NLDIMSR Faculty Insights: The Rise of Big Data

‘Big Data is the new science which empowers the world’. Indeed, analytics for big data is the new emerging science, stimulated by advances in computer processing power and tools for big data. Big data derives most of its value from the insights it produces when analyzed such as finding patterns, deriving meaning and ultimately making business decisions. With big data technology continuously evolving, businesses are increasingly turning to predictive analytics to help them deepen their customer engagement, optimize processes, and reduce their operational costs. The massive scale and growth of data particularly unstructured data outstrip the capabilities of traditional storage and analytic solutions. Needless to say data rich organizations require new analytic processes and technologies to help them unlock the potential of big data.

The combination of real-time data streams and predictive analytics have the potential to deliver a significant competitive advantage for business. For instance, predictive models are informed by historical data that in real time which may be a few seconds or minutes old. In the past, predictive models took time to build and test to exploit those patterns. The large volumes of data provide greater opportunities for fine-tuning and refining the model. In this way, data analytics differs from more traditional data mining. Automated analytics algorithms like machine learning, continuously inform the predictive model and enable it to adjust. Each adjustment can increase the accuracy of the model as the system continues to generate new algorithms as needed, ensuring that the model remains relevant.


By Prof Dr Nigel D’silva

Faculty at NL Dalmia Institute of Management Studies and Research

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