The Diver Platform Reviews

You know the pain. 8,000+ formulas in your Excel budget, any one of which could break. Department heads emailing versions back and forth. Mystery errors appearing right before board meetings. Weekends lost hunting for that one number that doesn't add up. We built Budgyt because we lived that nightmare as CFOs ourselves. It's a true database that works like Excel, so your team doesn't need training. But formulas never break. Every number traces back to source with one click. Import your chart of accounts and actuals directly from your accounting system. Click any variance to drill down to vendor-level detail instantly. Run rolling reforecasts every month without rebuilding everything from scratch. We connected it via API so you're up and running in hours, not spending months on implementation consulting. Built for multi-department organizations where budgeting needs to be collaborative, but the finance team needs to stay in control. No more emailing spreadsheets around. No more "did I break something?" panic. Just budgeting that actually works.

AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack. Its Governed Control Model connects business meaning, data structures, transformation rules, dependencies, lineage and technical implementation in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design. Generated outputs can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, supported Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns. Because generated outputs are native Microsoft technology, no AnalyticsCreator runtime is required in production. Organisations retain ownership of the resulting implementation and can integrate generated assets into Git, Azure DevOps and CI/CD workflows. Lineage, documentation and dependency information remain connected to the design, helping teams understand change impact before regenerating affected assets. Design Intelligence extends this governed project context into AI-assisted data engineering by providing authorised AI tools and agents with structured access to metadata, lineage, dependencies and design rules. Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery and repeatable data product engineering.