Lakehouse Architecture and the Semantic Revolution: Bridging Analytics and Governance with AI
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V3I3P114Keywords:
Lakehouse Architecture, Semantic Layer, Data Governance, AI in Analytics, Unified Data Platform, Data Mesh, Data Lake, Data Warehouse, Business Intelligence, Metadata Management, Data Lineage, ML-Driven GovernanceAbstract
In the present day's digital world, businesses are moving beyond the limits of traditional data warehouses and lakes and using data lakehouse architecture, which is more flexible and more scalable. This hybrid architecture combines the reliability of data warehouses with the flexibility & low price of the data lakes to provide a single platform that makes analytics easier and makes data more accessible. But as data grows in size and complexity, merely having good storage isn't enough. The semantic layer is a strong abstraction that makes it possible for all data consumers to have the same business-oriented definitions. This makes sure that data is easy to find, understand, trust & use again. The semantic layer makes raw data relevant and links the technological information infrastructure to these strategic decisions. When you add AI to this bridge, it becomes wiser. AI makes it easy to automate things like keeping track of information, watching provenance, identifying more abnormalities, and making their own findings. This improves data governance and makes predictive and prescriptive analytics possible. A convincing case study shows how a big company uses lakehouse architecture, together with a strong semantic layer and AI, to speed up time-to-insight, data compliance, and communication across more departments by a lot. This change not only improved their technology foundation, but it also changed how their company thought about data-driven innovation. The combination of lakehouse frameworks, semantic intelligence, and AI marks the beginning of the latest way of doing business analytics: one that is well-organized, more smart & planned to be that way. This convergence not only solves problems that already exist, but it also gives us a chance to rethink how data supports business at all levels. Not only will we need to save information in the future, but we will also need to understand it, manage it ethically & use it wisely to get the all actual outcomes.
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