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Data EngineeringService — KorabTech Technologies

Raw data.Into decisions.At Nigerian scale.

We build data warehouses on Snowflake and BigQuery, dbt transformation pipelines, Airflow orchestration and Power BI dashboards that give Nigerian executives real-time intelligence. Nigerian businesses generate enormous data every day — almost none of it is properly engineered into insight.

Request Free Consultation📊 Try Live Data Analysis Demo
Snowflake
& BigQuery warehouses
dbt
Transformation pipelines
Power BI
& Looker dashboards
Real
time streaming
🏗️
Data Warehouse Design & Build
Modern cloud data warehouse on Snowflake or Google BigQuery — dimensiona...
Available
🔄
ETL/ELT Pipeline Engineering
Automated data pipelines from source systems to the warehouse — using Fi...
Available
📊
BI & Dashboards
Executive and operational dashboards in Power BI, Looker or Metabase — r...
Available
⚡
Real-time Streaming Analytics
Event streaming pipelines for real-time intelligence — transaction fraud...
Available
Why Now

Nigerian businesses are generating data they cannot read. That is a competitive crisis.

MTN Nigeria processes 100 million transactions daily. Nigerian commercial banks onboard tens of thousands of customers per week. FMCG distributors move millions of SKUs across 36 states. All of this produces data — and almost none of it is properly engineered into a form that executives can act on.

The typical Nigerian enterprise analytics situation: disconnected source systems, Excel-based reporting with week-old data, no single source of truth and business decisions made on gut feel because reliable data is not available fast enough to inform them.

KorabTech builds modern data infrastructure — centralised warehouses, automated pipelines, governed data models and self-service dashboards. Your CEO should be able to open a phone and see last night's revenue.

100M+
Transactions MTN Nigeria processes daily — almost zero analytics depth
₦14T
SME financing gap — driven partly by lack of proper financial data
Excel
Most Nigerian enterprise reporting is still manual spreadsheet-based
What We Build

8 Data Engineering service offerings.

Every service includes full documentation, source code handover and a 90-day post-launch support window.

🏗️
Data Warehouse Design & Build
Modern cloud data warehouse on Snowflake or Google BigQuery — dimensional modelling, data vault design, schema governance and access control. Your single source of truth.
SnowflakeBigQueryRedshiftData VaultStar Schema
🔄
ETL/ELT Pipeline Engineering
Automated data pipelines from source systems to the warehouse — using Fivetran, Airbyte or custom Python/Spark pipelines with full lineage tracking.
dbtFivetranAirbyteApache SparkAirflowPython
📊
BI & Dashboards
Executive and operational dashboards in Power BI, Looker or Metabase — revenue analytics, customer cohort analysis, operational KPIs and self-service reporting.
Power BILookerMetabaseTableauDAXLookML
⚡
Real-time Streaming Analytics
Event streaming pipelines for real-time intelligence — transaction fraud detection, clickstream analysis, live operational dashboards using Apache Kafka and Flink.
Apache KafkaApache FlinkKinesisSpark Streaming
🤖
AI-powered Analytics
Natural language query on your data warehouse — executives ask questions in plain English and get charts and tables. Anomaly detection, demand forecasting and churn prediction.
dbtGPT-4LangChainAutoMLBigQuery MLVertex AI
🗂️
Data Governance & Cataloguing
Data catalogue implementation, column-level lineage, PII tagging for NDPC compliance, data quality rules and master data management.
Monte CarloGreat ExpectationsOpenMetadatadbt Tests
📱
Self-service Analytics Enablement
Train your business team to build their own reports. BI tool deployment, semantic layer design, training programmes and ongoing support.
Power BILooker StudioMetabaseTrainingSemantic Layer
💾
Data Lake Architecture
Raw data lake on S3 or GCS — Bronze/Silver/Gold medallion architecture, schema-on-read for unstructured data and Delta Lake or Apache Iceberg table formats.
S3GCSDelta LakeApache IcebergAWS GlueDatabricks
Use Cases

Real Nigerian business problems we solve.

Live opportunities in the Nigerian market — businesses currently paying overseas rates for these exact solutions.

01
🏦 Banking
Real-time Transaction Analytics for Commercial Bank
Unified data warehouse consolidating core banking, mobile, internet banking and card systems. Executive dashboard with real-time deposit and loan portfolio metrics. Fraud alert pipeline with sub-60-second detection.
02
📦 FMCG
Distribution Analytics for FMCG Company
Analytics platform consolidating 800 distributor sales reports into a single BigQuery warehouse. SKU-level sell-out data, territory performance and demand forecasting reducing out-of-stock events by 30%.
03
🏥 Healthcare
Patient Flow Analytics for Hospital Group
Hospital analytics — bed occupancy, patient wait times, revenue-per-department, physician productivity and predictive discharge planning. Reduces average length of stay by identifying bottlenecks.
04
📡 Telecoms
Churn Prediction for Nigerian Telecoms
ML churn prediction model on subscriber usage data — identifies high-risk subscribers 30 days before churn, triggers targeted retention interventions and reduces monthly churn rate by 18%.
05
🛒 E-Commerce
Customer Lifetime Value Analytics
Analytics platform — customer segmentation by LTV, product affinity modelling, personalised recommendation data layer and marketing attribution across Google, Meta and email channels.
06
🏛️ Government
Social Programme Impact Analytics for Federal MDA
Data platform for a federal social protection programme — beneficiary registration, payment disbursement tracking, leakage detection and impact measurement for World Bank reporting.
Technology Stack

The tools our engineers actually use.

