Implementing Data Strategy

Design Considerations and Reference Architecture for Data-Enabled Value Creation


  • Radhakrishnan Balakrishnan Indian Institute of Management, Raipur
  • Satyasiba Das Indian Institute of Management, Raipur, India
  • Manojit Chattopadhyay Indian Institute of Management



Data management, Reference architecture, Data strategy, Big Data design considerations, Big Data governance, Data-enabled value creation


With the arrival of Big Data, organizations have started building data-enabled customer value propositions to increase monetizing and cost-saving opportunities. Organizations have to implement a set of guidelines, procedures, and processes to manage, process and transform data that could be leveraged for value creation. This study has approached the journey of an organization towards data-enabled value creation through four levels of data processing, such as data extraction, data transformation, value creation, and value delivery. This study has critical inferences on using data management solutions such as RDBMS, NoSQL, NewSQL, Big Data and real-time reporting tools to support transactional data in internal systems, and other types of data in external systems such as Social Media. The outcome of this study is a methodological technology independent data management framework an organization could use when building a strategy around data. This study provides guidelines for defining an enterprise-wide data management solution, helping both the academicians and practitioners.

Author Biography

Satyasiba Das, Indian Institute of Management, Raipur, India

Associate Professor, 
Business Policy and Strategy, Indian Institute of Management Raipur, India
Atal Nagar, Kurru (Abhanpur), Raipur, Chhattisgarh, India 493 661




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How to Cite

Balakrishnan, R., Das, S., & Chattopadhyay, M. (2020). Implementing Data Strategy: Design Considerations and Reference Architecture for Data-Enabled Value Creation. Australasian Journal of Information Systems, 24.



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