US

Data governance project for a bank

  • Faster-reporting

    Faster reporting

  • Standardized-processes

    Standardized processes

  • Stronger-data-governance

    Stronger data governance

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).

Client information

Under NDA

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 organization.

Solution-delivered-image-1-1
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Key features

Features-delivered-images

  • JSON-based report

    Report is defined and represented in a standardized JSON format, making it machine-readable, consistent, and easy to process programmatically.

  • Business Glossary

    We created a collection of clear, standardized definitions for key terms and concepts, ensuring that everyone in the bank uses the same language and meaning.

  • Report data models

    Our team developed abstract representations of how data is organized, related, and structured for reporting purposes, focusing on business meaning and relationships.

  • Report access by roles

    We introduced the approach to accessing reports based on Role-Based Access Control (RBAC).

Project-overview-image-

  • Bank metadata architecture

    Structured hierarchy of the bank metadata pool, including data sources, business entities, and SQL queries was introduced.

  • Cloud data governance framework

    We offered a set of policies, processes, roles, and technologies that ensure data in cloud environments is properly managed, secured, compliant, and used effectively.

  • Data visualization controls

    Data filtering and masking mechanisms for report visualization based on user roles was proposed.

  • Bank ontological model

    A framework that defines and organizes the core entities, relationships, and rules of the banking domain was created.

Value to our client

  • Faster reporting

    With our solution, BI developers can create reports through a graphical interface without needing technical knowledge of physical data structures.

  • Standardized processes

    The reporting process is enhanced through the use of an ontological model, logical data model, and metadata pool, ensuring consistency and scalability across business units.

  • Stronger data governance

    A modern data infrastructure with structured processes ensures secure, transparent, and well-managed use of data as a strategic asset of the bank.

Our tech stack

  • SQL SQL
  • Django Python (Django)
  • Java-EE JavaEE
  • JS JavaScript

Client feedback

We have great progress now.

Let's do a demo/walkthrough of COMPLETED flows in managing data points in the platform.

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    Case study
    Data governance project for a bank
    diceus.com
    Case study
    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).
    Client information

    Under NDA

    Information
    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 organization.

    Key features
    • JSON-based report

      Report is defined and represented in a standardized JSON format, making it machine-readable, consistent, and easy to process programmatically.

    • Business Glossary

      We created a collection of clear, standardized definitions for key terms and concepts, ensuring that everyone in the bank uses the same language and meaning.

    • Report data models

      Our team developed abstract representations of how data is organized, related, and structured for reporting purposes, focusing on business meaning and relationships.

    • Report access by roles

      We introduced the approach to accessing reports based on Role-Based Access Control (RBAC).

    • Bank metadata architecture

      Structured hierarchy of the bank metadata pool, including data sources, business entities, and SQL queries was introduced.

    • Cloud data governance framework

      We offered a set of policies, processes, roles, and technologies that ensure data in cloud environments is properly managed, secured, compliant, and used effectively.

    • Data visualization controls

      Data filtering and masking mechanisms for report visualization based on user roles was proposed.

    • Bank ontological model

      A framework that defines and organizes the core entities, relationships, and rules of the banking domain was created.

    Value to our client
    • Faster reporting

      With our solution, BI developers can create reports through a graphical interface without needing technical knowledge of physical data structures.

    • Standardized processes

      The reporting process is enhanced through the use of an ontological model, logical data model, and metadata pool, ensuring consistency and scalability across business units.

    • Stronger data governance

      A modern data infrastructure with structured processes ensures secure, transparent, and well-managed use of data as a strategic asset of the bank.

    Tech stack used in project
    • SQL
    • Python (Django)
    • JavaEE
    • JavaScript

    We have great progress now.

    Let's do a demo/walkthrough of COMPLETED flows in managing data points in the platform.

    diceus.com