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Breaking Down Silos: The Key to Unlocking Unified Operational Data

Introduction

AI and advanced analytics are transforming the industrial sector, enabling organizations to predict equipment failures, optimize supply chains, and make real-time decisions. However, there’s a catch: these technologies are only as effective as the data they rely on. 

The quality, structure, and accessibility of your data determine whether AI provides actionable insights or misleading noise. Without preparation, even the most sophisticated AI tools can fail. 

In this article, we’ll explore why preparing your data for AI is critical, the steps involved, and how forward-thinking organizations are future-proofing their operations. 

Why Data Preparation Is Critical for AI

AI is designed to identify patterns, predict outcomes, and automate decision-making—but it can only work with reliable, well-structured data. Industrial environments often face challenges like: 

  • Unstructured Data: Equipment logs, sensor data, and manual entries are often stored in inconsistent formats. 

  • Data Silos: Separate systems prevent AI from accessing the full picture. 

  • Incomplete or Inaccurate Data: Missing values or errors compromise model accuracy. 

 

In fact, research shows that poor data quality is a leading cause of failed AI initiatives, costing organizations millions in wasted investments and delayed projects. 

The Key Characteristics of AI-Ready Data:

  1. Accuracy: Clean, error-free data ensures reliable outputs.

  2. Consistency: Standardized schemas and formats eliminate discrepancies.

  3. Completeness: Historical and real-time data provide context for better predictions.

  4. Accessibility: Centralized systems ensure data is readily available for analysis. 

Without these characteristics, AI initiatives will fail to deliver value.

The Risks of Ignoring Data Preparation

Organizations that skip proper data preparation face several risks: 

1. Misleading Insights

AI models trained on incomplete or inaccurate data can produce unreliable recommendations. For example: 

  • A predictive maintenance tool may fail to flag an impending failure due to missing sensor data. 

  • Supply chain optimizations may backfire if inventory data is outdated. 

2. Wasted Investments

Investing in AI tools without addressing data readiness leads to inefficiencies. Studies show that 80% of the time spent on AI projects goes toward cleaning and organizing data—a step that should have been addressed beforehand. 

3. Competitive Disadvantage

Competitors with well-prepared data will implement AI faster and gain a head start in improving efficiency, reducing costs, and driving innovation. 

The message is clear: ignoring data preparation is not an option for organizations looking to lead in the era of AI. 

How to Prepare Your Data for AI

Data preparation is a multi-step process that ensures your data systems are ready to support AI and advanced analytics. Here’s how industrial organizations can approach this challenge: 

1. Conduct a Data Audit

Start by assessing the current state of your data systems. Key questions to ask: 

  • What types of data are being collected?
     
  • Where are the gaps in data quality or completeness? 

  • Which systems or departments are working in silos? 

A comprehensive audit identifies weaknesses and opportunities for improvement. 

2. Standardize Data Formats and Schemas

AI requires data in consistent formats to identify patterns and make predictions. To achieve this: 

  • Define a unified schema for all data inputs. 

  • Automate standardization processes using ETL (Extract, Transform, Load) tools. 

  • Align data collection practices across departments to ensure consistency. 

3. Clean and Enrich Your Data

Dirty data leads to flawed outputs. Cleaning processes should address: 

  • Errors: Correct typos, duplicates, and outliers. 

  • Missing Values: Use statistical methods or machine learning algorithms to fill gaps. 

  • Enrichment: Add contextual information to make data more meaningful. 

4. Integrate Siloed Systems

AI thrives on comprehensive datasets. Integrating siloed systems allows AI to analyze data across the entire operation. This can be achieved through: 

  • APIs to connect legacy systems with modern platforms. 

  • Data lakes or warehouses that centralize information. 

  • Real-time synchronization tools to ensure data is always up-to-date. 

5. Implement Real-Time Data Pipelines

For AI to provide actionable insights, it needs access to real-time data. Enable continuous updates by: 

  • Deploying IoT platforms to collect sensor data. 

  • Automating data flow between devices, systems, and analytical platforms. 

  • Leveraging cloud-based tools for scalability and speed. 

6. Establish Data Governance

AI-ready data requires robust governance to maintain quality and compliance. Governance policies should address: 

  • Data ownership and accountability. 

  • Regular audits to ensure ongoing quality. 

