Enterprise Data Solutions — Our Capabilities
Comprehensive enterprise data solutions capabilities delivered by certified specialists.
Data Warehouse Implementation
Cloud data warehouse design and build on Snowflake, BigQuery, and Redshift — scalable, governed, and query-optimised.
Lakehouse Architecture
Modern lakehouse implementations on Databricks and Delta Lake — combining data lake flexibility with warehouse performance.
ETL/ELT Pipelines
Reliable data pipelines using dbt, Informatica, SnapLogic, and Azure Data Factory — with monitoring, alerting, and lineage tracking.
BI & Dashboard Development
Power BI, Tableau, and Looker dashboards designed for business users — self-service analytics without the complexity.
Data Governance
Data cataloguing, lineage, quality rules, and access control — ensuring your data is trusted, compliant, and discoverable.
Real-Time Analytics
Streaming data pipelines using Kafka, Spark Streaming, and Kinesis — delivering real-time insights for operational dashboards and alerts.
Our Delivery Process
A structured, transparent process designed to deliver results — not just outputs.
Data Discovery
We audit your data sources, volumes, quality, and current reporting landscape — identifying gaps and opportunities.
Architecture Design
We design a scalable, cost-effective data architecture aligned to your analytics use cases and growth trajectory.
Pipeline Development
Data pipelines are built with idempotency, monitoring, and alerting — so failures are caught and corrected automatically.
Data Modelling
Dimensional or data vault models are built for analytical performance and business understandability.
BI & Insight Delivery
Dashboards and self-service analytics are deployed with user training and adoption support.
Why It Matters
Tools & Technologies
Industry-standard platforms and frameworks we use to deliver enterprise data solutions.
Clients Who Trust Rapson
Frequently Asked Questions
A lakehouse combines a data lake’s flexibility for raw, unstructured data with a data warehouse’s performance for analytics. It’s ideal for organisations with diverse data types, large volumes, and both historical analysis and real-time analytics needs.
We implement data quality rules, validation checks, and monitoring at every stage of the pipeline — with automated alerts for data quality violations and a clear remediation process.
Yes. We build data layers that connect to whatever BI tool your teams already use — Power BI, Tableau, Looker, Qlik, or custom dashboards.
A foundational data warehouse with core pipelines and initial dashboards typically takes 3–5 months. We recommend a phased approach — delivering business value at each stage rather than waiting for a ‘big bang’ delivery.
