Data Evolution: From Data Warehousing Foundations to Intelligence Insights

Jaishankar Inukonda

doi:10.5281/zenodo.14353060

Authors

Jaishankar Inukonda Author

DOI:

https://doi.org/10.5281/zenodo.14353060

Keywords:

Data Warehousing, Data Marts, Data Lakes, Business Intelligence, Big Data, Data Science, Healthcare Data, Data Security, ETL, Database, Unstructured Data, Data Analytics

Abstract

The evolution of data management has transformed the way organizations process, analyze, and use information to drive strategic decisions. From the very beginning of structured, centralized data warehouses in the late 20th century, the journey has led to advanced, intelligence-driven analytics in the 21st century. Data warehouses provided a foundation for collecting and organizing structured data, enabling historical analysis and standardized reporting. While big data, cloud computing, and machine learning are making great strides, these gave way to new paradigms and ways of handling enormous quantities of data in complex formats with enormous speed. Today, powered by artificial intelligence, predictive analytics, and natural language processing, insights give organizations a crystal ball to anticipate trends, optimize operations, and proactively address challenges. This article recounts the milestones in data evolution, technological breakthroughs, challenges in integration and scalability, while emerging trends have the potential to define the role of data anew in shaping future innovation.

References

Inmon, W. H. (2005). Building the Data Warehouse. Wiley.

Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209.

Manyika, J., et al. (2011). Big Data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.

Tableau Software. (2021). Tableau and the Role of Business Intelligence. Retrieved from www.tableau.com.

Gartner. (2020). The Future of Analytics: Trends in Augmented and Artificial Intelligence.

Davenport, T. H., & Harris, J. G. (2007). Competing on Analytics: The New Science of Winning. Harvard Business Review Press.

Mishra, B. K., & Panda, P. (2019). Evolution of Data Warehousing to Big Data Analytics: A Review. Journal of Advanced Database Management & Systems, 6(1), 12–22.

Zhang, D., Hu, P. J., & Kotlarsky, J. (2020). Exploring the Role of Cloud Computing in Business Intelligence and Analytics: A Case Study. Journal of Information Technology, 35(4), 352–374.

Russom, P. (2011). Big Data Analytics: TDWI Best Practices Report. The Data Warehousing Institute.

Marr, B. (2016). Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results. Wiley.

Ramesh, V., & Dhuruvasan, S. (2020). The Transition from Traditional Data Warehousing to Real-Time Data Analytics. International Journal of Data Science, 5(2), 85–98.