Unleash the power of automation in data modelling governance.

In today’s data-driven landscape, organizations face the dual challenge of managing vast amounts of data while ensuring its quality, security, and compliance. A robust solution that combines data modeling, enterprise architecture, and design capabilities empowers organizations to navigate this complex terrain effectively, and also in data-centric organizations,?seamless access to critical data sources?is essential for driving innovation and business growth. Two primary access methods are commonly used:?direct access?and?integration with tools like ServiceNow.

?

?????? All the data sources' XML/JSON/DDL scripts are initially pushed into version control systems such as GitLab, Bitbucket, etc…These scripts contain valuable data that needs to be governed and managed effectively to ensure consistency, quality, and security. XML/JSON/DDL scripts, the lifeblood of data operations, reside in version control systems like GitLab, Bitbucket, etc…

??

? PDD and LDD to Business Terms, data sources undergo scrutiny to identify critical data elements (CDE) and personally identifiable information. This ensures that sensitive data is appropriately handled and protected throughout the governance process. so now the Lorang Meta Data Integration framework (MIF) acts as the bridge between the SCM/VCS pipelines and Collibra. This involves fetching DDL (Data Definition Language) scripts from pipelines, auto-creating physical dictionaries, and automapping them to LDD and Business Terms. This seamless integration with the help of MIF further enhances data governance capabilities, ensuring comprehensive coverage of data assets. Lorang MIF parses and transforms metadata from XML/JSON/DDL scripts into a format compatible with Governance/Catalog tools. Here SCM/VCS pipelines play a crucial role in the data governance process, facilitating the seamless transfer of data scripts from development to production environments. Automated processes within pipelines ensure that changes to data scripts are tracked, versioned, and audited, maintaining data integrity and compliance. Jenkins and other pipelines are used as source to parse XML/JSON/DDL scripts, ensuring that only validated and approved scripts are integrated into the governance framework.

?? Governance tools like Collibra serves as the central hub for data governance by referring a unified view of data assets. PDD to LDD Mapping can use UDP (User-Defined Properties) values so that PDD entities are automatically mapped to their corresponding LDD counterparts. This ensures consistency between physical and logical representations though the LDD and PDD sourced from different products. Now a day most of the governance tools intelligent algorithms map PDD and LDD elements to relevant business terms based on the recommendation scores generated by inbuilt AI capabilities or as an alternative, Lorang MIF can replace these gaps and achieve the same goal. Business stakeholders gain a holistic understanding of data, bridging technical and business perspectives.????

?Here there are two seamless access to critical data sources?is essential for driving innovation and business growth. Two primary access methods are commonly used:?direct access?and?integration with tools like ServiceNow. Direct Access granting plays a crucial role in enabling data consumer to get access swiftly without any bureaucracy or overhead of any other additional access granting processes/tools.

Unlock Effortless Governance: Your Data Modeling Made Easy - Key Steps Brief Updates

1a). Data modeling tools are instrumental in storing data within various data sources. These tools enable organizations to design, structure, and organize data as per their requirements. They facilitate the creation of logical data representations, establishment of data relationships, and enforcement of data integrity constraints. Moreover, data modeling tools aid in translating conceptual data models into physical data structures suitable for implementation in databases or other storage systems. In essence, these tools serve as a centralized solution for managing the entire data lifecycle efficiently.

1b). SCM/VCM tools:

• All the data sources' XML/Json/DDL scripts are initially pushed into version control systems such as GitLab or Bitbucket.
• These scripts contain valuable data that needs to be governed and managed effectively to ensure consistency, quality, and security. XML/Json/DDL scripts, the lifeblood of data operations, reside in version control systems like GitLab or Bitbucket.
• PDD and LDD to Business Terms, data sources undergo scrutiny to identify critical data elements (CDE) and personally identifiable information. This ensures that sensitive data is appropriately handled and protected throughout the governance process.

2). CI’s (Pipelines) Integration: Pipelines play a crucial role in the data governance process, facilitating the seamless transfer of data scripts from development to production environments. Automated processes within pipelines ensure that changes to data scripts are tracked, versioned, and audited, maintaining data integrity and compliance. Jenkins and other pipelines are used as source to parse XML/JSON/DDL scripts, ensuring that only validated and approved scripts are integrated into the governance framework.

