Enterprise data
platforms
Design and build cloud data warehouses, lakehouses and dependable pipelines. Bring fragmented sources together in a manageable, cost-effective data landscape.
Turn complex data into trusted insights, intelligent automation and confident decisions. We connect your business ambitions to practical enterprise delivery.
Based in South Africa. Built for enterprise challenges.
Technology expertise.
Business perspective.
Organise. Analyse. Commercialise. Our services help you take control of your data and put it to work.
Design and build cloud data warehouses, lakehouses and dependable pipelines. Bring fragmented sources together in a manageable, cost-effective data landscape.
Give teams a consistent view of performance with trusted semantic models, clear KPIs and reporting that supports evidence-based decisions.
Identify practical AI opportunities, prepare the data they need and automate repetitive processes. Build towards forecasting and predictive analytics with a reliable foundation.
Align your data roadmap to business priorities. Establish ownership, quality controls and shared definitions so that your teams can work with confidence.
Improve the reliability and performance of existing platforms, pipelines and reporting. Keep your data environment useful as business needs evolve.
Start with the business problem. We’ll help you assess the current landscape, identify priorities and define a practical next step.
Our solutions are shaped by practical experience in complex, data-intensive business environments.
Customer insights, operational reporting and dependable data for business decisions.
Connected reporting across commercial, customer and operational performance.
Data foundations and analytics to understand performance and support planning.
A clearer view of customer journeys, engagement and service performance.
A selection of the work behind our approach, described by business need and industry.
Customer 360 modelling and reporting across application volumes, conversion and abandonment, supporting a clearer understanding of customer behaviour and product holdings.
Cloud data transformation and business intelligence using Snowflake, dbt and Power BI to connect data preparation with commercial and financial reporting.
Databricks and Power BI delivery across workforce reporting, learning data ingestion, effective-dated models and consistent business measures.
Integration, modelling and pipeline improvements that turn source-system data into structured information for reporting and analytics.
Experience reflects work led by Qubitron’s founder, including consulting engagements. Client names and confidential project information are withheld.
We help your business understand, predict and optimise performance through data-driven tools and capabilities. Our approach combines technical depth with an understanding of the decisions your business needs to make.
From accessing and organising data to describing, diagnosing, predicting and shaping performance, we help turn your data sources into accessible insights.
To be the leading business intelligence and machine learning organisation in the Southern African region and beyond.
We extract valuable insights from organisational data sources to facilitate better decision making.
Founder & Director, Qubitron
A senior data engineering, business intelligence and analytics consultant with enterprise delivery experience across financial services, telecoms, customer experience and other data-intensive environments.
Practical expertise across Microsoft Fabric, Azure, SQL Server, Power BI, Databricks, data architecture and AI-ready analytics platforms.
Clarify the business problem, stakeholders and decisions that matter.
Assess the data landscape and agree a practical architecture and roadmap.
Build, validate and refine with business users throughout delivery.
Support adoption, document the solution and help your teams use it.
Open a topic for a quick perspective on building platforms that support better decisions.
Useful AI depends on accessible, well-defined and reliable data. Before choosing a model, identify the business decision, assess source quality and establish ownership. A dependable data foundation makes AI initiatives easier to evaluate and sustain.
When teams calculate the same measure differently, reporting becomes a reconciliation exercise. Shared business definitions and governed semantic models help everyone work from the same numbers, with clear ownership and traceability.
A data platform creates value when people can use it. Start with business questions and work backwards through measures, models and pipelines. This keeps engineering priorities connected to reporting, planning and operational action.
Tell us about your challenge. Let’s explore the right next step for your data, analytics or AI journey.