BI and data platforms should work together—not become separate silos.
Aurea Quantra helps organizations assess, connect, improve, and modernize analytics environments across Microsoft, AWS, Snowflake, Databricks, SQL, and leading BI tools.
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Disclaimer: Platform names identify technologies we can assess, integrate, or support. They do not imply vendor partnership or certification unless explicitly stated.
Power BI and Microsoft Fabric
Fits when: Leadership needs trusted Power BI reporting, or you are staging Fabric/OneLake without abandoning what already works.
Engagements: Semantic model hardening, executive dashboards, Fabric readiness, governance, and adoption.
Connects to: Azure data services, SQL Server, ERP/CRM extracts, Databricks or Snowflake when hybrid.
Azure data services
Fits when: Data Factory, Synapse, Azure SQL, or lake storage need a practical path into governed BI consumption.
Engagements: Architecture review, pipeline design, semantic-layer handoff to Power BI.
Connects to: Fabric, on-prem SQL, SaaS APIs, operational systems.
AWS analytics and Amazon Redshift
Fits when: AWS is your cloud home and Redshift, S3, Glue, Athena, or QuickSight need clearer cost, modeling, and BI patterns.
Engagements: Warehouse assessment, workload review, BI integration, modernization planning.
Connects to: Power BI, Tableau, QuickSight, ERP/CRM feeds, lakehouse patterns on S3.
Snowflake
Fits when: Snowflake is (or will be) the warehouse, but metrics and BI tools still disagree.
Engagements: Modeling for consumption, integration design, Tableau/Power BI semantic alignment.
Connects to: ERP/CRM/SaaS sources, BI tools, adjacent lakes or Spark workloads.
Databricks and Spark
Credential: Databricks-certified practitioner delivery focused on lakehouse patterns and BI handoff.
Fits when: Volume or pipeline complexity outgrew desktop refresh and isolated SQL jobs.
Engagements: Lakehouse readiness, PySpark/Spark job design, gold-layer tables for Power BI.
Connects to: Power BI, Fabric, Snowflake, AWS lakes, operational extracts.
Databricks consulting → · PySpark & Spark deep-dive → · Book My BI Diagnostic →
Tableau and visualization
Fits when: Tableau is the preferred front end but the model underneath is weak or inconsistent.
Engagements: Dashboard redesign, performance, metric alignment to warehouse definitions.
Connects to: Snowflake, Redshift, SQL Server, Databricks, Excel exports you want to retire.
SQL, ERP, CRM, and operational systems
Fits when: The business systems of record do not produce a single trusted analytical story.
Engagements: Integration mapping, dimensional models, pipeline-to-order logic, customer matching.
Connects to: Any of the BI and warehouse platforms above.
Not sure which platform path is right?
Bring the current stack and the decision your team cannot make confidently. The BI Diagnostic stays vendor-neutral.