Data Governance Expert Anupam Sharma: Turning Data Chaos into Crystal-Clear Narratives
In the rapidly evolving world of data governance and analytics, few professionals possess the unique blend of technical expertise and strategic vision that Anupam Sharma brings. As APAC Data Governance Manager for ELAIT & ELAIT Health, Sharma has built a career spanning over 14 years, transitioning from programming to techno-functional roles that bridge deep technical knowledge with strategic implementation. Welcome Anupam, sharing his insight in Data Demystified Thoughts series.
The Data Whisperer
For Sharma, data is more than just numbers on a spreadsheet; it’s a dynamic force shaping decision-making and innovation.
Perhaps most telling is Sharma’s perspective on data itself: “Data isn’t just numbers; it’s a playground of possibilities and a powerful toolkit for solving real-world problems. I thrive on the challenge of teasing out hidden stories and actionable insights from raw information. Think of me as a data whisperer, turning complexity into crystal-clear narratives that reveal not just problems but also the solutions.”
This philosophy defines his approach to data governance—creating not only reliable data systems but also ones that drive tangible impact. “I’m driven by the desire to translate data into measurable impact—optimising systems, improving lives, and even tackling global issues. Data governance is the bedrock of this process, ensuring data is reliable, secure, and accessible to those who need it.”
The Evolution of Data Science Skills
The data science landscape is shifting, demanding a combination of technical and soft skills.
“The data science field is rapidly evolving,” Sharma explains. “Data scientists today need a mix of expertise—machine learning, natural language processing (NLP), generative AI, programming, real-time data processing, and cloud architecture—alongside communication skills, ethical awareness, and adaptability. Specialisation in areas like NLP and computer vision is becoming increasingly valuable as businesses seek deeper insights.”
Effective Data Governance: Striking the Right Balance
One of Sharma’s core responsibilities is ensuring effective data governance while maintaining accessibility. His approach is pragmatic: “To make data governance work, I establish clear rules and implement access controls. Role-based permissions help balance control and accessibility, ensuring security needs and business goals are met.”
His governance philosophy can be summed up in a simple yet powerful mantra: “Delivering the right data, at the right time, in the right form, for the right user.”
Tackling Data Quality Challenges
Ensuring data quality across diverse sources is one of the biggest hurdles in data governance. Sharma identifies key challenges:
- Diverse data formats complicate integration.
- Inconsistencies cause data mismatches.
- Human errors degrade data integrity.
- Lack of standardisation hinders effective data integration.
His solutions are methodical: “Rigorous validation and cleaning processes, standardisation of data formats, lifecycle governance for consistency, advanced data management tools, and collaboration with cross-functional expert teams are all essential to maintaining data integrity.”
The AI Revolution in Data Management
AI is revolutionising data management, and Sharma has been at the forefront of this transformation. “AI automates data cleaning, enhances pattern recognition, improves accuracy, and extracts insights from unstructured data through NLP.”
These benefits translate into tangible results. “AI has helped us reduce data quality errors by 40% through automated validation and has streamlined our business glossary development.”
Looking ahead, Sharma sees generative AI as a game-changer. “Generative AI is transforming our industry—enhancing content creation, boosting creativity, delivering personalised experiences, and advancing automation. We’ve leveraged it for dynamic data management processes and improved customer interaction efficiency.”
Ethical Considerations in the AI Era
With AI’s growing influence, ethical considerations are more critical than ever. Sharma ensures his organisation upholds data ethics through a structured approach:
- Transparency in data collection.
- Alignment with privacy regulations.
- Data anonymisation to protect user identities.
- Commitment to mitigating data bias and ensuring AI transparency.
“AI ethics must be a priority,” Sharma states. “It’s about balancing innovation with responsibility—ensuring fairness, transparency, and accountability in AI-driven decisions.”
Data Visualisation: Telling Stories with Clarity
Sharma is also a strong advocate for data visualisation as a storytelling tool. His approach is rooted in clarity and audience awareness: “Simplify complex data into clear visuals. Tailor visualisations to match the audience’s expertise. Effective tools like Tableau and Power BI make data more digestible.”
He also warns against common pitfalls. “Avoid overcomplicating visuals, misusing chart types, and using misleading colours. Simplicity and clarity ensure effective communication of insights.”
The Future of Data, AI, and Emerging Technologies
Looking ahead, Sharma predicts that AI, blockchain, and quantum computing will drive the next wave of technological evolution. “We are investing in AI research and talent development, focusing on ethical AI implementation to stay ahead of the curve.”
Perhaps most telling is the career advice that has guided Sharma’s approach: “Focus on a people-centric and process-centric approach when solving problems, not just on technology.”
As data continues to shape business strategy and operations, professionals like Anupam Sharma will be at the forefront—navigating the complex intersection of technology, ethics, and human needs and transforming data chaos into crystal-clear narratives that drive meaningful action.
A big thank you to Anupam Sharma, for sharing your insights on data governance, AI, and analytics with us in Data Demystified Thoughts series. If you want to connect with Anupam after reading his Data Demystified Thoughts, please reach out via his LinkedIn!
See more Data Demystified Thoughts interview pieces here!
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Last updated: March 2025
