Engineering an analytics and reporting platform for Awash Bank

Banks generate data across many systems — accounts, transactions, lending, channels — and turning that raw material into reporting people can act on is a genuine engineering problem, not a matter of connecting a dashboard to a database. Data has to be sourced, modelled, reconciled and made consistent before a chart on top of it can be trusted.

For a bank building out its analytics capability, the difficulty is as much about trust and governance as about visualisation. Reports that disagree with one another, or that cannot be traced back to a definition, undermine the very decisions they are meant to support, so the platform beneath the dashboards matters more than the dashboards themselves.

Delivering this on Tableau meant engineering both layers: the data foundation that produces clean, consistent, well-defined measures, and the reporting layer that presents them to the bank's teams in a usable form.

A bank runs on its numbers. Leadership needs a reliable view of performance, risk and customers to steer the business, and teams across the bank need consistent reporting to do their work. Analytics that cannot be trusted are worse than none, because they move decisions in the wrong direction with false confidence.

The capability stake is the bank's ability to see itself. A governed analytics and reporting platform is the difference between reconstructing the picture by hand each time it is needed and having a dependable, shared view the whole organisation can work from.

The engineering team began with the data: understanding the sources, agreeing the definitions of the measures that mattered, and designing a data model that could produce consistent, governed reporting rather than a set of one-off extracts.

The data engineering that fed Tableau was built to make the reporting layer trustworthy — sourcing, shaping and reconciling data so that what appears in a dashboard traces back to an agreed definition rather than a hidden query.

Reporting was then built iteratively on Tableau, developing and validating dashboards and reports with the bank's users so the platform reflected the questions people actually needed answered, and hardening it as it went rather than treating governance as an afterthought.

Cloud23 engineered an analytics and reporting platform on Tableau, backed by the data engineering that makes such a platform dependable. The result gives the bank governed dashboards and reports built on a consistent data foundation rather than ad hoc extracts.

The data-engineering layer sources and shapes the bank's data into clean, well-defined measures, so the reporting on top is consistent and traceable — the same definition producing the same number wherever it appears.

On that foundation, Tableau presents the reporting to the bank's teams in a usable, visual form, giving people across the organisation a shared way to see performance and answer the questions their work depends on.

The programme delivered a governed analytics and reporting capability, giving the bank dashboards and reports built on a consistent, well-defined data foundation rather than a scatter of disconnected extracts.

The platform gives the bank's teams a shared, trustworthy view of the business — reporting that traces back to agreed definitions, so numbers can be relied on rather than reconciled by hand each time they are needed.

Because the capability is built on an engineered data foundation, it gives the bank a base to extend as new reporting questions arise, rather than a fixed set of dashboards that must be rebuilt when needs change.