Anjana Data Platform Features

Different functionalities for multiple roles and diverse purposes to achieve a 360º view of Data & AI management and governance with a technology-agnostic approach.

Intuitive UX & UI adapted to each profile

It offers a simple, intuitive user experience oriented to non-technical profiles. The interface adapts to each role within the governance model, displaying only the information and actions relevant to each user. This accelerates adoption, reduces the learning curve and facilitates collaboration between business, data and technology.

Advanced Configuration Portal

Centralises the configuration of the governance model, metamodel and operation of the platform in a single, advanced portal. Defines domains, roles, permissions, flows, templates and rules without the need for development, by means of no-code and low-code parameterisation, allowing the platform to be adapted in an agile way to organisational evolution.

Multi-language interface and content

Adapt the platform to global environments and multinational organisations thanks to its advanced multi-language capabilities. The user interface and governed content - metadata, descriptions, business terms and documentation - can be managed in multiple languages, enabling a consistent, inclusive experience aligned with the operational reality of each team.

Operationalisation of the governance model

It implements and operationalises any Data & AI governance model - centralised, federated or hybrid - through the flexible definition of domains, roles and permissions. The platform abstracts people from responsibilities, allowing the organisational model to evolve over time without friction and ensuring that governance is applied consistently across all modules.

Policies, procedures, workflows and notifications

Design and execute governance policies and procedures through dynamic role-based workflows. Integrated BPM automates approvals, status and validations throughout the asset lifecycle, incorporating alerts and notifications to facilitate collaboration and ensure a governance-first and governance-by-design approach.

Data Catalogue & metadata-centric IA

It inventories and manages any Data & AI asset in a technology-agnostic way from a metadata-centric approach. The Catalogue centralises technical, business, operational, quality and regulatory metadata in a single Metadata Lake, offering a complete, contextualised view that is always aligned with the actual use of the data.

Business glossary and semantic layer

Builds a common and shared language for the entire organisation through a Business Glossary fully integrated with the technical catalogue. Defines business terms, concepts and metrics linked to information assets, facilitating understanding, reuse and alignment between business and technology in a collaborative environment.

Hybrid, global, extended and multilayered lineage

It visualises the complete traceability of information assets from origin to consumption, and from the technical to the business layer. The multi-layered lineage allows to adapt the experience to different profiles and build a Knowledge Graph that enhances impact analysis, trust and leveraging the Data & AI ecosystem.

Information portal and global search engine

Easily access corporate knowledge on Data & AI through a unified portal with semantic search in natural language. Apply dynamic filters on any Metadata Lake metadata, save customised searches and quickly find the most relevant assets based on context and your needs.

Information and Knowledge Marketplace

Publish, discover and consume Data, AI and Knowledge Products in a governed environment. The Marketplace enables the management of Data Sharing Agreements and Data Contracts, enabling regulated self-service similar to e-commerce, with automated end-to-end processes to democratise access without losing control.

Active metadata management

Enables Data & AI governance by continuously capturing, generating and enriching metadata from multiple sources. The platform orchestrates automated actions on governed assets, integrating governance, DataOps and demand management to place control from design and across the entire value chain.

Impact control in the face of change

Proactively analyses the impact of any change before implementing it. Thanks to lineage, versioning and lifecycle management, the platform allows you to identify dependencies, prevent risks and coordinate actions with affected stakeholders, reducing errors and ensuring controlled and traceable changes.

Workspace for mass actions

Optimises operational management through a workspace designed to execute massive actions on multiple information assets. It allows you to apply changes, validate statuses, assign responsible parties or launch processes in an efficient and controlled manner, reducing manual tasks and ensuring consistency with the defined governance model.

Change history and audit trail

Logs and audits all actions taken on information assets, regardless of channel or user. Maintain a complete history of changes, versions and events, also integrating audit information from external systems to ensure traceability, compliance and evidence for internal and external audits.

Data quality management & AI

Defines, manages and monitors quality rules and metrics associated with information assets. The platform centralises the results of external quality engines, allowing you to analyse trends, manage alerts and coordinate corrective actions from a single point, aligning quality, governance and decision-making.

Data Observability & AI

Gain continuous visibility into the status, usage and behaviour of governed Data & AI assets. The platform allows you to observe metrics, events, quality, access and processes throughout the lifecycle, facilitating early detection of risks, deviations and opportunities for improvement from a governance perspective.

