Evolutionary Trends in Data Warehousing: Progress, Challenges and Future Directions

Deepak Jayabalan

Abstract: Data warehousing has come a long way from serving as mere repositories of structured data to complex ecosystems for storage, management, and analytics. This research paper has reviewed the evolutionary trends in data warehousing considering emerging paradigms such as cloud-based data warehousing, data lakehouses, and data mesh. We have discussed the challenges of variety, velocity, and volume presented by data and the prospects and cons affected by the new trends. Finally, by reviewing the literature, we identify the areas that require further research or enhancement in data warehousing. Our findings indicate that modern data warehousing architecture needs to be scalable, agile, and interoperable. In addition, we conclude with the prospects in the field of data warehousing and possible areas that could be ripe, given the prospects in the field of data warehousing, for sustaining sustainable and ethical practices in data handling.

Keywords: Data warehousing, cloud-based data warehousing, data lakehouses, data mesh, agile data warehousing, data governance, data quality