Drayage logistics
A logistics data platform that answers in seconds
The platform got faster through diagnosis and code, on the same server.
See the project ↗Services / Data platforms
Get the numbers while they still matter.
Connect raw data to useful decisions, with a warehouse, pipeline, and reporting layer built around the people using them.
Does this sound familiar?
A good fit when…
- Reports arrive after the decision has been made
- Different systems disagree about the same number
- Slow queries or refresh cycles hold the team back
From the problem to the handover
What we’ll build.
What you’ll keep.
The numbers arrive too late, too slowly or in too many versions to act on. Reports finish after the decisions they were meant to inform, and nobody is sure which spreadsheet is current.
- 01 / Deliverable
A warehouse and pipeline built from nothing or rebuilt in place
- 02 / Deliverable
Indexes and queries tuned against measured timings
- 03 / Deliverable
Dashboards fed from data that is current enough to act on
- 04 / Deliverable
Role-based access, with personal details kept off dashboards where the data is sensitive
- 05 / Deliverable
Before and after timings, written down with how they were measured
How we get there
- 01
Measure where the time goes before changing anything: query plans, pipeline timings and the full cycle end to end.
- 02
Fix the cause in code before anyone buys a bigger server.
- 03
Build or rebuild the warehouse in layers, from raw sources to clean, reporting-ready tables, loading only what changed.
- 04
Keep sensitive details off the screen: dashboards show the metrics people need with no personal details, behind role-based access.
Experience you can inspect
Similar challenges.
Concrete outcomes.
Earlier work that informs how I approach this service. Each engagement has its own scope.
Before we start
A few useful answers.
Bring a report, a slow query, or a decision people cannot make with today’s data. We’ll trace its sources and where the time or trust is lost.
More about working together ↗Does Aternex work with our existing database?
Yes. I have shipped production work on PostgreSQL, SQL Server and Snowflake, and loaded data out of MongoDB, and I work in whatever the business already runs.
Do we need a bigger server?
Usually not first. On one logistics pipeline, several rounds of measured fixes in code took the cycle from 11 to 16 minutes down to 6.8 to 17.3 seconds; at the 50-second stage, 30 seconds of each cycle turned out to be metadata overhead, and a cached refresh log removed it.
How is sensitive data kept out of reports?
Dashboards show the metrics people need with no personal details on screen, and what each person can see is gated by role. On one clinical analytics dashboard, facility metrics were shown with no patient details, behind role-based access.