3).? Lorang Metadata Integration Framework (MIF): MIF acts as the bridge between Pipelines and Collibra. This involves fetching DDL (Data Definition Language) scripts from Pipelines, auto-creating physical dictionaries, and auto Mapping them to LDD and Business Terms. This seamless integration further enhances data governance capabilities, ensuring comprehensive coverage of data assets. It parses and transforms metadata from XML/Json/DDL scripts into a format compatible with Collibra.

4).? The Data Governance Hub: Governance tools like a Collibra serves as the central hub for data governance, providing a unified view of data assets. Direct Access granting plays a crucial role in enabling data consumer to get access swiftly without any bureaucracy or overhead of any other additional access granting processes/tools.

Key components include:

• Physical Data Dictionary (PDD): Describes the actual data structures in databases.
• Logical Data Dictionary (LDD): Represents data models without database-specific details.
• Business Terms: Define common business concepts and terminology.

Using the Lorang Meta Data Integration framework (MIF):

• PDD to LDD Mapping: Using UDP (User-Defined Properties) values, PDD entities are automatically mapped to their corresponding LDD counterparts. This ensures consistency between physical and logical representations.
• PDD and LDD to Business Terms Mapping:Collibra’s intelligent algorithms map PDD and LDD elements to relevant business terms based on score.Business stakeholders gain a holistic understanding of data, bridging technical and business perspectives.

5). seamless ?access to critical data sources?is essential for driving innovation and business growth. Two primary access methods are commonly used:?direct access?and?integration with ServiceNow.

?5a).? Direct Access:

Collibra, a leading data governance platform, plays a crucial role in enabling direct access to critical data sources.

With Collibra, organizations can:

• Catalog?and organize their data assets effectively.
• Define and enforce?data policies?and?rules.
• Ensure?data quality?and?compliance.
• Provide a?single system of engagement?for data management.

? 5b).? Integration with ServiceNow:

ServiceNow is a powerful platform for managing incidents, service requests, and other IT-related processes.

Here’s how it works:

• Incident Tracking: Any user can record and track an occurrence (incident) until service is restored and the problem is fixed.
• Assignment and Documentation: Incidents are allocated to relevant service desk staff, who complete the assignment and document the investigation.
• Resolution and Closure: When the incident is resolved, it can be manually closed. Alternatively, incidents can be closed automatically based on predefined criteria (e.g., last update time or resolution status).

6) Pipelines, The seamless transfer of data scripts from development to production environments. Automated processes within pipelines ensure that changes to data scripts are tracked, versioned, and audited, maintaining data integrity and compliance.

7)When managing access permissions for data modeling tools, organizations prioritize secure and streamlined processes. One crucial aspect of access granting involves establishing a seamless connection between data sources and the user interface (UI) of the data modeling tools. This entails granting users the necessary permissions to access and manipulate data stored in various data sources directly through the UI of the data modeling tools.

Benefits of this use case: -

• Enhanced Security and Validation: The Metadata Harvester ensures data security and validates mappings. REST APIs connect Collibra seamlessly with Data Governance Tools and Data Catalogs.
• The Impact: Informed Decision-Making By streamlining data modeling and governance, organizations reap several benefits:
• Efficiency: Automation reduces manual effort, allowing teams to focus on higher-value tasks.
• Accuracy: Auto-mapping ensures consistency and eliminates human errors.
• Visibility: Stakeholders gain a comprehensive view of data lineage, business terms, and relationships.
• Compliance: Governance practices align with industry standards and regulations.

???????????????????? The conclusion with this Lorang accelerator, organizations can Catalog?and organize their data assets effectively, Define and enforce?data policies?and?rules, ensure?data quality?and?compliance, achieve a?single system of engagement?for data management. And also bringing the pipeline integrations under governance prior to directly deploying in the destination environments will help organizations to effectively manage data, bridge technical and business domains, and make informed decisions based on high-quality, well-governed data.