Admin dashboards

What it is

An internal view of data that already exists somewhere: headline metrics, the records underneath them, filters, saved views, drill-down into the rows behind a number, and an export when someone needs it in a sheet. It reads your systems rather than replacing them.

Why businesses need it

Operational decisions are made quickly and will not wait on a query. When the number on the screen is stale, undefined or takes half a minute to load, the team goes back to the spreadsheet it came from and the dashboard quietly stops being used.

What MIWEBX delivers

• Operations, support, finance and management views over existing databases
• Metric tiles with their definition, time range and comparison on the page
• Filterable record tables with saved views per team or role
• Drill-down from any figure to the individual rows that produced it
• Exports and scheduled reports delivered by mail
• Role-scoped access so each team sees its own records only

Core features

• Every headline number links to the rows behind it
• Filters, sort and page kept in the URL so a view is shareable
• Date ranges compared against a stated previous period
• Nulls, partial days and timezone edges shown instead of hidden
• Column-level restriction on anything sensitive, including salary and contact data
• Wide exports queued and capped rather than run against the live system

Technical capabilities

• Query layer checked for repeated per-row fetching and full table scans before a view ships
• Aggregations pre-computed or materialised where live counting is too costly
• Indexes added on the columns the filters actually use, verified by reading the plan
• Keyset pagination on large tables so deep paging stays cheap
• Access rules enforced server-side, never only in the menu
• Slow queries logged with their timings so the cost stays visible to the owner
• Reporting reads kept off the transactional path where volume demands it

How we build it

• List the decisions the screen has to support before drawing it.
• Agree and write down one definition for every number.
• Map each metric to its query, tables and cost.
• Build the table and the drill-down path first, the tiles second.
• Run it against real data volumes, then index what is slow.
• Set roles, exports and refresh, and hand over the definitions.

Technology stack

• React
• Next.js
• TypeScript
• Node.js
• PostgreSQL
• Prisma
• Redis
• Looker Studio

What you receive

• The dashboard deployed with its queries and definitions documented
• Role-based access mapped to the teams that use it
• Saved views and export paths for the recurring reports
• A metric dictionary stating how each number is calculated
• Query cost and refresh notes for anything on a schedule

Business benefits

• Staff stop rebuilding the same report every week
• Management sees status without asking for an update
• Arguments move from the number to the decision
• Several logins and a folder of exports collapse into one screen