.

.@hyperquery combines the best of notebooks, apps, and dashboards and supercharges them with a built-in knowledge-base and a data catalog.

It's the single workspace for data discovery, exploratory analytics (ad-hoc work), dynamic analytics (building app-based explorations), and productionized analytics (building recurring-use dashboards and apps), and a place to organize those assets in a Notion-styled wiki.

With @SnowflakeDB, @getdbt, and @hyperquery, everyone can finally set up the right infrastructure to tackle data-driven decision-making at any scale. We can this the "DSH" stack (pronounced "dash").

.@jthandy (CEO @getdbt), Christian Kleinerman (SVP Product @SnowflakeDB), and I (CEO @hyperquery) are working hard to build this new future. Come join us for a once-in-a-lifetime opportunity to refactor the modern analytics stack!