Certified Data Analyst Associate

Data analysts are primarily focused on deriving insights and making data-driven decisions. The Gold layer, with its highly processed and refined data, is most suitable for their needs. It provides them with reliable, business-ready data that can be used for in-depth analysis, reporting, and visualization.

The correct place in Databricks SQL where an analyst can write and execute SQL queries is the SQL Editor page. This page is specifically designed for creating, testing, and running SQL queries, providing a dedicated interface for these tasks.

Databricks SQL is designed to complement traditional BI tools like Tableau, Power BI, and Looker. While these tools are often used for professional-grade presentations and detailed dashboards, Databricks SQL enhances this ecosystem by providing an efficient platform for quick in-platform BI work, enabling users to perform rapid analysis and exploration directly within Databricks before possibly exporting the data to other BI tools for further refinement and presentation.

To connect Databricks to Fivetran for data ingestion, use Partner Connect's automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with. This method avoids the need to manually set up clusters and simplifies the integration process.

Data engineers primarily use Databricks Data Science and Engineering for tasks such as data transformation, pipeline creation, and general data engineering. While they may use Databricks SQL to query data for validation or troubleshooting, it is not their primary tool. This makes Databricks SQL a secondary service for data engineers, aligning with the question's requirement.