For organizations and teams that are: Drowning in data but starving for insights. Whether your existing reporting is incomplete, inaccurate or too slow, or if you're looking to take the leap and implement a BI visualization tool, we can help you.

• Assess your current reporting landscape, with measurable opportunities

• Build semantic models / star-schema warehouses for tools like Power BI, Tableau, or Looker

• Design and implement executive dashboards and domain-specific analytics (finance, operations, sales, HR, clinical/healthcare, etc.), including advanced functionality such as app embedding and RLS

• Enable self-serve analytics without compromising security and governance

• Fix or refactor existing reports/models that are slow, fragile, or opaque

• Lead knowledge transfer & coaching sessions with your BI team to impart data modeling/visualization best practices

For organizations and teams that are: Overdue an upgrade to a modern data strategy with better reliability and scalability, but wrestling with the mountain of options.

• Assess your current SQL Server / ETL / reporting landscape

• Design a modern architecture in your cloud of choice (Azure, AWS, GCP)

• Implement data platforms like Microsoft Fabric, Snowflake, or Azure Synapse/Databricks

• Plan and execute migrations from on-prem to cloud with minimal downtime

• Optimize cost and performance (storage vs compute, tiering, scheduling, etc.)

• Guide you through vendor/platform selection

For organizations and teams that are: Struggling with blind spots in their data visibility, with complex SaaS/ERP platforms that need to be wrangled so their data can be utilized.

• Ingest data from ERP/CRM/HRIS, custom apps, and third-party APIs

• Build robust ETL/ELT pipelines using tools like Fabric Dataflows, ADF/Synapse, dbt, or custom Python

• Standardize and model data for analytics and data science

• Implement monitoring, alerting, and error handling so the pipelines keep flowing when we're gone

• Set up CI/CD and deployment patterns appropriate to your size and maturity

For organizations and teams that are: Getting ready or looking to get ready for the AI wave.

• Evaluate readiness (current state of the data environment)

• Assess & propose use cases based on the data available, so you focus your efforts on impactful and realistic implementations, rather than a wild goose chase

• Data modeling/preparation for use by modern data science techniques and libraries

• Proof-of-concept implementations on concrete machine-learning use cases, for any audience