  • Compliance with industry standards and regulations. 

Case Studies: The ROI of AI-Ready Data

Predictive Maintenance Success

A mining company used AI-driven predictive maintenance to reduce equipment downtime by 30%. The key to their success? Preparing their data by cleaning sensor logs, integrating operational systems, and ensuring real-time monitoring. 

Supply Chain Optimization

An industrial manufacturer improved delivery times by 20% using AI to optimize its supply chain. Data preparation efforts included standardizing inventory data and connecting ERP systems with IoT sensors. 

These examples highlight how prepared data directly translates into measurable business outcomes. 

Technologies That Support AI-Ready Data

Several tools and platforms can accelerate data preparation for AI: 

  • ETL Tools: Automate data cleaning, standardization, and transformation.
     
  • Data Lakes: Store and manage vast amounts of structured and unstructured data. 

  • IoT Platforms: Enable real-time data collection and integration. 

  • AI-Powered Data Prep Tools: Use machine learning to identify and fix data quality issues. 

 

Organizations should evaluate these technologies to ensure they align with their goals and infrastructure. 

The Benefits of AI-Ready Data

Preparing data for AI is an investment that delivers long-term benefits: 

  • Improved Efficiency: Automation reduces manual effort and operational delays. 

  • Smarter Decisions: AI-driven insights enable leaders to act quickly and confidently. 

  • Future-Readiness: Clean, well-integrated data supports the adoption of emerging technologies. 

 

By prioritizing data preparation, organizations position themselves as leaders in innovation and operational excellence. 

Conclusion: Take the First Step Toward AI Readiness

AI and advanced analytics are powerful tools, but they depend entirely on the quality of your data. Preparing your data isn’t just a technical challenge—it’s a strategic initiative that determines your organization’s ability to compete and grow. 

If you’re ready to future-proof your operations, watch our webinar: Data Transformation: From Raw Data to Insights. Learn actionable strategies to prepare your data for AI and unlock its full potential. 

Register for the Webinar Here

Sarah Burghardt

CPHR President

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Sarah Burghardt is the President of Dexcent, responsible for the day-to-day leadership of the organization, enabling strong execution across teams and delivering exceptional value to customers. With a track record of building high-performing teams and strengthening delivery capability, she has been an integral part of Dexcent’s growth and evolution. Sarah is known for a leadership style grounded in authenticity, clarity, and collaboration, consistently embodying Dexcent’s core values of Integrity, Care, and Excellence. She brings experience spanning executive leadership, consulting, and business operations, helping organizations align people and priorities to achieve meaningful outcomes. 

Andrew Capper

Vice President of Industrial Digital Transformation

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Andrew Capper is Vice President of Industrial Digital Transformation at Dexcent, helping industrial organizations improve data-driven decision-making by optimizing the data journey, reuniting siloed information, and delivering a trustworthy version of the truth.

With more than 25 years of experience, he is known as a results-driven leader who delivers on commitments and tackles complex information management challenges with a practical, human-centric approach. His work spans digital transformation strategy and roadmaps, governance, digital maturity assessments, and performance measurement through clear KPIs and metrics. Andrew is a NAIT graduate with training in Instrumentation Engineering Technology and Security Systems, and he brings a strong focus on safer, more effective operations from data producers through to data consumers

Nader Asgharinia

MP, P.Eng.

Vice President of Enterprise SCADA & Advanced Applications.

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Nader Asgharinia, PMP, P.Eng., is Vice President of Enterprise SCADA & Advanced Applications at Dexcent, leading the delivery of complex, mission-critical solutions with a clear focus on client experience and operational excellence. With more than 30 years in business execution and over 25 years managing multi-million-dollar programs for mission-critical and SCADA systems, he brings a pragmatic, delivery-at-scale approach to every engagement. Nader is recognized for building high-performing teams, driving disciplined portfolio execution, and delivering measurable business outcomes, including significant growth in program portfolios and team capacity over time. He holds a B.Sc.(Hons.) in Electrical and Electronics Engineering from the University of Newcastle-Upon-Type in the UK, a B.Sc. in Computer Science from the University of Calgary, completed Georgetown University’s Director’s Program, is a Professional Engineer in Alberta, and a Project Management Professional.

