FEATURE: NETWORK AND SECURITY efficiency. Organisations can optimise costs by identifying inefficiencies and improving resource use. Personalisation at scale strengthens customer loyalty and experience. Predictive models also support proactive adaptation to market shifts. These platforms uncover untapped revenue opportunities and help craft competitive pricing strategies. Beyond numbers, they foster a culture of innovation and continuous improvement. For modern enterprises, adopting Big Data and analytics is a strategic imperative – transforming decision-making from reactive to anticipatory, and unlocking long-term value.
Kunal Purohit, President – Next Gen Services at Tech Mahindra
What are the technology challenges around implementation and management of Big Data and predictive analytics platforms?
Organisations face multiple technology challenges when implementing Big Data platforms. Integrating data from diverse sources while ensuring consistency and quality is a major hurdle. As data volumes grow, scalability becomes essential without compromising performance or cost. Security and privacy compliance – especially with regulations like GDPR – remain on-going concerns. A shortage of skilled professionals complicates real-time analytics implementation. Infrastructure costs and the need for continuous optimisation further strain resources. Model drift is a key challenge, maintaining, monitoring and validating becomes critical for predictive models, Tech Mahindra’ s VerifAI solution is built to address this challenge. Lastly, organisational change management is often overlooked but crucial, as successful adoption demands shifting traditional mindsets toward datadriven operations. Addressing these challenges requires a blend of technical excellence, strategic vision and cross-functional collaboration.
What is the required enterprise skill sets around implementation and management of Big Data and predictive analytics platforms?
Enterprises need a multi-disciplinary skill set to implement and manage Big Data platforms effectively. Data engineering and cloud architecture skills are vital for building scalable pipelines using tools like Hadoop, Spark and cloud services. Data scientists must be adept in Machine Learning, modelling and analytical tools. Data governance experts must ensure compliance with regulations such as GDPR and Central Consumer Protection Authority( CCPA). Business Intelligence tool proficiency is essential to convert insights into actions. Soft skills like collaboration, project management and change leadership help align cross-functional teams. At Tech Mahindra, our Centres of Excellence drive continuous upskilling and foster innovation across enterprise-wide data initiatives. p
www. intelligentcio. com INTELLIGENTCIO MIDDLE EAST 27