No proprietary lock-in. No obsolete frameworks. The same tools the best firms globally use.

❄️
Snowflake
Cloud data warehouse
🔶
Google BigQuery
Serverless analytics
🔴
Amazon Redshift
AWS data warehouse
🔧
dbt
Data transformation
🌀
Apache Airflow
Pipeline orchestration
⚡
Apache Kafka
Event streaming
📊
Power BI
BI dashboards
👁️
Looker
Data exploration
🔵
Fivetran
Data connectors
🚀
Apache Spark
Big data processing
🐍
Python
Data engineering
🧊
Delta Lake
Open table format
Our Process

How a Data Engineering project gets built.

Every project follows a structured, phased delivery process. Each phase has a defined deliverable, a sign-off milestone and a go/no-go before the next phase begins. You see exactly where your project stands at all times.

Phase 1
Data Discovery
Source system audit, data quality assessment, business requirements workshops and data model design.
2 weeks
Phase 2
Foundation Build
Cloud warehouse setup, IAM and access control, pipeline framework and CI/CD for dbt models.
2–3 weeks
Phase 3
Pipeline Development
Source-to-warehouse connectors, dbt transformation models, data quality tests and documentation.
4–10 weeks
Phase 4
Dashboard Development
BI tool setup, semantic layer design, dashboard builds and UAT with business stakeholders.
3–6 weeks
Phase 5
Governance & Training
Data catalogue, lineage documentation, NDPC PII tagging, business user training and adoption support.
2 weeks
Phase 6
Operations & Growth
Pipeline monitoring, dbt model maintenance, new source integrations and dashboard iteration as business needs evolve.
Ongoing
Pricing

Flexible pricing for every scale.

All projects start with a free discovery call. Final quotes depend on scope — contact us for a tailored proposal with no hidden fees.

Starter
Data Foundation
  • Data warehouse setup (Snowflake or BigQuery)
  • Up to 3 source system connectors
  • Core dbt transformation models
  • Executive dashboard (Power BI or Looker)
  • 30-day post-launch support
Get Started
Growth
Full Data Platform
  • Full data warehouse + data lake
  • Up to 10 source system connectors
  • Complete dbt model suite
  • 3 executive dashboards + self-service layer
  • AI-powered natural language query
  • 90-day post-launch support
Request Quote
Enterprise
Managed Data Platform
  • Unlimited data sources
  • 24/7 pipeline monitoring
  • Dedicated data engineer
  • Monthly data quality reports
  • Ongoing dbt model development
  • NDPC compliance management
Get Started
FAQ

Common questions answered honestly.

What source systems can you connect to?
We have built connectors for most common Nigerian enterprise systems — Flexcube, Finacle and T24 core banking, SAP and Oracle ERP, Salesforce and HubSpot CRM, Paystack and Flutterwave payment APIs, and custom in-house systems via REST API or database replication. Fivetran and Airbyte give us 300+ pre-built connectors for SaaS tools.
How long before we see our first dashboard?
Typically 6–8 weeks from kick-off to first production dashboard. The first 3–4 weeks focus on pipeline engineering (getting data into the warehouse), the next 2–3 weeks on transformation models, and the final 1–2 weeks on dashboard builds. We deliver incremental value throughout — you see data flowing in the warehouse from week 2.
What is the difference between a data warehouse and a data lake?
A data warehouse stores clean, structured, query-optimised data for business analytics — think dashboards and reports. A data lake stores raw, unprocessed data in its original format — useful when you want to keep everything and decide how to use it later. Most Nigerian enterprises start with a warehouse (immediate business value) and add a lake layer as their data maturity grows.
Do you use Nigerian data centres or international cloud?
We use international cloud providers (AWS, GCP) for data warehousing because they offer capabilities that local data centres cannot match. For clients with strict NDPC data residency requirements, we design storage architecture to comply — typically using the AWS Africa (Cape Town) region and documenting the data flow for regulatory examination.
Ready to Build

Your Data Engineering project.
Our engineers. Nigeria's infrastructure.

Book a free 60-minute technical consultation. No pitch, no obligation — just an honest conversation about your project and what it takes to build it right.

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