Gerrit Nel

CISSP, CISM – Vice President of OT Infrastructure and Cyber Security Services

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Tobias (Gerrit) Nel, CISSP, CISM, is Vice President of OT Infrastructure and Cyber Security Services at Dexcent, leading the development and delivery of practical services and solutions that integrate, complement, or replace OT infrastructure and protect OT assets from cyber threats. He is known for building resilient security frameworks, governance processes, and integrated solutions that reduce risk and support compliance across diverse industries. Gerrit has over 40 years of relevant IT/OT experience and has built and delivered highly skilled and high-performance delivery teams. His strengths include Cyber Security roadmaps, security architecture, incident response, and alignment to standards such as IEC 62443, NIST, and NERC CIP. Furthermore, he has deep foundational technical experience in Networking and OT infrastructure systems architectures that he leverages in building and leading successful delivery teams. Gerrit holds a B.Sc. in Computer Science from the University of Johannesburg and brings deep cross-sector experience supporting clients in oil and gas, mining, chemical, healthcare, financial, and government environments.

Jaydeep Deshpande

P.Eng. – Chief Strategy Officer (CSO)

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Jaydeep Deshpande, P.Eng., is Chief Strategy Officer at Dexcent, where he helps shape the company’s future by connecting strategy, innovation, and execution. Having led Dexcent as President for six years, he combines 28 years of experience with a deep understanding of what it takes to scale a business while staying true to its culture and purpose.
 
Known for his people-first leadership and ability to navigate complex transformation, Jaydeep plays a central role in advancing Dexcent’s strategic priorities, strengthening key relationships, and unlocking new growth opportunities. He brings a disciplined yet human approach to change, aligning teams, accelerating growth, and ensuring the organization evolves with clarity and intent. He is passionate about building strong teams, fostering a culture grounded in integrity, care, and excellence, and positioning Dexcent to create lasting value for its customers, people, and partners.
 
He holds a Bachelor of Science in Engineering from the University of Alberta, is a Prosci Certified Change Practitioner and a Project Management Professional (PMP), and completed the CMA Accelerated Accounting Program, complemented with more than 20 years of financial management expertise.

Karim Amarshi

Chairman of the Board

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Karim Amarshi is Chair of Dexcent’s Board of Directors, providing governance leadership and strategic oversight to support the company’s long-term strategy and executive team. With nearly 40 years as an entrepreneur and owner-operator, he is recognized for building high-performance organizations and forging strategic alliances across Information Technology, government, health care, education, and energy. He is the former co-owner and Chief Executive Officer of one of Canada’s leading enterprise Information Technology solution providers, where he led the organization through three successful mergers and helped scale long-term client and vendor partnerships. Karim remains active across a diverse business portfolio, serving as a founding principal, officer, and advisor to organizations spanning Information Technology, hospitality, manufacturing, retail, and real estate in Canada and internationally.

Yasmin Jivraj

FCIPS, I.S.P. | Board Member

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Yasmin Jivraj, FCIPS, I.S.P., is a Board Member at Dexcent, providing executive guidance and strategic oversight to support corporate management and long-term business direction. Over a 35-year career, she has held senior leadership roles across private, public, and non-profit organizations, with a track record of building operating foundations and driving profitable growth. Following a 15-year tenure as a co-owner and President of one of Canada’s leading strategic Information Technology solution providers, she expanded her governance leadership through active board service in post-secondary education and community-focused organizations. She is recognized for decisive, purpose-led leadership, clear communication, and deep expertise in technology, business models, and methodologies that help enterprise organizations advance digital transformation.

Nadir Jivraj

CEO, Board Member

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As Chief Executive Officer, Nadir is accountable for providing overall leadership and Dexcent’s Industrial operational performance. Nadir has been involved as an executive sponsor with Oil & Gas and Mining companies for over 35 years, and through the years has developed a strong working relationship with the Executive leadership team of many Fortune 500 companies.

Nadir is known for recognizing value and superior investment opportunities in the technology services sector. His pursuit of highly prospective technology companies around the world has resulted in numerous company start-ups. Prior to starting Dexcent, Nadir had led companies through highly profitable business transactions, including the merger of Atlas Systems Group with CompCanada (later renamed Acrodex) in 2000 and later as Chairman of the Board of Axcend Pvt – an engineering solutions provider – based in Bangalore, India from 2004 – 2014. Acrodex and Axcend were sold in 2015