Introduction

The Information domain in Orthogramic is the foundation for managing the data and knowledge that drive business decisions and operations. This domain provides a detailed view of how Information flows through the organization, supporting Capabilities, Value Streams, and strategic objectives. By integrating Information with real-time analytics and governance rules, Orthogramic ensures data accuracy, relevance, and accessibility. Explore how the Information domain helps your organization leverage data as a strategic asset to achieve business goals efficiently and effectively.

What is Information in Orthogramic?

In Orthogramic, Information is a foundational domain of the business architecture that captures, organizes, and governs the data and knowledge critical to an organization’s operations and strategic decisions. Unlike BIZBOK, which treats Information primarily as a static domain focused on documentation and classification, Orthogramic integrates Information dynamically with other business architecture domains, making it an active component that supports real-time decision-making and strategic alignment. This interconnected approach ensures that Information is not just about what data an organization has, but how that data is used, shared, and leveraged across the business to drive performance and achieve objectives.

In Orthogramic, Information is closely linked to other domains such as Capabilities, Value Streams, Products, Stakeholders, and Policies. These relationships are managed through a detailed structure of attributes, elements, and sub-elements, allowing organizations to understand how Information supports and influences different aspects of their business. For example, Information might be connected to specific Capabilities that require data for execution or associated with Value Streams where Information flows between various activities. This interconnectedness provides a more comprehensive view of how Information contributes to the overall business architecture, ensuring that data is contextualized and relevant to organizational goals.

A key distinction between Orthogramic and BIZBOK is how Information is maintained and utilized. In BIZBOK, Information is often documented in a static format, relying on data catalogs, classification schemes, and manual updates to keep records current. This traditional method can lead to delays in accessing relevant data, particularly when the business environment changes rapidly. Orthogramic, in contrast, employs advanced automation and real-time data integration, allowing Information to be continuously updated and aligned with business needs. This means that as the business landscape evolves, Information in Orthogramic remains accurate and relevant, supporting agile decision-making and reducing the risk of relying on outdated or incomplete data.

Orthogramic’s use of AI and machine learning also sets it apart from the BIZBOK approach to Information management. The platform can analyze patterns in data usage, identify trends, and recommend adjustments to Information architecture based on predictive insights. This capability allows organizations to anticipate changes in Information requirements and proactively adjust how data is collected, managed, and shared. In contrast, BIZBOK often relies on periodic information audits and assessments, which may not capture emerging needs or trends quickly enough. Orthogramic’s predictive analytics enable a forward-looking approach to Information, ensuring that data management is not only reactive but anticipatory.

Another area where Orthogramic differs significantly from BIZBOK is in its emphasis on contextualizing Information. In BIZBOK, Information is often treated as an isolated resource that must be classified and stored, with less focus on how it interacts with other domains. Orthogramic, however, integrates Information directly into the workflow of the organization, ensuring that it is immediately accessible to those who need it. For example, Information in Orthogramic can be linked to Policies that govern data use or Capabilities that rely on specific data inputs, providing context that makes Information more actionable and relevant. This contextualization transforms Information from static data into a living asset that directly influences business operations and strategic choices.

Orthogramic’s Information domain also includes a focus on data governance and quality, embedding rules and guidelines within the Information architecture itself. This governance ensures that data is not only accessible but accurate, secure, and compliant with internal and external standards. In BIZBOK, data governance is often a separate consideration, requiring dedicated documentation and management processes outside the core Information domain. Orthogramic embeds governance into every aspect of Information management, ensuring that data quality and compliance are continuously monitored and enforced. This integrated approach simplifies data governance and reduces the administrative burden typically associated with maintaining high data standards.

The democratization of Information access is another key feature that differentiates Orthogramic from BIZBOK. In BIZBOK, access to Information may be restricted to specialized roles or departments, limiting the flow of data across the organization. Orthogramic, on the other hand, provides a user-friendly interface that enables a broader range of roles—from business architects to operational staff—to access, share, and utilize Information. This inclusivity ensures that Information is not locked away in silos but is available to support collaborative decision-making and cross-functional initiatives.

In summary, Information in Orthogramic is not a static asset to be catalogued and stored, as it often is in BIZBOK, but a dynamic, integrated resource that drives business performance and strategic alignment. By embedding Information within the broader business architecture and linking it to other domains, Orthogramic transforms data from a passive resource into an active driver of organizational success. This modern approach enables organizations to maintain data relevance, anticipate changes, and make informed decisions faster than traditional, documentation-heavy methods. Orthogramic’s holistic, real-time, and predictive methodology empowers organizations to leverage Information not just for operational efficiency but for achieving long-term strategic goals.

Information domain modernized

To modernize the concept of information beyond the Information domain in BIZBOK, using an API from a data catalog like Atlan offers transformative possibilities. Data catalogs provide a comprehensive, metadata-driven platform for managing data across various ecosystems, which allows you to rethink how information is managed and leveraged within an enterprise.

Here’s how you could extend the traditional BIZBOK information domain using a data catalog:

Metadata-Driven information architecture

• Traditional approach: BIZBOK’s Information domain often centers around mapping information concepts and entities relevant to the organization.

• Modernized approach: With a data catalog’s API, you could introduce dynamic, metadata-driven architecture. This goes beyond static information mapping to real-time metadata management that integrates with various systems, offering up-to-date information governance.

• Benefit: Enhances data discoverability, lineage tracking, and improves collaboration across data users (e.g., business analysts, data engineers).

Data Lineage and governance automation

• Traditional approach: BIZBOK promotes understanding how information supports business processes through static mappings.

• Modernized approach: A data catalog’s API could automate and visualize data lineage. This provides a comprehensive view of how data flows across the enterprise, who uses it, and for what purposes—offering richer insights into the lifecycle and integrity of data.

