Data governance project for a bank
Project overview
Our customer sought to establish effective and comprehensive policies for handling BDW/BI/MIS data across the executive team and all other bank departments.
Within the project’s scope, we analyzed existing reports, created structured JSON-based report descriptions, a business glossary, and logical report data models. We also developed a high-level bank ontological model and a structured hierarchy of the bank metadata pool, which included data sources, business entities, and SQL queries to gather necessary data.
Our goal was also to develop a more differentiated approach to accessing reports based on Role-Based Access Control (RBAC), create and implement data filtering and masking mechanisms for report visualization based on user roles, and develop the cloud Data Governance Framework, implementing all the above-mentioned features based on Django (Python).
Business challenge
The bank lacked a unified approach to governing its BDW/BI/MIS data, which made it difficult for bank employees to access accurate, consistent, and secure reports. Our customer needed to enhance data governance, standardize reporting processes, and ensure that sensitive information was properly filtered, masked, and role-restricted, while also creating a scalable framework to support future growth and compliance requirements.
Technical challenges
The main technical challenge was the integration of the solution offered by DICEUS with diverse multi-platform cloud and in-house infrastructure.
Solution delivered
We implemented a cloud-based Data Governance Framework that standardized the bank’s reporting processes. Our solution includes structured JSON report descriptions, a unified business glossary, logical data and ontological models, and a centralized metadata hierarchy connecting data sources, entities, and SQL queries. Role-Based Access Control with data filtering and masking ensured differentiated access and protection of sensitive information. As a result, BI developers can now build reports through a graphical interface without needing to understand the physical data structure. The new framework turned data into a strategic asset and strengthen decision-making across the bank.
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Key features
Structured JSON-based report descriptions
Business Glossary
Logical report’s data models
High-level bank ontological model
Structured hierarchy of the bank metadata pool, including data sources, business entities, and SQL queries that gather necessary data
Approach to accessing reports based on Role-Based Access Control (RBAC)
Data filtering and masking mechanisms for report visualization based on user roles
Cloud Data Governance Framework
Value to our client
Our tech stack
SQL
JavaScriptClient feedback
We have great progress now. Let’s do a demo/walkthrough of COMPLETED flows in managing data points in the platform.
