Dexcent IDS

We are Industrial DataOps Practitioners!
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Navigating the Digital Transformation Landscape in Asset Management: A Leadership Guide

In the fast-evolving landscape of industrial operations, the integration of digital technologies has become paramount for achieving optimal efficiency and cost savings. When it comes to asset management, organizations are increasingly recognizing the need for a digital transformation journey to stay ahead in the competitive business arena. The question arises: How do you gauge your […]

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Has your Industrial Asset Maintenance Program Flatlined?

Has your organization taken all the possible steps to ensure your success? Industrial organizations spend considerable time and effort planning and strategizing to maximize production, minimize downtime, and prevent equipment failure. These are critical aspects to ensure success in the industry. Some of the steps typically taken in the drive to operational excellence include: •

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Challenges Faced by Innovation Managers in the Oil and Gas Industry

We all live in a data-driven world, organizations in various industries are recognizing the value of data and the need to effectively manage and leverage it for operational excellence. Within the complex and dynamic landscape of the Oil and Gas industry, innovation managers face unique challenges in harnessing the power of data for driving innovation

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Navigating Alberta’s Lithium Frontier: Integrating DataOps for Sustainable Mining

In the midst of the global drive towards sustainable and eco-friendly energy solutions, the demand for electric vehicles (EVs) is skyrocketing, intensifying the need for lithium and other essential metals used in EV battery production. While Australia, Chile, and China currently dominate the lithium market, Alberta, Canada, is poised to emerge as a significant player,

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The Six Impact Pillars of DataOps: Driving Efficiency and Collaboration in Data Management

We’re currently reading The DataOps Revolution by Simon Trewin. DataOps, an emerging approach to data operations, has gained significant attention as a solution that promotes collaboration, agility, and automation throughout the data lifecycle. At its core, DataOps aims to streamline and optimize data integration, data quality, and data delivery. To achieve these objectives, DataOps relies

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Challenges Faced by Innovation Managers in the Oil and Gas Industry

We all live in a data-driven world, organizations in various industries are recognizing the value of data and the need to effectively manage and leverage it for operational excellence. Within the complex and dynamic landscape of the Oil and Gas industry, innovation managers face unique challenges in harnessing the power of data for driving innovation

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Unlocking Operational Excellence Through APM Programs

A Holistic Approach to Streamlining Operations In today’s dynamic business environment, operational excellence isn’t just a buzzword – it’s a strategic imperative. Organizations must continuously improve processes, enhance efficiency, and minimize risks to thrive. Asset Performance Management (APM) Programs present a holistic solution that addresses these challenges head-on. Operational readiness, risk assessment, and lifecycle asset

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Introduction to DataOps Part 3: Getting Started with DataOps: Key Principles and Best Practices

Welcome to the final part of our three-part blog series on DataOps. In the previous posts, we explored what DataOps is and why it matters, as well as the benefits of adopting DataOps practices in today's industrial landscape. In this post, we will delve into the key principles and best practices that can help you

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Intro to DataOps Part 2: The Benefits of Adopting DataOps Practices

Welcome back to the second part of our three-part blog series on DataOps. In the previous post, we explored the fundamentals of DataOps and its significance in the data-driven era. In this post, we will delve deeper into the benefits that organizations can reap by adopting DataOps practices. From improved agility to enhanced decision-making, DataOps

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DataOps 101
Part 1: What is DataOps and Why Does it Matter?

Welcome to the first part of our three-part blog series on DataOps 101. In today's rapidly evolving digital landscape, organizations are collecting and generating vast amounts of data. However, merely amassing data is not enough to gain insights and drive value. To harness the power of data effectively, businesses need efficient and streamlined processes. That's

DataOps 101
Part 1: What is DataOps and Why Does it Matter?
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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
6.Discovery
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