Headless BI Architecture and Trade-offs – Pavel Tiunov, Cube Dev

Headless BI Architecture and Trade-offs – Pavel Tiunov, Cube Dev

There has been a proliferation of tools in different categories of the modern data stack. This talk will focus on the Headless BI category and Cube’s implementation of Headless BI. Headless BI injects a component between data warehouses and other data sources and tools on the other side of the stack (e.g. CDP, data exploration tools, custom data apps, etc.). This new component encapsulates several critical functions like data modeling, access control, and aggregate awareness while deliberately omitting others, like data visualization and presentation. We’ll explore: – Keeping data models separate from data sources and not substituting data modeling with mere data transformation. – Managing access control centrally, aggregate awareness, and caching in a separate layer upstack from data consumers. – Removing data presentation features and embracing data accessibility via a set of APIs.

Drag and Drop Query Builder for PrestoDB – Ravishankar Nair, PassionBytes

Drag and Drop Query Builder for PrestoDB – Ravishankar Nair, PassionBytes

You use multiple tools for databases, for example Azure Data Studio for SQLServer access, Toad or SQLDeveloper for Oracle access, MySQLWorkbench for MySQL databases. Imagine we have one tool and we can query any database, bring any table from any catalog to a single canvas! Now you join, the underlying PrestoDB compatible query is generated. Click a button, you get the profiled data, including distributions and correlations. An amazing tool in action.