The original mode of operation at the city government was characterized by data duplication in different departments and their systems, ineffective data sharing between systems, a lack of formal data governance, and duplication of business logic.
The city government aimed to overcome these limitations by implementing an effective Master Data Management solution.
Data duplication: Duplicated data was a common issue across all main data entities and departments. Some attributes were shared, while others were specific to the department or system.
Ineffective data sharing: Difficulty and a lack of formal processes to share information across departments in a seamless manner. Shared data was not synchronized with the original source of the data, and additional checks and updates were required.
Lack of formal data governance: Given informal data sharing procedures and the fact that common entities are authored and managed in multiple processes, the lack of formal data governance presented a problem when trying to share data among departments.
Application/function/business logic duplication: A common resource for accessing data did not exist, and the replication of function and business logic to support local instances of the data was necessary. Data was replicated even at a local level.
Complicated service structure: Hundreds of municipal services within a dozen departments—some of them similar from the operational perspective. A substantial number of these services relate directly to data management and IT deployment.
Complex organization: Services share similar data models with common entities and similar attributes, but some values are local to the specific service. This caused an inclination to replicate common data entities and their attributes.
Corporate applications: Large software solutions deployed without support for data sharing between various systems.
Distributed IT governance: Each department assumed responsibility for managing the acquired data, as well as deploying and supporting its own services.
The solution created a data-sharing hub for the city systems (across all different governmental departments) by implementing transactional Master Data Management (MDM) for all identified entities. The solution enabled an efficient and effective common view of all shared information and entities, ensuring consistency and completeness of this information while avoiding redundancy.
Ataccama Master Data Center (MDC) – a high-performance platform that makes consistent, accurate, and up-to-date data instantly available across a broad range of enterprise applications and systems.
Ataccama DQ Issue Tracker (DQIT) – a user-friendly web app offering manual correction of data quality issues that cannot be resolved automatically.
Central data model: Defining a common central data model for core, shared entities in the city systems.
Automatic cleansing and consolidation: Enabling automatic processing of all information in the MDM, and ensuring a common view of this data for all systems. All entities go through cleansing and enriching processes to improve the quality of the data, and a matching and merging process to create golden records for the mastered entities. This maximizes the quality of data used in all processes for all departments and systems.
Easy management of an MDM repository: Enabling an MDM repository for storing master data (including the original source data, i.e., instance data) to be effectively managed and shared across all city systems.
Compatibility with legacy systems: Enabling batch interface development to interact with legacy systems.
Application integrations: Leveraging centralized logic, modular components, and shared services—e.g., validations, DQ firewalls, value providers. Reducing application size and complexity by simplifying integrations.
Service-oriented architecture: Providing a set of native core services to interact with the data in MDM, thus complying with the SOA requirement.
Manual issue resolution: Using Ataccama MDC and DQIT to enable the correction and control of data quality at an instance level, with the ability to propagate results to the source level. The solution offers administration, reporting, advanced management, and workflow for issues based on predefined rules.
Data monitoring: Providing a shared presentation tool and a dashboard for data quality monitoring.
Security: Centralizing security and privileges when accessing data in MDM.
Scalability: Scalability of the proposed SOA using adequate load balancing, and reliance on web services for common operations.
Easy access to information: Alignment with the Open Data concept by enabling easier access to information.