Evolution of Enterprise Data Warehouse: Past Trends and Future Prospects |
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| © 2023 by IJCTT Journal | ||
| Volume-71 Issue-9 |
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| Year of Publication : 2023 | ||
| Authors : Sivakumar Ponnusamy | ||
| DOI : 10.14445/22312803/IJCTT-V71I9P101 | ||
How to Cite?
Sivakumar Ponnusamy, "Evolution of Enterprise Data Warehouse: Past Trends and Future Prospects," International Journal of Computer Trends and Technology, vol. 71, no. 9, pp. 1-6, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I9P101
Abstract
Data Warehousing has evolved over the past few decades primarily due to the exponential growth of data that traditional system is unable to handle and secondly due to technological advancement, which makes it feasible to have real-time data and cloud technology which provides unlimited storage and scalability. The journey for these changes started with the MIS (Management Information system) when data integration from various IT systems was possible. In the next stages, data repositories come into demand, and warehousing modernizes with the assistance of data mart mechanisms. The emergence of new tools and software used for the same has also given rise to Modern cloud-based SaaS data processing systems. Data lakes and data lakehouses have transformed the systems, providing greater autonomy and enabling the processing of larger volumes of data to generate insights for decision-making. The future of Datawarehouse will be based on AI and Machine Learning, which would be helpful with infrastructure scalability, cost savings, and agility, as well as increasing the reliability and usability of the data as well.
Keywords
Data warehouse, ETL, DataLakeHouse, Bigdata, Machine learning.
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