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
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
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 :
- What is a data lake? - introduction to Data Lakes and analytics - AWS. (n.d.). https://aws.amazon.com/ what-is/data-lake/
- 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
- 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
- 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
- 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/
- 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.
