The Data Lakes: A Leap Forward Future of Data Warehousing


Authors : Bhushan Fadnis

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/msj4vkwk

Scribd : https://tinyurl.com/3vh3xt8y

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY2158

Abstract : With the rise of data and technological advancements, organizations are more interested than ever in exploring infinite data. As data grows, there are no limits to what we can analyze and derive from it. An organization needs a central data repository that should be one trustworthy source. A data lake will benefit any company by helping it make data-driven decisions and identify the right business strategy. Unlike data warehouses built for specific use cases, a data lake can be built for broader use cases addressing current or future business rising needs. Data Lakes are a steppingstone in the data exploration journey, and they have come a long way from traditional databases and data warehouses. This research paper will describe the data lake architecture, functionality, and ways to build it. To build a lake, this paper will examine Amazon Web Services (AWS) and the various tools it provides for this case. Every organization today should consider data lakes strongly and consider their advantages.

Keywords : Data Lakes, Data Warehouse, Database, Analytics.

References :

  1. What is a data lake? - introduction to Data Lakes and analytics - AWS. (n.d.). https://aws.amazon.com/ what-is/data-lake/ 
  2. Khine, P. P., & Wang, Z. S. (2018, February 2). Data lake: A new ideology in Big Data Era. ITM Web of Conferences. https://doi.org/10.1051/itmconf/2018 1703025
  3. Llave, M. R. (2018). Data lakes in business intelligence: Reporting from the trenches. Procedia Computer Science, 138, 516-524. https://doi.org/ 10.1016/j.procs.2018.10.071 
  4. Nambiar A, Mundra D. An Overview of Data Warehouse and Data Lake in Modern Enterprise Data Management. Big Data and Cognitive Computing. 2022; 6(4):132. https://doi.org/10.3390/bdcc6040132
  5. Data Lake vs Data Warehouse vs Data Mart - difference between Cloud Storage Solutions - AWS. (n.d.-a). https://aws.amazon.com/compare/the-difference-between-a-data-warehouse-data-lake-and-data-mart/
  6. Secure data lake - aws lake formation - AWS. (n.d.-c). https://aws.amazon.com/lake-formation/

With the rise of data and technological advancements, organizations are more interested than ever in exploring infinite data. As data grows, there are no limits to what we can analyze and derive from it. An organization needs a central data repository that should be one trustworthy source. A data lake will benefit any company by helping it make data-driven decisions and identify the right business strategy. Unlike data warehouses built for specific use cases, a data lake can be built for broader use cases addressing current or future business rising needs. Data Lakes are a steppingstone in the data exploration journey, and they have come a long way from traditional databases and data warehouses. This research paper will describe the data lake architecture, functionality, and ways to build it. To build a lake, this paper will examine Amazon Web Services (AWS) and the various tools it provides for this case. Every organization today should consider data lakes strongly and consider their advantages.

Keywords : Data Lakes, Data Warehouse, Database, Analytics.

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