Dedicated Semantic Layer Architecture for Effective Data Analytics and Visualization: A Case Study

Ramla Suhra1

1

Publication Date: 2024/11/18

Abstract: Organizations these days increasingly rely on fast growing data for their critical business decision making. To leverage full potential of data, petabytes of data are being ingested into central data lakes mostly powered by cloud. They also realize that it is not enough to just collect huge amounts of data. To derive value from this data, it must be cleansed, interconnected and translated from its complex technicalities into an easily interpretable and more familiar business terminology. Building a semantic view of the data enriched with business metrics enable users to query, analyze and visualize information as quickly as the business demands. While the semantic layer is perceived as the cornerstone in modern data architecture, there are different perspective towards where or how this should be implemented. Additionally, understanding the evolution of semantic layer over the years can help choose the right architecture when attempting to build one in an organization. With the advent of Artificial Intelligence (AI), it is imperative that we discuss the impact of AI on this topic. This research delves into the evolution of the need and significance of semantic layer, exploring their architecture, benefits. It also analyzes the challenges faced during semantic layer adoption and the outlook.

Keywords: Data Analytics; Artificial Intelligenc;, Data Architecture; Semantic Layer.

DOI: https://doi.org/10.38124/ijisrt/IJISRT24OCT1676

PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24OCT1676.pdf

REFERENCES

  1. J.-M. Cambot, B. Liautaud, and S. F. Sa, “US5555403A - Relational database access system using semantically dynamic objects          - Google Patents.” https://patents.google.com/patent/US5555403
  2. “Microstrategy, Inc. v. Business Objects, S.A., 661 F. Supp. 2d 548 | Casetext Search + Citator.” https://casetext.com/case/microstrategy-inc-v-business-objects-3
  3. Wikipedia contributors, “Online analytical processing,” Wikipedia, Oct. 08, 2024. https://en.wikipedia.org/wiki/Online_analytical_processing
  4. M. 2023 7 M. Read, “What is a data cube?,” 365 Data Science, May 02, 2023. https://365datascience.com/trending/data-cube/
  5. Emilien, “Business Intelligence Trends 2020,” Wiiisdom | Analytics Governance Solutions, Feb. 09, 2023. https://wiiisdom.com/ebook/business-intelligence-trends-2020/
  6. A. Kumar, “The semantic layer movement: the rise & current state,” Modern Data 101, May 02, 2024. https://moderndata101.substack.com/p/the-semantic-movement-the-story-of
  7. A. Keydunov, “Real-time AI experiences can’t advance without a universal semantic layer,” RTInsights, Mar. 03, 2024. https://www.rtinsights.com/real-time-ai-experiences-cant-advance-without-a-universal-semantic-layer/
  8. A. Schwanke, “Semantic layer — one layer to serve them all - Axel Schwanke - medium,” Medium, Aug. 29, 2024. [Online]. Available: https://medium.com/@axel.schwanke/semantic-layer-one-layer-to-serve-them-all-d0ef7eff1ffa
  9. “The Journey towards metric Standardization | Uber Blog,” Uber Blog, Jan. 12, 2021. https://www.uber.com/blog/umetric/