Sales, stock and sensor data sit in separate places.
Duplicates, gaps and errors are fixed on the way in.
One trusted source, updated on a schedule you set.
Dashboards and models all use the same agreed figures.
Data Engineering
Reliable data your teams can report on.
We collect data from your scattered systems, clean it and store it in one well-organised place. Your reports, dashboards and models then draw on figures everyone agrees on.
What you get
01One source of truthSales, finance and operations figures pulled together and reconciled in one store.
02Automated pipelinesScheduled data loads that replace manual spreadsheet exports and copy-pasting.
03Reports people trustClear definitions for each metric, so meetings stop arguing over whose number is right.
How we deliver
Four stages, each ending with something you can see and review before the next one starts.
01
Map
List your data sources, who uses them and the reports or decisions that depend on them.
02
Model
Agree metric definitions and design the structure of the central store.
03
Build
Create pipelines, quality checks and the first set of reports on real data.
04
Hand over
Document everything, train your staff and support the platform as it grows.
What we buildOur data engineering capabilities
Data pipelines
Automated jobs that move data from your apps and databases into a central store.
Discuss thisData warehouses
Designing a central database built for reporting and analysis across the business.
Discuss thisData lakes
Low-cost storage for large raw files, logs and sensor data kept for later analysis.
Discuss thisData modelling
Organising tables and defining metrics so the same question gives the same answer.
Discuss thisDashboards and reporting
Visual reports for managers, built on checked data rather than manual extracts.
Discuss thisReal-time streaming
Handling events as they happen, for live tracking, alerts and operational screens.
Discuss thisData quality checks
Automatic tests that catch missing, duplicated or out-of-range values early.
Discuss thisData governance and access
Rules on who can see what, with audit trails and handling of personal data.
Discuss thisKlasendra
Decades of seismic graphs existed only on paper, so the archive could not be analysed.
Selected work · KlasendraAnimated illustration
Energy sector: data recovered from paper archives
What we built
- A specialised OCR system for paper seismic graphs
- Extracts structured data from each graph
- Makes the historical archive available for analysis
What it changed
The energy company can analyse its historical archive for the first time.
Delivered by Hoki and its engineering partners. Product and client names belong to their owners.
Discuss a similar projectFrom the Hoki portfolio
The technology we build with
We pick tools around your existing systems, your team and how the product will be run.
Storage and warehouses
PostgreSQLSnowflakeBigQueryAmazon RedshiftDatabricks
Pipelines and processing
Apache AirflowdbtApache SparkApache KafkaFivetranAirbyte
Reporting
Power BITableauLookerMetabaseApache Superset
Where this applies
The same engineering, shaped by the rules and realities of each sector.
Retail and e-commerce
Combining store, online and stock data to see what sells, where and at what margin.
Logistics and supply chain
Shipment, warehouse and carrier data joined up for live tracking and cost analysis.
Financial services
Controlled reporting pipelines with audit trails for finance and regulatory returns.
Manufacturing
Machine and production data collected for yield, downtime and quality analysis.
Energy and utilities
Meter and sensor readings stored at scale for usage analysis and forecasting.
Public sector and education
Bringing records from separate departments into one governed reporting store.
Frequently asked questions
Can you work with our existing databases and software?
Yes. Most projects start from systems already in place, such as accounting, ERP, CRM or custom databases. We connect to them through their APIs, database access or file exports, without replacing them.
Should our data be in the cloud or on our own servers?
Either can work. Cloud warehouses are quicker to set up and scale easily. On-premise suits strict data residency rules. We explain the trade-offs in cost, control and maintenance and you decide.
How do you handle personal and sensitive data?
We apply access controls, encryption and masking where needed, and follow the data protection laws that apply to you, such as PDPA in Singapore. Sensitive fields are only exposed to people who need them.
Can we start with one report rather than a full platform?
Yes, and we often recommend it. Building one valuable report end to end proves the approach and the data quality. The platform then grows one source and one report at a time.
Another question? Email hello@hoki.co
Spending too long reconciling reports?
Show us where your data lives and which figures matter most, and we will propose a sensible first step.
Start a project
Tell us what you want to build.
Share a few details about your data engineering project. We will reply with questions and a suggested next step.
- What problem you want solved
- What you already have in place
- Any timing or budget you are working to
Start a project
Tell us what you want to build
A few details help us bring the right people to the first call.
Thank you.
Your enquiry is with our team. Here is what happens next.
1We read your enquiry and bring in the people best placed to help.
2We reply by email to arrange a call at a time that suits you.
3On the call, we agree a clear next step, with scope and cost.
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