Dexcent IDS

We are Industrial DataOps Practitioners!

Infrastructure Assessment

By conducting thorough infrastructure assessments, organizations can gain a comprehensive understanding of their asset health, vulnerabilities, and performance. This information allows for informed decision-making, proactive maintenance, and strategic planning to ensure the reliability, safety, and efficiency of infrastructure assets throughout their lifecycle.

Asset Inventory and Condition Assessment : Identifying and cataloging all infrastructure assets, such as buildings, roads, bridges, utilities, and other physical structures. Conducting condition assessments to understand their current state, potential vulnerabilities, and maintenance needs.

Health Monitoring and Asset Performance: Implementing systems and technologies to continuously monitor the performance and health of infrastructure assets. This includes using sensors, IoT devices, and other monitoring tools to collect real-time data on asset conditions, usage, stress, and potential failures.

Risk and Resilience Assessment : Evaluating risks associated with infrastructure assets, such as vulnerabilities to natural disasters, aging components, environmental factors, or potential safety hazards. Assessing resilience strategies to mitigate risks and ensure the continuity of operations.

Lifecycle Management and Planning: Developing strategies for the entire lifecycle of infrastructure assets, from acquisition or construction to operation, maintenance, and eventual decommissioning or replacement. Planning for upgrades, repairs, and replacement based on asset conditions and performance.

Compliance and Standard Adherence : Ensuring that infrastructure assets comply with relevant regulations, safety standards, and industry best practices. Conducting assessments to verify compliance and identify areas that require improvements to meet standards.

Data Analysis and Decision Making Support : Analyzing data collected from various assessments to make informed decisions about asset maintenance, repair, or replacement. Using data-driven insights to optimize asset performance and allocate resources effectively.

Cost Benefit Analysis : Assessing the cost-effectiveness of maintenance and improvement strategies. Conducting cost-benefit analyses to determine the most efficient ways to manage infrastructure assets while optimizing their performance and longevity.


Gap and Weakness Identification : Infrastructure assessment identifies gaps and weaknesses in the existing technology infrastructure. Understanding these shortcomings is crucial for planning necessary upgrades or changes to support digital initiatives effectively.

Enhanced Scalability and Flexibility : Scalability ensures that the organization’s infrastructure can accommodate increased workloads or expanded operations without significant disruptions. Flexibility allows for easier adaptation to changing business needs.

Improved Reliability and Performance : By evaluating infrastructure components organizations can enhance the reliability and performance of the systems. Identifying and addressing performance bottlenecks or reliability issues helps to ensuring consistent and efficient operations.

Optimized Costs : Infrastructure assessment allows organizations to optimize costs by identifying areas of redundant technology, underutilized resources, or inefficiencies. This helps in streamlining operations, consolidating systems, or adopting more cost-effective technologies, ultimately leading to improved cost efficiency.

Enhanced Security and Compliance : Identification of security vulnerabilities and compliance risks strengthens security measures and ensures compliance with industry regulations and data protection standards, crucial for safeguarding information and maintaining customer trust.

Technology Enablement : Understanding the existing infrastructure lays the groundwork for seamless integration of new technologies, allowing for better compatibility and integration between different systems. It ensures that new digital solutions or innovations can be smoothly integrated into the existing technology landscape.

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Table of Content

1. Purpose
1.1. Purpose and Goals
1.2. Why The Industrial DataOps Process Is Needed?
1.3. Industrial DataOps Practitioner Engagement
1.3.1. Oversee An Existing Industrial DataOps Program
1.3.2. High Data Secrecy Organizations
1.3.3. Full Engagement
1.4. Principles
1.4.1. Know Your Data
1.4.2. Curate Your Data
1.4.3. Unify Your Data
1.4.4. Analyze Your Data
1.4.5. Hardware, Software, and People Working Together
1.5. Lifecycle
2. Intention
2.1. Scope
2.2. Assumptions
3. Terminology & References
3.1. Definitions
3.2. Acronyms and Abbreviations
3.3. Industry References, Standards, Regulations and Guidelines
3.4. Site Related References, Standards, Regulations and Guidelines
4. Expectations and Responsibilities
4.1. Roles
4.2. Role Job Description
4.3. Role Assignment
5. Opportunity Identification
5.1. Need Initiated
5.2. Improvement Initiated
7. Baselining
7.1. Data Rationalization
7.2. Data Justification
7.3. Data Impact
7.4. Data Flow
7.4.1. Data Producer
7.4.2. Data Path
7.4.3. Data Consumer
7.5. Data Good State
7.5.1. Failure Conditions
7.5.2. Warning Conditions
7.5.3. Abnormal Conditions
7.6. Data Processing Team
8. Target Confidence Factors
9. Critical Success Factors
10. Risk Analysis / Mitigation Plan
10.1. Risk Analysis
10.2. Mitigation Plan
11. Technology Selection
11.1. Hardware
11.2. Software
11.3. People
12. Project Execution
12.1. Project Synergy
12.2. Project Synergy
12.3. Resource Acquisition
12.4. Scheduling
12.5. Implementation
12.6. Training
12.7. Maintenance
12.8. Contingency
13. Evaluation Vs Baseline
14. Calibration & Sustainment
14.1. Training
14.2. Maintenance
14.3. Obsolescence
15. Continuous Improvement Process
15.1. Continuous Process Documentation
15.2. Audit
16. Management Of Change (MOC)
16.1. Applicability
16.2. Methodology