Analytics Engineering
Siloed teams, poor data quality, and governance bolted on too late often results in programmes that underdeliver. At Entelect, we embed into your teams and build analytics engineering solutions that fit your architecture, your controls, and business needs – from data modelling and transformation pipelines to security, visualisation, and DevOps-aligned deployment.
Our Work
Standard Bank's Corporate and Investment Banking division needed a smarter way to manage customer data across complex risk functions.
Standard Bank's CIB Risk division sought to elevate their team ability to access consistent, governed customer data. They needed a platform that could consolidate data sources, enable self-service reporting, and uphold strict regulatory and access control requirements.
Entelect partnered with Standard Bank to design and deliver an API platform, offering downstream applications a governed catalogue of API endpoints. Business rules were applied to ensure data consistency, with user restrictions managing access control. Datasets and database views were built to support secure, self-service reporting – with all data sourced from a trusted, curated foundation.
Data consolidation: A single source of truth replaced fragmented spreadsheets, eliminating reporting errors and improving governance across the CIB Risk ecosystem.
Operational agility: Teams gained self-service access to real-time data, reducing reliance on manual processes and improving efficiency across reporting and compliance workflows.
Scalable foundation: Enhanced data governance and Power BI integration created a platform built for future data-driven features and long-term growth.
What We Do
Analytics Engineering
Bridges the gap between data platforms and decision‑making by transforming raw data into analytics‑ready assets that scale across dashboards, applications, and advanced analytics use cases.
Analytics Data Modelling and Transformation
Designing and building fact and dimension models that represent the business in a consistent, performant, and analytics‑ready way. This includes reusable transformation logic, stable schemas, and clearly defined grain.
Semantic Modelling and Metrics Governance
Creating governed semantic layers and shared metric definitions so that key business measures are consistent across reports, teams, and tools – eliminating conflicting numbers and enabling reliable self-service analytics.
Data Quality, Testing and Trust
Embedding automated data quality checks, freshness monitoring, and analytics‑specific tests directly into the analytics lifecycle, ensuring decisionmakers can trust the data they consume.
Analytics Delivery and Visualisation
Building user‑friendly, analytical experiences - dashboards, reports, and embedded analytics - on top of well‑engineered models.
Analytics DevOps and Lifecycle Management
Implementing version control, CI/CD, and deployment pipelines for analytics assets - aligned with your DevOps philosophy.
Analytics Embedding and Integration
Surfacing insights directly inside business applications by embedding analytics capabilities and integrating them into the broader data and application landscape.
Analytics Security and Access Control
Implementing robust security models, including Active Directory integration, role‑based access, and dynamic row‑level security.
Pathway to Advanced Analytics and Decision Intelligence
Laying an analytics foundation that supports advanced analytics, data science, and decision intelligence as organisational data maturity grows.
KEY PARTNERS
