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Quarterly Journal of Emerging Technologies and Innovations

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Published

2023-06-29

Issue

Vol. 8 No. 2 (2023): QJETI-APRIL-JUNE

Section

Articles

How to Cite

Kothandapani, H. P. (2023). Emerging Trends and Technological Advancements in Data Lakes for the Financial Sector: An In-depth Analysis of Data Processing, Analytics, and Infrastructure Innovations. Quarterly Journal of Emerging Technologies and Innovations, 8(2), 62–75. Retrieved from https://vectoral.org/index.php/QJETI/article/view/127

Emerging Trends and Technological Advancements in Data Lakes for the Financial Sector: An In-depth Analysis of Data Processing, Analytics, and Infrastructure Innovations

Hariharan Pappil Kothandapani

Senior Data Science Analytics Developer at FHLBC, MS Quantitative Finance @ Washington University in St Louis

https://orcid.org/0009-0006-1768-9328

Keywords: artificial intelligence, data lakes, data lakehouse, data mesh, financial industry, hybrid cloud, machine learning

Abstract

The financial sector is increasingly adopting data lakes to manage and analyze vast amounts of structured and unstructured data. This paper explores the latest trends and technological advancements in data lakes, focusing on their application in the financial industry. Key areas of analysis include the integration of artificial intelligence (AI) and machine learning (ML) for predictive modeling, risk assessment, and process automation. Additionally, the paper examines real-time data processing and its importance in enabling immediate decision-making and market responsiveness. The evolution of data lakehouse architecture, which merges data lakes with data warehouses, is discussed as a solution for handling diverse data types and supporting both batch and real-time analytics. On the infrastructure side, the paper explores innovations such as serverless data lakes, which reduce operational complexity and costs while providing scalability. The shift towards hybrid cloud environments is analyzed for its balance of data security and cloud-based scalability. The paper looks at data mesh architectures, which decentralize data management to align with specific business domains, improving scalability and governance. Lastly, the evolution of data lakehouse architecture, which merges data lakes with data warehouses, is discussed as a solution for handling diverse data types and supporting both batch and real-time analytics. This paper aims to provide a clear understanding of how these advancements are shaping the future of data management in the financial sector.

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Submission Guidelines for the Journal of Quarterly Journal of Emerging Technologies and Innovations (QJETI) General Guidelines:

  1. Article Types: We accept a variety of article types including Original Research Articles, Review Papers, Short Reports, and Opinion Pieces.

  2. Language: Manuscripts must be written in English, and should be clear, concise, and free of jargon.

  3. Length: There is no strict word limit, but Original Research Articles should generally be between 4,000 and 10,000 words, including references.

  4. Formatting: Manuscripts should be submitted as a single Word or LaTeX document, formatted in double-spaced 12-point font.

  5. Abstract: An abstract of 250-300 words is required for all submissions, summarizing the key objectives, methods, findings, and implications of the research.

Manuscript Structure:

  • Title Page: Must include the title, author names, affiliations, and contact information for the corresponding author.

  • Introduction: Provide background, state the problem, and outline objectives.

  • Methods: Detail the methods and tools used in your research.

  • Results: Present the findings of your study.

  • Discussion: Interpret results, discuss their impact, and suggest future research directions.

  • Conclusion: Summarize the main points of the paper.

  • References: Citations should be formatted according to the IEEE/APA style.

Ethical Guidelines:

Authors must ensure that their research adheres to ethical standards and that informed consent has been obtained for any human or animal subjects involved.

Plagiarism:

The Journal of Computational Social Dynamics uses plagiarism detection software. Any manuscript found to include plagiarized content will be rejected.

Peer Review Process:

All submissions undergo a double-blind peer review process. Authors can expect initial feedback within six to eight weeks.

Submission Process:
  1. Prepare your manuscript according to the guidelines.
  2. Submit your manuscript through our online portal.
  3. After submission, you will receive a confirmation email with a manuscript ID for tracking purposes.
Revisions:

If revisions are requested, authors must resubmit the revised manuscript within the specified timeframe.

Publication Fees:

The journal has a nominal publication fee, waived for authors who lack funding. Details are available on our website.

For any questions or concerns, please contact the editorial office at editorial@vectoral.org. Thank you for considering QJETI as a venue for your research.

Published by Vectoral Publishing, the Quarterly Journal of Emerging Technologies and Innovations maintains high standards in peer-review and scientific inquiry. Authors who wish to submit manuscripts should adhere to the guidelines detailed on our website, www.vectoral.org/QJETI. Vectoral Publishing does not bear any responsibility for the accuracy of information or for any outcomes related to the use of the research published. For editorial correspondence and submissions, please reach out to editorial@vectoral.org.

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