• Benefit: Data lineage can empower decision-makers to ensure regulatory compliance and data quality in real time.

AI-Enhanced information discovery

• Traditional approach: In BIZBOK, information discovery is often a manual process involving stakeholders identifying key information entities and relationships.

• Modernized approach: Leverage AI/ML models within a data catalog to automate the discovery of data relationships, anomalies, and patterns across datasets. This helps enrich the context around data assets, making them more actionable and valuable to business architecture activities.

• Benefit: AI-enhanced discovery helps with faster insights and makes business architecture more agile by providing actionable, context-aware information.

Collaborative data and information stewardship

• Traditional approach: BIZBOK views information management in siloed roles like Data Architects or Business Analysts.

• Modernized approach: Atlan allows for collaborative data stewardship by involving multiple stakeholders, using data democratically across the organization. Data cataloging, enriched through user-generated insights, ensures a collaborative platform where everyone contributes to and benefits from information transparency.

• Benefit: Breaking silos and encouraging a cross-functional approach ensures that business decisions are made with comprehensive information.

• Data may be owned, maintained or consumed by different organization units. See Inter-unit domain relationships for standardised role definitions and usage patterns.

Real-Time analytics and KPIs

• Traditional approach: BIZBOK’s Information domain often relies on static KPIs derived from past data.

• Modernized approach: Integrating Atlan with other real-time analytics platforms allows you to monitor live KPIs and dashboards. This provides immediate insights into the performance of various processes and supports more dynamic decision-making.

• Benefit: You can adapt strategies and operations in real-time, improving agility and performance outcomes.

Automated data governance policies

• Traditional approach: Governance policies within the BIZBOK Information domain are often manually implemented and updated.

• Modernized approach: Using a data catalog's API, you could automate data governance policies, applying them across different data sources and ensuring continuous compliance with regulatory frameworks.

• Benefit: This approach minimizes manual overhead while ensuring governance standards are met efficiently.

Data as a Service (DaaS)

• Traditional approach: BIZBOK’s Information domain looks at information as a support function for business processes.

• Modernized approach: By leveraging Atlan’s API, you could promote Data as a Service (DaaS), enabling business users to access curated datasets and insights on demand. This shifts the focus of information from being a static asset to an actionable service.

• Benefit: Information becomes more valuable and accessible across the organization, supporting a range of business architecture and strategy needs.

By integrating Atlan’s advanced capabilities into your enterprise architecture, you can transcend BIZBOK's static concept of the Information domain, creating a more dynamic, automated, and collaborative environment for managing and utilizing information across your business.

Information attributes

Information Element

Information JSON schema

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "Information Domain Schema",
  "description": "Schema for the Information domain in the Orthogramic Metamodel",
  "type": "object",
  "properties": {
    "title": {
      "type": "string",
      "description": "The name or title of the information management element"
    },
    "description": {
      "type": "string",
      "description": "A detailed explanation of what the information management element entails"
    },
    "purpose": {
      "type": "string",
      "description": "The intended purpose or function of the information management element within the Organization"
    },
    "owner": {
      "type": "string",
      "description": "The individual or team responsible for the information management element"
    },
    "orgUnitTitle": {
      "type": "string",
      "description": "The Organization unit(s) to which the information management element is linked"
    },
    "inputs": {
      "type": "string",
      "description": "The resources information or materials required for the information management element"
    },
    "outputs": {
      "type": "string",
      "description": "The deliverables or results produced by the information management element"
    },
    "processes": {
      "type": "string",
      "description": "The set of processes that define how the information management element operates"
    },
    "performanceIndicators": {
      "type": "string",
      "description": "Metrics used to measure the effectiveness and efficiency of the information management element"
    },
    "dependencies": {
      "type": "string",
      "description": "Other elements processes or systems that the information management element depends on"
    },
    "relatedInformationElements": {
      "type": "string",
      "description": "Information elements that are related or linked to this element"
    },
    "maturityLevel": {
      "type": "string",
      "description": "The current maturity level of the information management element"
    },
    "toolsAndTechnologies": {
      "type": "string",
      "description": "Tools and technologies used to support or enable the information management element"
    },
    "complianceAndStandards": {
      "type": "string",
      "description": "Regulatory requirements and standards the information management element must adhere to"
    },
    "cost": {
      "type": "string",
      "description": "The financial cost associated with implementing and maintaining the information management element"
    },
    "risks": {
      "type": "string",
      "description": "Potential risks associated with the information management element and its operations"
    },
    "improvementOpportunities": {
      "type": "string",
      "description": "Areas where the information management element can be enhanced or improved"
    },
    "strategicAlignment": {
      "type": "string",
      "description": "How the information management element aligns with the Organizations strategic goals and objectives"
    },
    "informationComponent": {
      "type": "array",
      "description": "Components or pieces of information",
      "items": {
        "type": "object",
        "properties": {
          "title": {
            "type": "string",
            "description": "The name or title of the information component"
          },
          "description": {
            "type": "string",
            "description": "A detailed explanation of the information component"
          },
          "purpose": {
            "type": "string",
            "description": "The intended use or function of the information component"
          },
          "owner": {
            "type": "string",
            "description": "The individual or team responsible for managing the information"
          },
          "orgUnitTitle": {
            "type": "string",
            "description": "The Organization unit(s) using the information component"
          },
          "dataSources": {
            "type": "string",
            "description": "The sources from which the information is collected"
          },
          "dataQuality": {
            "type": "string",
            "description": "The quality measures and standards for the information component"
          },
          "security": {
            "type": "string",
            "description": "The security measures applied to protect the information"
          }
        }
      }
    }
  }
}