BI and Analytics Integration
That is a definition problem, not a chart problem. We build a reporting layer over your ERP with agreed metrics, then connect your BI tool so every dashboard answers the same way.
Why It Matters
Revenue can mean ordered, delivered, invoiced or collected. Margin can be before or after landed cost, freight and discount. Until those choices are written down and agreed, two correct reports will disagree and everyone will blame the tool.
Letting a BI tool query your live transactional database directly means one heavy report can make the system crawl for everyone raising orders.
We collect the decisions you make weekly and the questions behind them.
Each metric is written down and agreed, including what it excludes.
We build the reporting layer and the refresh schedule that feeds it.
Dashboards per role, checked against the ERP figures line by line.
We sit with each team, watch them use it, and adjust what they ignore.
Definitions, filters and owners for every figure that appears on a dashboard.
Documented tables and relationships, kept tool-neutral so BI products can change.
Per dataset, with monitoring and an alert when a refresh fails or runs long.
Dashboard figures reconciled against ERP reports before anyone is asked to trust them.
Row and column level restrictions mapped to roles and documented.
Model documentation and guidance so your team can extend it without us.
A dashboard that does not change what someone does is a cost, not an asset.
We will not build a revenue chart until everyone agrees what revenue means.
We build these systems, so the model reflects how the data really behaves.
Change BI product later and you rebuild charts, not the foundation.
Every figure is reconciled before anyone is asked to make a decision on it.
Almost always because the metric was never defined, not because a chart is broken. Revenue can mean ordered, delivered, invoiced or collected, and each team quietly picks a different one. We write the definitions down first and build every dashboard from that shared layer, so two reports cannot disagree by accident.
If your questions are operational and single-source, ERP reporting is usually enough and far cheaper to run. A separate BI tool earns its place when you need to combine ERP data with other sources, hold history the ERP overwrites, or serve people who should never have ERP logins. We give you a straight recommendation either way.
It can, which is why we do not let dashboards query the live transactional database directly. We extract to a separate reporting layer on a schedule, so a badly written query in a BI tool cannot slow down the people trying to raise invoices.
As current as you actually need, which is usually less current than people first ask for. Most management reporting runs on an overnight or hourly refresh. We reserve near real-time for the few operational dashboards that genuinely change a decision within the hour, because it costs more to build and run.
Any tool that can read from a database or a documented API. The reporting layer is deliberately tool-neutral, so if you change BI product later you rebuild the dashboards rather than rebuilding the whole data foundation underneath them.
A first set of dashboards on a defined scope is usually 4 to 8 weeks. The modelling and the metric definitions take most of that. Building charts once the layer exists is quick, which is why we resist starting with the charts.
Related
The other services in this section, and related pages from TCB Infotech.
No commitment. A practical look at your reporting and where it disagrees.
