Data includes hundreds of insurance data entities such as insurance policies, providers and brokers; as well as product, operational, and sales data.
Analytics are used across all levels of business up to the C-level.
Reporting is based on Tableau, transformation is based on dbt.
Datasets are typically delivered to business users as VIEWs or tables under dashboards.
Challenge
Data schema is very complex requiring dozens of JOINs for every data question.
Only the data engineering team has the capability to handle the complexity.
Business users require flexibility in their Tableau dashboards and analysis but are limited by the data engineering team bandwidth for every change.
Honeydew bootstrapped a shared semantic layer, based on the existing KPI dashboards.
Business users dashboards are connected directly to Honeydew semantic layer using a JDBC proxy, instead of static VIEWs or tables in Snowflake.
Business users can easily slice any metric at any grain or level of granularity (required JOINs and SQLs are generated on the fly in a transparent way).
Hence, BI team maintains every shared business metric on Honeydew.
Solution
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