Technology — Data & Analytics
Turn data into decisions.
Data engineering, analytics, and predictive modelling for enterprises that have accumulated years of data but haven't yet unlocked its value. We build the pipelines, the models, and the dashboards — and we explain what the numbers mean.
The Reality
Most enterprises are data-rich and insight-poor.
After five or ten years of operation, enterprise systems contain an extraordinary record of customer behaviour, operational performance, product usage, and financial outcomes. That data is usually siloed across a CRM, an ERP, a data warehouse no one trusts, and a collection of spreadsheets maintained by whoever had the time.
We've worked with 30+ enterprise clients in exactly this position. The work starts with getting the data reliable and accessible — clean pipelines, a single source of truth, and a data quality framework. Then we build the models and dashboards that surface the patterns worth acting on.
Chief Architect Ali Raza leads our data practice with 20 years of experience in data science and analytics across fintech, EdTech, and enterprise software. He knows what questions are worth asking — and what analysis is just expensive noise.
Data Audit
We assess your current data landscape — sources, quality, accessibility, and the gaps between what you have and what you need.
Architecture Design
Data platform architecture selecting the right warehouse, pipeline tools, and access patterns for your scale and budget.
Pipeline Build
ETL/ELT pipelines built for reliability, observability, and incremental load — not fragile scripts that break on schema changes.
Model Development
Predictive and descriptive models developed iteratively with your domain experts, evaluated against business metrics.
Dashboard Delivery
Dashboards designed for decision-makers, tested for load, and documented for self-service use by your team.
Handover & Enablement
Full documentation, training for your data team, and optionally ongoing model maintenance and retraining support.
Data & Analytics Capabilities
From raw pipeline engineering to predictive models and executive dashboards — the full data value chain.
Data Pipeline Engineering
Robust ETL and ELT pipelines that move, transform, and load data reliably — from raw source to analytics-ready warehouse. Built for both batch and streaming workloads using Azure Data Factory, Apache Airflow, dbt, and Spark.
BigQuery & Cloud Data Warehouses
Schema design, query optimisation, partitioning, and cost management for BigQuery. Equivalent expertise in Snowflake, Azure Synapse, and Redshift. We design warehouses that are fast to query, cheap to run, and easy to extend.
Azure Data Platform
Full Azure Data ecosystem — Azure Data Factory for orchestration, Azure Databricks for large-scale processing, Azure Synapse Analytics for enterprise warehousing, and Azure Data Lake for cost-effective storage of raw and curated data.
Data Cleansing & Quality
Systematic data quality frameworks covering completeness, consistency, timeliness, and accuracy. Automated profiling, anomaly detection, deduplication, and lineage tracking — so your analytics are built on data you can trust.
Predictive Modelling
Statistical and machine learning models that generate actionable predictions from your historical data — churn prediction, demand forecasting, risk scoring, and customer lifetime value. Models delivered with explainability and confidence intervals.
Pattern Discovery & Exploration
Exploratory data analysis, cohort analysis, funnel analysis, and statistical hypothesis testing. We find the signals in your data that aren't visible in standard reports — and tell you what they mean for your business.
Business Intelligence & Dashboards
Power BI and Tableau dashboards designed for the people who make decisions — not the people who built the data model. Self-service analytics layers, row-level security, and scheduled refresh with alerting on KPI movements.
Real-Time Analytics
Streaming data pipelines using Kafka, Azure Event Hubs, and AWS Kinesis. Real-time dashboards, event-driven anomaly alerting, and low-latency analytics for operational decision-making.
Technology Stack
Analytics We've Delivered
Real problems we've solved with data engineering, predictive modelling, and analytics across industries.
Higher Education
Student success prediction and intervention scoring
Multi-model analytics combining LMS engagement, assessment scores, attendance, and demographic data to predict students at risk of course failure — four weeks before the drop deadline. Delivered ranked intervention recommendations to advisors in real time.
Fintech
Transaction anomaly detection and fraud scoring
Behavioural analytics pipeline processing high-volume payment transaction sequences to score anomaly probability in near-real-time. Integrated with an East African payment gateway serving multiple merchants and mobile wallets.
Community Platform
Discussion community health analytics
NLP and engagement analytics across millions of forum posts — topic extraction, sentiment trending, influence network analysis, and engagement decay prediction. Delivered via Power BI dashboards for community management teams.
Enterprise SaaS
Multi-tenant usage analytics and churn prediction
Usage telemetry pipeline for a SaaS platform processing event streams from thousands of enterprise users. Feature adoption scoring, health index per account, and churn probability model driving customer success team prioritisation.
Sitting on years of data you haven't fully used?
Let's look at what you have and map out the analysis that would be most valuable to your business.