New Delhi, July 2 -- In the rapidly evolving digital landscape of India, a new paradigm is emerging that promises to revolutionise how businesses operate and innovate: data intelligence.
As the country's digital economy continues to flourish, organisations are recognising that data is not just an asset but a catalyst for growth and transformation. Data intelligence represents the next critical step in harnessing the power of information, going beyond mere data collection and analysis to unlock profound insights that drive decision-making and strategic planning.
Data intelligence represents tailored AI solutions that leverage an organisation's proprietary data, focusing on domain-specific insights rather than broad, general intelligence. For instance, in India, this could mean using data intelligence and AI to optimise supply chains in the manufacturing sector or improving crop yield predictions in agriculture which address local business challenges directly.
This approach allows enterprises to harness the power of custom AI models built on their unique data assets, delivering targeted intelligence that directly addresses their specific business needs and challenges.
This synergy creates a powerful framework enabling enterprises to extract maximum value from their data assets, turning raw information into actionable insights.
The Indian Context
In India's burgeoning economy, data has emerged as a new form of currency, driving growth across sectors. According to a report by NASSCOM, India's data and AI industry is expected to contribute $450-500 billion to the country's GDP by 2025, accounting for 10% of the $5 trillion economy aspiration. This projection underscores the immense potential of data intelligence in shaping our nation's economic future.
The Indian government's initiatives like Digital India and the push for Smart Cities have created a fertile ground for the proliferation of data-driven technologies. These programs have not only increased digital adoption among citizens but also generated vast amounts of data that can be leveraged for public good. For instance, the Smart Cities Mission is utilising data analytics to improve urban planning, traffic management, and public service delivery.
In the private sector, industries such as Banking, Financial Services, and Insurance (BFSI), healthcare, and manufacturing are at the forefront of embracing data intelligence:
BFSI: Banks are using advanced analytics to detect fraud, assess credit risk, and personalise customer experiences. Healthcare: Data intelligence is enabling predictive diagnostics and improving patient outcomes through data-driven treatment plans. For instance, Tata 1mg serves 220 million customers across 27,000+ pin code markets in India, achieving a 50% reduction in ETL costs and empowering 1,000+ non-data team business users to access data insights. Manufacturing: Firms are optimising their supply chains and predicting equipment failures, leading to significant cost savings and increased productivity.
Role of AI in the Data Intelligence Platform
The integration of AI with data management systems is a cornerstone of data intelligence. AI-powered data lakehouse platforms are emerging as a solution to unify data management and analytics, addressing critical challenges such as data silos and governance issues. These platforms provide a single source of truth for all data within an organisation, enabling seamless integration of structured and unstructured data for comprehensive analysis.
This is exemplified by Indian airline giant Air India, which is leveraging this technology to enhance both its enterprise operations and customer experience.
On the enterprise side, Air India's management team can now gain quick insights into various operational aspects using natural language queries. Executives can simply ask questions about commercial performance of flights, on-time performance challenges at specific airports, or overall operational status, and receive responses in plain English.
In terms of customer-facing applications, instead of requiring customers to navigate through complex websites, the airline now offers chatbots and AI agents that can answer queries on refunds, baggage policies, and ticket rules, in natural language.
Moreover, given the sensitive nature of customer information and strict industry regulations, the airline utilises Unity Catalog, a unified and open governance solution for data and AI, to securely manage sensitive customer data, including names, dates of birth, and travel documents, while maintaining the highest standards of data privacy and security.
AI's role in enhancing decision-making and operational efficiency cannot be overstated. By leveraging machine learning algorithms, businesses can predict trends, automate routine tasks, and optimise processes. In the manufacturing sector, AI is being used to refine product inspection and quality control, significantly reducing defects and improving overall productivity.
Strategies for Indian Enterprises
To fully leverage the potential of data intelligence, Indian enterprises must adopt a comprehensive and strategic approach. This involves cultivating a data-first culture, investing in scalable infrastructure, focusing on data quality and governance, integrating AI/machine learning, and prioritising data privacy and ethics.
The cultural shift of developing a data-first culture requires prioritising data literacy across all levels of the organisation, ensuring that employees understand the value of data and how to use it effectively in their roles. With an inclusion of over 80% of data and analytics strategies and change management programmes, a Gartner study showed that data literacy has already become an explicit and necessary driver of business value.
Investing in scalable infrastructure is another crucial aspect of leveraging data intelligence. The International Data Corporation (IDC) predicts that by 2025, the global datasphere will grow to 163 zettabytes, and nearly 30% of this data will need real-time processing. This staggering growth in data volume and velocity necessitates a robust, flexible and scalable infrastructure capable of adapting to evolving data needs.
Data governance policies also become paramount, as a comprehensive policy can maintain high-quality data that serves as a solid foundation for data intelligence initiatives.
Furthermore, integrating AI and machine learning into data analytics processes is crucial for uncovering hidden patterns, generating predictive insights, and enhancing decision-making capabilities.
Prioritising data privacy and ethics is also paramount. Organisations must establish clear guidelines for data collection, usage, and storage to maintain trust with customers and stakeholders.
Conclusion
The journey towards becoming a data-intelligent nation is not without challenges. However, with continued investment in infrastructure, skills development, and partnerships between technology leaders and Indian enterprises, our country is well-positioned to lead the global data intelligence revolution.
As we stand on the cusp of this data-driven era, the message is clear: embrace data intelligence, for it holds the key to unlocking India's full potential in the digital age.
By leveraging the power of data, AI, and advanced analytics, Indian businesses can drive innovation, improve operational efficiency, and create new value for their customers and stakeholders.
The future of India's digital economy is intrinsically linked to the ability to harness data intelligence effectively, and the time to act is now.
Published by HT Digital Content Services with permission from TechCircle.