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
Keywords: 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




Addagada, T. (2019). Customer Data Protection: Deriving Value and Ownership. Retrieved May 24, 2019, from

Anderson, C., & Li, M. (2017). Five building blocks of a data-driven culture. Retrieved May 27, 2019, from

Aviza, E. (2017). Data is the Gold of the 21st Century. Retrieved May 20, 2019, from

Bowen, R., & Smith, A. R. (2014). Developing an enterprisewide data strategy. Healthcare Financial Management, 68(4).

Braganza, A. (2004). Rethinking the data – information – knowledge hierarchy : towards a case-based model. International Journal of Information Management, 24, 347–356.

Commercial Bank, C. G. (2018). Why Dual Approval Matters. Retrieved May 6, 2019, from

Data Integration. (2018). Retrieved May 20, 2019, from

Davenport, T. H. (2014). Big Data at work: Dispelling the myths and uncovering the opportunities. Harvard Business Review Press.

Davenport, T. H., Harris, J. G., Long, D. W. De, & Jacobson, A. L. (2001). Data to Knowledge to Results: Building an Analytic Capability. California Management Review, 43(2).

Davenport, T., & Verma, A. (2018). It’s time to modernize your big data management techniques. Retrieved May 18, 2019, from

Doyle, M. (2017). The Importance of a “Data Integration First” Strategy. Retrieved May 15, 2019, from

Foote, K. D. (2019a). A Brief History of Master Data. Retrieved May 12, 2019, from

Foote, K. D. (2019b). Data Modeling in an Agile World. Retrieved May 15, 2019, from

Franklin, M., Halevy, A., & Maier, D. (2005). From databases to dataspaces: A new abstraction for information management. SIGMOD Record, 34(4), 27–33.

Ghosh, P. (2019). Data Governance and Data Quality Use Cases. Retrieved May 12, 2019, from

Griffin, J. (2005). Data governance: a strategy for success. DM Review, 15(8), 15, 70.

Grolinger, K., Higashino, W. A., Tiwari, A., & Capretz, M. A. M. (2013). Data management in cloud environments : NoSQL and NewSQL data stores. Journal of Cloud Computing.

Hendler, J. (2009). Web 3.0 Emerging. IEEE Computer Society, 42(January), 111–113.

Huber, G. P. ., & Power, D. J. . (1985). Retrospective Reports of Strategic-Level Managers : Guidelines for Increasing Their Accuracy. Strategic Management Journal, 6(2), 171–180.

Kambatla, K., Kollias, G., Kumar, V., & Grama, A. (2014). Trends in big data analytics. Journal of Parallel and Distributed Computing, 74(7), 2561–2573.

Kaur, K., & Sachdeva, M. (2017). Performance Evaluation of NewSQL Databases. In International Conference on Inventive Systems and Control (pp. 1–5).

Khatri, V., & Brown, C. V. (2010). Designing Data Governance. Communications of the ACM, 53(1).

Kooper, M., Maes, R., & Lindgreen, R. E. (2011). Information Governance as a Holistic Approach to Managing and Leveraging Information Prepared for IBM Corporation. International Journal of Information Management, 31.

Korhonen, J. J., Melleri, I., Hiekkanen, K., & Helenius, M. (2013). Designing Data Governance Structure : An Organizational Perspective. GSTF Journal On Computing, 2(4), 11–17.

Lawton, G. (2019). 7 enterprise use cases for real-time streaming analytics. Retrieved May 20, 2019, from

Lim, C., Kim, K., Kim, M., Heo, J., Kim, K., & Maglio, P. P. (2018). From data to value : A nine-factor framework for data-based value creation in information-intensive services. International Journal of Information Management, 39(January 2017), 121–135.

Link, S., & Prade, H. (2019). Relational database schema design for uncertain data Relational Database Schema Design for Uncertain Data $. Information Systems.

Lourenço, J. R., Cabral, B., Carreiro, P., Vieira, M., & Bernardino, J. (2015). Choosing the right NoSQL database for the job: a quality attribute evaluation. Journal of Big Data, 2(1), 1–26.

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation , competition , and productivity. McKinsey Global Institute, (May).

Marco, D. (2006). Understanding data governance and stewardship, Part 1. DM Review, 16(9), 28.

Mazzei, M. J., & Noble, D. (2017). Big data dreams : A framework for corporate strategy. Business Horizons, (60), 405–414.

McAfee. (2019). Overview of Serbanes-Oxley. Retrieved May 20, 2019, from

Mirza, H. T., Chen, L., & Chen, G. (2010). Practicability of dataspace systems. International Journal of Digital Content Technology and Its Applications, 4(3), 233–243.

Mohan, C. (2013). History Repeats Itself : Sensible and NonsenSQL Aspects of the NoSQL Hoopla. IBM Alamaden Research Center, 11–16.

Newman, D., & Logan, D. (2009). Governance Is an Essential Building Block for Enterprise Information Management. Gartner Research, (May 2006).

Pääkkönen, P., & Pakkala, D. (2015). Big Data Research Reference Architecture and Classification of Technologies , Products and Services for Big Data Systems. Big Data Research, 2(4), 166–186.

Patrizio, A. (2019). What is Data Virtualization? Retrieved May 20, 2019, from

Pavlo, A., & Aslett, M. (2016). What is really new with NewSQL ? SIGMOD Record, 45(2), 45–55.

Perera, S. (2018). A Gentle Introduction to Stream Processing. Retrieved May 20, 2019, from

Pokorny, J. (2013). NoSQL databases: A step to database scalability in web environment. International Journal of Web Information Systems, 9(1), 69–82.

Rocha, L., Vale, F., Cirilo, E., Barbosa, D., & Mourao, F. (2015). A Framework for Migrating Relational Datasets to NoSQL ∗. Proceedia Computer Science, 51, 2593–2602.

Salido, J. (2010). Data Governance for Privacy, Confidentiality and Compliance: A Holistic Approach. ISACA Journal, 6, 1–7.

Sareen, P., & Kumar, P. (2015). NoSQL Database and its comparison with SQL Database. International Journal of Computer Science & Communication Networks, 5(5), 293–298.

Simsek, G. (2019). What is new about NewSQL? Retrieved June 7, 2019, from

Spivack, N. (2011). Web 3.0: The Third Generation Web is Coming. Retrieved May 18, 2019, from

Stantic, B., & Pokorny, J. (2014). Opportunities in Big Data Management and Processing. Databases and Information Systems VIII.

Techopedia. (2011). Garbage In, Garbage Out (GIGO). Retrieved May 15, 2019, from

Weber, K., Otto, B., & Osterle, H. (2009). One Size Does Not Fit All — A Contingency Approach to Data Governance. ACM Journal of Information Quality, 1(1).

Weill, P., & Ross, J. (2005). A matrixed approach to designing IT governance. MIT Sloan Management Review, 46(2), 26–34.

Yang, F. (2016). Building a Streaming Analytics Stack with Apache Kafka and Druid. Retrieved May 20, 2019, from

Zack, M. H. (1999). Managing Codified Knowledge. Sloan Management Review, 40(4), 45–58.

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.
Research Articles