Decommissioning Legacy Reporting Cubes for a Modern Cloud BI & Lakehouse Ecosystem

1. The Operational Challenge (Fragmented Inputs)

Many established mid-market and enterprise organizations rely on a patchwork of aging on-premise SQL servers, rigid reporting cubes, and fragile departmental Excel macros built over a decade ago. While those systems worked for static historical reporting, they create severe bottlenecks when leadership needs agile cross-functional analytics.

Across enterprise digital transformation initiatives, organizations faced three recurring barriers:

• Brittle Legacy Infrastructure: On-premise reporting cubes required specialized maintenance, broke frequently during schema updates, and could not scale to ingest modern API or cloud data streams.
• Shadow IT & Spreadsheet Drift: Because central reporting was slow to modify, each business unit maintained its own Excel transformations—leading to conflicting numbers in executive meetings.
• Low Adoption of New Tools: Purely technical IT migrations often fail because frontline analysts and managers are not guided through workflow redesign and hands-on enablement.

2. The amplitiq Architecture & Delivery Approach

Following an enterprise-wide Digital Maturity Assessment and Board-approved transformation roadmap, Tim Tong partnered across data engineering and operational business units to execute a phased modernization:

• Legacy Decommissioning & Cloud Migration: Systematically retired legacy on-premise databases and reporting cubes, migrating data pipelines, archiving, and integrations to Snowflake, Azure Databricks, and Informatica ETL/ELT.
• Enterprise Semantic Modeling: Designed governed SSAS semantic models and source-to-target mappings that established a single, auditable definition for every financial and operational KPI.
• Unified Self-Service BI Layer: Deployed interactive executive and operational dashboards across Power BI and Tableau, directly connected to planning platforms (Quorum Execute, Enersight).
• Organizational Change Management (OCM): Led cross-functional process-mapping workshops, User Acceptance Testing (UAT), and role-specific training journeys to embed a digital-first culture across engineering, operations, land, marketing, and finance.

3. Executive & Business Outcomes

Combining cloud data engineering with disciplined change management ensured the new architecture delivered lasting operational ROI:

• Thousands of Cumulative Manual Hours Eliminated: Automated compilation, validation, and exception flagging freed technical specialists from low-value data wrangling.
• >95% Sustainable User Adoption: By involving frontline change champions early in requirements scoping and UAT, business units embraced self-service BI rather than reverting to legacy spreadsheets.
• Executive & Audit Confidence: Delivered end-to-end data lineage and governance controls meeting Bill 198, SOX, and ITGC audit compliance standards.