Data Governance Programme for MIND ID

Executive Summary

PT Mining Industry Indonesia (MIND ID), the state-owned mining holding company, manages data across many entities — from exploration to product marketing. Today that data is scattered across systems with limited integration, inconsistent definitions, unclear ownership, and reactive management. These gaps reduce the reliability of insight, weaken decision-making, and limit the organization's ability to meet regulatory and operational standards.

The Data Lake initiative in MIND ID's IT Master Plan must deliver tangible business value. Its success depends on a structured Data Governance framework — supported by a Metadata Development program and a Data Management Roadmap — to prevent the Data Lake from degrading into a “data swamp” and to enable accurate, data-driven decision-making.

Zentara proposes an enterprise Data Governance programme aligned with DAMA-DMBOK best practices. The approach runs a regulatory and best-practice review, holistic data discovery, a maturity and gap assessment, and structured stakeholder engagement to define the target state — then designs a complete operating model covering governance structure, stewardship roles, RACI, policies, standards, and procedures.

Delivered as a 20-week, five-phase programme, the engagement establishes a Data Governance Council, develops enterprise policies, runs capacity-building, and launches early pilot quick wins — such as a business glossary and a metadata registry. On completion, MIND ID gains a robust, scalable framework that strengthens data quality, improves compliance, and unlocks greater business value from enterprise data.

Client Context & The Challenge

Organizational Context

As the state-owned mining holding company, MIND ID oversees a group of entities whose operations span the full value chain — from exploration and processing to commercial activities and product marketing. At that scale, data integrity is not an IT concern alone; it is a strategic asset central to the group's digital transformation and to confident, coordinated decision-making across subsidiaries.

Current Condition

Zentara's reading of the current state identifies five recurring conditions that limit the value MIND ID draws from its data:

• Fragmentation. Data is scattered across multiple systems with limited integration.
• No shared standards. There are no consistent data standards, metadata, or shared definitions.
• Reactive management. Data management practices are reactive and lack a structured roadmap.
• Unclear ownership. Data ownership and accountability are unclear within business functions.
• Limited strategic use. Data use for strategic decision-making remains limited.

Project Objectives & Scope of Solution

The programme is organized around four expectations, the ownership needed to execute them, and the three solution components that deliver them.

Project Expectations

• Enhance operational efficiency. Integrated, high-quality data streamlines business processes across entities — exploration, processing, and commercial activities.
• Ensure regulatory compliance. Manage data to relevant standards, mitigating the regulatory risks pertinent to a state-owned mining enterprise.
• Enable data-driven decisions. Provide a credible single source of truth via the Data Lake, empowering management to decide faster and more accurately.
• Optimize data asset value. Transform raw data into a strategic asset that generates new insight and drives innovation across the corporation.

Execution Ownership

• Governance Council. An executive-level Data Governance Council provides mandates, approves policies, and ensures subsidiary entities comply with the established framework.
• Owner & Steward roles. Data Owners (business leadership) and Data Stewards (operational) are explicitly defined to enforce policy, monitor quality, and manage day-to-day metadata.
• Technology team. IT leads the technical development of the Data Lake and the deployment of the centralized Data Catalog and metadata solutions.
• Cross-functional integration. Project leads ensure close collaboration between Business, IT, and Compliance to create a practical, adopted governance framework.

2.3 The Solution

Zentara's Approach — A Six-Step Methodology

Zentara structures the engagement as one continuous capability build, not a one-off project. Six steps move MIND ID from discovering the current landscape, through defining and designing the governance model, to executing and sustaining it.

How the methodology helps

The six steps group into three arcs, each producing a concrete result:

• Discovery & Alignment (Steps 1–2). Uncovers the current data landscape and ensures regulatory compliance.
• Definition & Design (Steps 3–4). Defines ownership, roles, and a clear governance structure.
• Execution & Roadmap (Steps 5–6). Provides an actionable plan for governance maturity improvement.

What is Data Governance

Data Governance is the framework of policies, processes, roles, and responsibilities that ensures data is accurate, consistent, secure, and used responsibly to support business objectives. It defines how data is managed, who is accountable, and what standards apply across its entire lifecycle — from creation through usage, sharing, and retention. Its purpose is to make data trusted, well-managed, and aligned with organizational goals, enabling better decision-making, efficiency, and risk management.

Key Principles

• Accountability. Clear ownership and stewardship of data assets.
• Quality. Data that is accurate, complete, and reliable.
• Security. Protection from unauthorized access and misuse.
• Compliance. Meeting legal, regulatory, and ethical standards.
• Consistency. Standardized definitions, policies, and metadata across systems.

Reference Frameworks

Several established frameworks guide enterprise data governance. Zentara anchors the MIND ID programme on DAMA-DMBOK, drawing on the others where they add value.

The DAMA-DMBOK Framework

DAMA-DMBOK (Data Management Body of Knowledge) is a global standard framework by DAMA International that provides comprehensive guidance for managing data as a strategic asset. It defines the principles, functions, and best practices of data management, and positions Data Governance as the core discipline that ensures consistency, quality, and accountability across all data-related activities.

Objectives for MIND ID

• Best-practice reference for enterprise data management.
• Established governance, policies, and accountability for data management.
• Improved data quality, security, and business value of information assets.

The 11 Functional Areas — Structure & Key Activities

Data Governance sits at the center of eleven functional areas. Each area carries a focus, key activities, and expected outcomes that shape the MIND ID roadmap.

Solution Methodology, Scope & Timeline

The programme runs across five phases over twenty weeks. Each phase carries defined activities and concrete deliverables, sequenced so that governance design is validated before implementation and sustained after handover.

Consolidated Deliverables

Across the programme, MIND ID receives a complete, auditable governance package — from assessment through sustainment:

• Maturity & gap assessment reports establishing the baseline and target state.
• Enterprise data policies and standards covering quality, security, access, and metadata.
• Governance structures — Data Governance Council charter, Owner/Steward roles, and a RACI matrix.
• Workflow templates for stewardship, change management, and data-quality monitoring.
• Pilot quick wins — a business glossary and a metadata registry that demonstrate early value.
• Training and awareness materials to embed data-driven practices across the workforce.
• A sustainability roadmap to carry the governance model forward after handover.
  

Target Outcomes & Value

The programme moves MIND ID from today's fragmented, reactive state to a governed, accountable, and trusted data environment.

On completion, MIND ID gains a robust, scalable Data Governance capability that strengthens data quality, enhances operational efficiency, improves regulatory compliance, and unlocks greater business value from enterprise data — positioning the group to operate with higher confidence in its data and supporting its broader digital transformation.

Zentara Technologies is a cybersecurity and enterprise technology company headquartered in Jakarta, with a regional office in Singapore. Zentara is not a reseller or vendor, but a strategic technology architect for high-stakes institutions and mission-critical enterprises — designing and building solutions that are precise, integrated, and built to endure.

Zentara's operations are certified to ISO 27001 (Information Security Management System) and ISO 42001 (Artificial Intelligence Management System). Its capabilities span cybersecurity, cyber intelligence, cyber defense, and enterprise solutions — including data governance, GRC, and system integration — aligned with local regulators (OJK, BSSN) and international frameworks (NIST, DAMA-DMBOK, PCI DSS).