End-to-End Data Services

From raw data ingestion to AI-powered decision systems — we cover every layer of your data platform.

Data Warehouse Design & Build

We design and deliver enterprise data warehouses from the ground up — starting with your business questions, working back to the right schema, and building the pipelines that keep it current and trusted.

Our architects are fluent in Kimball, Inmon, Data Vault 2.0, and medallion (Bronze/Silver/Gold) patterns. We select the methodology that fits your volume, team, and governance requirements — not the one we always use.

Dimensional Modelling: Star schema, snowflake, and conformed dimensions built to Kimball standards
Data Vault 2.0: Hub-Link-Satellite models for auditability and agility in high-change environments
Medallion Architecture: Bronze/Silver/Gold lakehouse patterns on Azure Synapse and Microsoft Fabric
Performance Engineering: Columnstore indexes, partitioning, distribution strategies, and materialised aggregations
Data Governance: Lineage tracking, data dictionary, POPIA-compliant classification, and row-level security
Technologies
Azure Synapse Dedicated Pool Microsoft Fabric SQL Server Delta Lake T-SQL dbt Data Vault 2.0
Typical Outcomes
Single source of truth across all business units
Month-end reporting reduced from days to hours
Full audit lineage for regulatory submissions
3–5× query performance vs legacy systems
Self-service analytics for business users
Reference projects
Banking · Insurance · Retail · Mining · Financial Institutions

Pipeline Design & ETL/ELT Build

We build the pipelines that keep your data warehouse current, accurate, and governed. From batch nightly loads to real-time streaming, we engineer for reliability, scale, and observability.

ADF Orchestration: Parameterised, reusable pipeline factories with automated retry, alerting, and monitoring
PySpark at Scale: Databricks notebooks and Delta Live Tables for high-volume distributed processing
CDC & Incremental Loads: Change-data-capture from SQL Server, Oracle, SAP, Salesforce, and REST APIs
Data Quality Frameworks: Automated validation, null checks, reconciliation, and quarantine patterns
CI/CD for Data: Azure DevOps or GitHub Actions pipelines with automated testing and deployment
Technologies
Azure Data Factory Azure Databricks Apache Spark / PySpark AWS Glue Python ADLS Gen2 Azure DevOps
Typical Outcomes
Fully automated end-to-end data refresh
Pipeline failures detected and alerted in <5 minutes
50M+ records processed within SLA windows
Zero manual data transformation steps
Reusable pipeline templates cut future build time by 60%

Cloud Migration & Architecture

We migrate on-premises data warehouses and databases to cloud-native platforms on Azure, AWS, and GCP — with zero data loss, improved performance, and dramatically reduced infrastructure cost.

Migration Assessment: Source system analysis, schema mapping, complexity scoring, and migration roadmap
Azure Synapse Migration: SQL Server, Oracle, Teradata → Synapse Dedicated Pool with T-SQL refactoring
Microsoft Fabric: Lakehouse design, Direct Lake semantic models, and OneLake architecture
Cross-Cloud Pipelines: AWS S3 → ADLS Gen2, GCS → Azure, and hybrid on-prem/cloud architectures
Infrastructure as Code: Terraform-managed environments with DevOps-automated deployments
Platforms
Microsoft Azure Amazon Web Services Google Cloud Microsoft Fabric Terraform Azure DevOps
Typical Outcomes
40–65% infrastructure cost reduction post-migration
99.8%+ data fidelity validated post-migration
3× average query performance improvement
On-prem server decommissioned within project window
Elastic scaling for seasonal workload spikes

AI & Machine Learning

We build ML models that integrate directly into your data warehouse — not standalone experiments, but production systems that update daily, explain their decisions, and drive real business actions.

Predictive Modelling: Churn prediction, credit scoring, fraud detection, and risk classification at scale
Explainable AI: SHAP-based model explainability ensuring regulatory transparency and auditability
NLP & Document AI: Automated document extraction, sentiment analysis, and text-to-SQL assistants
Geospatial ML: Location-based risk scoring, hotspot detection, and GIS-integrated analytics
Generative AI Integration: LLM-powered data assistants and automated report generation via Azure OpenAI
Technologies
Python / scikit-learn XGBoost / LightGBM Azure Databricks ML SHAP Azure OpenAI GeoPandas TensorFlow
Typical Outcomes
Models refreshed daily from DW Gold layer
Audit-ready SHAP explanation reports
Fraud detection integrated into operational systems
>80% precision in pilot predictive deployments

Analytics & Reporting

We turn your Gold-layer data warehouse into dashboards and reports that executives actually use. No more Excel exports. No more waiting for IT. Self-service analytics at every level of the organisation.

Power BI Development: Semantic models, DAX measures, DirectQuery, Import, and Composite mode design
Row-Level Security: Dynamic RLS ensuring each user sees exactly their data — no more, no less
Embedded Analytics: Power BI Embedded and custom React/Chart.js dashboards for client-facing portals
Actuarial & Regulatory Reports: Bordereau, IFRS 17, SOLVENCY II, and SARB reporting templates
Technologies
Power BI Desktop & Service DAX Power BI Embedded React / Chart.js Paginated Reports
Typical Outcomes
Executive dashboards adopted as operational standard
Month-end reporting time reduced by 80%+
200+ concurrent self-service users enabled
Regulatory reports auto-generated and submitted

Database Design & Optimisation

Deep T-SQL expertise and database engineering for SQL Server, Azure Synapse, and PostgreSQL. From schema design to stored procedure development, indexing strategy, and query tuning.

T-SQL Development: Complex stored procedures, OPENJSON extraction, window functions, and dynamic SQL
Synapse Constraints: Expert handling of Columnstore, distribution, statistics, and workload management
Performance Tuning: Execution plan analysis, index strategy, partitioning, and statistics management
Schema Design: Physical data modelling, normalisation, surrogate key strategy, and naming standards
Technologies
SQL Server Azure Synapse SQL PostgreSQL / PostGIS T-SQL Columnstore Indexes Azure SQL
Typical Outcomes
Query runtimes reduced by 2–5× through indexing
Stored procedures fully documented and version-controlled
Zero production failures from Synapse constraint violations

Our Delivery Process

Four phases, Agile-aligned, with full client visibility at every step.

01

Discover

Source system analysis, stakeholder workshops, data profiling, and DW scoping. We understand your data before we touch it.

02

Design

Logical and physical data model, ERD, pipeline architecture, naming conventions, security design, and performance strategy.

03

Build

Sprint-based pipeline development, stored procedure coding, unit testing, data reconciliation, and iterative delivery.

04

Deploy

UAT support, performance tuning, CI/CD setup, full documentation, and knowledge transfer to your internal team.

Ready to Start Your Data Warehouse Project?

Talk to our architects about your requirements. We'll scope it, price it, and deliver it.

Request a Scoping Call →