01
Source discovery
Map databases, files and applications, their access permissions and the records your reports need.
Data engineering
Connect the information.
Clarify the next decision.
Data pipelines, integrations and reporting datasets that bring agreed sources together with clear validation and quality checks.
ROOTED IN SRI LANKA. BUILT AROUND YOU.02 / Data engineering
THE RIGHT STARTING POINT
Understand the work.
Define the right solution.
A useful report begins long before a dashboard. We discuss where your data comes from, what it means, how it changes and which checks it needs before it can support reporting.
- Agreed source definitions
- Visible data-quality checks
- Reporting-ready datasets
FROM REQUIREMENTS TO HANDOVER
A scope you can review.
A path you can follow.
These are areas we can discuss. Your quotation defines which deliverables are included in your project.
02
ETL / ELT pipelines
Scope collection, transformation and loading steps, including refresh schedules and failure handling.
03
Validation & modelling
Define required fields, duplicate rules, joins and reporting models without guessing missing information.
04
Operation & handover
Agree monitoring, documentation, ownership and the support needed to keep a pipeline running.
INTERACTIVE EXAMPLE / FICTIONAL DATA
Follow a data pipeline
Run sample records through validation, inspect the quality report and prepare a clean CSV with a guided walkthrough.
Start the guided demo01 / FOLLOW A WORKFLOW02 / SEE THE RECORDS CHANGE03 / EXPLORE THE RESULT
A working sample to explore possibilities. Production features and delivery are agreed separately.
POSSIBLE STARTING POINTS
Start with your working day.
Illustrative situations to help you describe what you need.
Bring exports together
Explore how sales files and a product catalogue could become a consistent reporting dataset.
Explain data quality
Make rejected, changed and duplicate records visible so your team can investigate the source.
Connect reporting sources
Plan refresh needs and common definitions across the systems used by different teams.
A CONSIDERED DELIVERY PROCESS
Clarity at every stage.
- 01
Discover
Understand users, workflows, constraints and priorities.
- 02
Define
Agree deliverables, price, responsibilities and acceptance checks.
- 03
Develop & review
Build or configure the agreed solution and review the scoped work.
- 04
Handover & support
Agree documentation, access, team guidance and ongoing arrangements.
What shapes the quotation?
Sources, access permissions, volumes, refresh frequency and platform requirements are agreed first. Cloud usage, licences, migration and ongoing operation are itemised separately.
Gokly is preparing its services for launch. Availability, suitability and terms are confirmed before work begins.
Prepare a relevant enquiryBEFORE WE BEGIN
A few useful answers.
Have a different question? Share a brief outline of your requirements.
Let’s discuss itCan you work with our current data sources?
We first check access, export options, permissions, volume and source quality. Compatibility and the proposed connection are included in the agreed scope.
Will the pipeline correct missing data?
Rules can standardise known formats and validate values. Missing or conflicting information should be held for review rather than invented.
Is a dashboard included?
Reporting datasets and dashboards are separate deliverables unless explicitly included together. We agree the report definitions, audience and refresh requirements during discovery.
LET’S MAKE IT HAPPEN
Your next step.
A clearer conversation.
Tell us what you want to achieve with data engineering. We’ll discuss suitability, scope and a practical way forward.