Analytic Information Hub
Turn complex data into actionable insight
Finance teams are working with large volume of data more than ever, but information is often spread across ERP systems, operational platforms, spreadsheets and other disconnected sources.
CCH Tagetik Analytic Information Hub (AIH) brings granular financial, operational and external data together in one flexible environment, helping organisations reduce reconciliation effort, improve visibility and make more confident decisions.
Bring your data together. Understand what drives performance.
AIH enables organisations to collect, validate, transform and analyse large volumes of detailed data without forcing it into a rigid financial structure.
With AIH, you can:
- Combine financial and operational data from multiple sources
- Analyse performance at customer, product, plant, transaction or any other level required
- Reduce reliance on spreadsheets and manual reconciliation
- Build detailed driver-based planning and forecasting models
- Improve profitability and cost analysis
- Drill from summary results into the underlying detail
- Process large, granular datasets efficiently
This helps finance teams move beyond reporting what happened and better understand why it happened.
Flexible analytics for complex business questions
From detailed profitability analysis to operational planning, AIH provides the flexibility to model data around your organisation’s requirements. Common use cases include:
Customer and product profitability
Driver-based planning and forecasting
Cost allocations
Transaction-level analysis
Operational and financial reporting
Scenario modelling
High-volume data processing
Finance-owned. Connected. Controlled.
Designed to reduce heavy reliance on IT, AIH gives finance teams greater control over data models, calculations, validation and reporting while maintaining workflow, security and auditability.
It can also work alongside the CCH Tagetik Financial Workspace (a core component of the CCH Tagetik Intelligent Platform), enriching granular data before trusted outputs are used across planning, consolidation and reporting processes.