**8. Conclusions**

Enterprises and business organizations exploit a huge volume of data to understand their customers and to make informed business decisions to stay competitive in the field. However, big data come in a variety of formats and types (e.g., structured, semi-structured and unstructured data), making it difficult for businesses to manage and use them effectively. Based on the structure of the data, typically, two types of data storage are utilized in enterprise data management: the data warehouse (DW) and data lake (DL). Although being

used as interchangeable terms, they are two distinct storage forms with unique characteristics that serve different purposes.

In this review, a comparative analysis of data warehouses and data lakes by highlighting the key differences between the two data managemen<sup>t</sup> approaches was envisaged. In particular, the definitions of the data warehouse and data lake, highlighting their characteristics and key differences, were detailed. Furthermore, the architecture and design aspects of both DWs and DLs are clearly discussed. In addition, a detailed overview of the popular DW and DL tools and services was also provided. The key challenges of big data analytics in general, as well as the challenges of implementation of DWs and DLs, were also critically analyzed in this survey. Finally, the opportunities and future research directions were contemplated. We hope that the thorough comparison of existing data warehouses vs. data lakes and the discussion of open research challenges in this survey will motivate the future development of enterprise data managemen<sup>t</sup> and benefit the research community significantly.

**Author Contributions:** Conceptualization, A.N. and D.M.; methodology, A.N. and D.M.; validation, A.N.; formal analysis, D.M.; investigation, A.N.; data curation, A.N. and D.M.; writing—original draft preparation, A.N. and D.M.; writing—review and editing, A.N. and D.M.; visualization, A.N.; supervision, A.N.; project administration, A.N. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.