Sample of information assets

It allows users to securely preview the content of information assets in a controlled manner. The platform obtains limited and obfuscated samples directly from source systems, respecting governance policies, to facilitate evaluation and understanding before requesting full access.

Monitoring and tracking governance

Measures and monitors the degree of Data Governance & AI implementation through customised dashboards, reports and alerts. Thanks to its open architecture, the platform integrates with any BI or analytics tool, providing continuous visibility into the usage, quality and compliance of the governance model.

Full interoperability through APIs

Anjana Data Platform integrates bi-directionally with any system or tool in the ecosystem through fully documented REST APIs. The platform allows automating processes, exchanging metadata and orchestrating external actions without black boxes or vendor lock-in, guaranteeing an open, extensible and interoperable architecture.

Integration with third-party technologies

1. Open architecture and API-first; bidirectional integration with OOTB plugins for SSO/IAM and local management.

2. Discovery and ingestion of metadata from dictionaries and catalogues (including cloud-native ones).

3. Comprehensive Quality, Safety and Audit Management: definition of rules and import of control results and logs.

4. Injection of tags/metadata into external technologies to activate security, privacy, and quality policies.

5. Secure, obfuscated on-demand sampling to preview format and content.

6. Permission management on underlying technologies to enable a truly automated marketplace.

7. Orchestration of actions in third-party tools for preventive and proactive governance.

How Anjana Data fits in in your architecture

A unified, comprehensive and cross-cutting layer of governance that does not replace your current Data & AI technology ecosystem.

Integrate, complement, and enrich your platforms' native technical catalogues thanks to native bidirectional integrations.

Operationalise your DataOps, Data Mesh, and Data Fabric initiatives with a common layer of governance and marketplace.

Learn about Anjana Data's architecture and integrations

Use cases enabled

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Knowledge management

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Foster a data culture aimed at eliminating silos and managing information knowledge in a cross-cutting and transparent manner to promote the reuse of data assets.

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Creating a single repository for accessing knowledge about the organisation's data assets through a Data Portal with a Business Glossary and a Data Catalogue containing all the necessary information for any interested party, in understandable language tailored to their profile.

 

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Decision-making

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Improve agility and effectiveness in data- and AI-driven decision-making by enhancing data quality and reducing the inherent risks associated with data usage.

 

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Implementing and integrating an adaptive operational framework for Data Governance and AI that enables the organisation to bring data closer to business roles by facilitating the application of custody policies and procedures for data quality, security, privacy, and ethics.

 

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Governed self-service

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Promote the democratisation and self-service of data assets across business areas for different use cases, facilitating information sharing in a federated ecosystem.

 

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Building an information marketplace that enables different stakeholders to understand the context of the data and share information effectively and efficiently without the need for technical expertise, in an environment regulated by Data Sharing Agreements and Data Contracts.

 

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Data monetisation

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Create data/information/AI products that can be monetised and generate new revenue streams by creating new business-oriented products and/or services.

 

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Adopting a domain-based Data Mesh architecture with advanced capabilities to group, manage, and publish different data/information/AI assets in various formats and supported by different technologies, making them available for multiple and diverse use cases.

 

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Cost reduction

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Leverage cutting-edge hybrid data and AI platforms and architectures to reduce risks, operational costs, and IT costs associated with data and AI management.

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Implementing an adaptive design governance operating model integrated into existing demand management processes to avoid bureaucracy and bridge the gap between business and IT, by operationalising Data&AIOps models with technical process automation within the layers of governance, integration, data storage and consumption, and AI. This model, driven by active metadata, is the basis for Data Fabric and Data Spaces architectures.

 

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Regulatory compliance

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Comply with existing regulations related to data and AI in a straightforward manner, facilitating custody processes and the submission of evidence to Central Government Bodies.

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Creating a taxonomy-driven metadata lake as a single source of truth to meet regulatory and/or compliance requirements by standardising metadata management, centralising observability, integrating audits, ensuring traceability, and controlling risks.

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Productivity and efficiency

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Increase the productivity of data stakeholders by reducing the time spent on manual tasks related to data and AI management and governance.

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Creating a federated collaborative environment that facilitates interaction between users while empowering them, and incorporating advanced process automation and recommendation functionalities.

Ready to take Data Governance & AI to the next level?

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