Dylan's BI Study Notes

My notes about Business Intelligence, Data Warehousing, OLAP, and Master Data Management

Semantic Layer for Data Scientist

Posted by Dylan Wan on June 16, 2022

I recently read a good buyer’s guide from AtScale: The Buyer’s Guide to the Best Semantic Layer Tools for Data and Analytics. I think the buyer’s guide is fair not because that the company I worked for also has such semantic layer, but I really feel that the drawback of the vendor specific semantic layer has a unnecessary vendor lock-in and the design is not customer-oriented.

How about a semantic layer that can be queryable from the SQL?

How about using the commonly available JDBC driver, such as postgreSQL driver?

I think that these two should be criteria for evaluating the semantic layer from the BI vendors, as we should not think that one company only has one BI tool. There are mixed of old and new and there are alternated solutions used by different departments.

This paper clearly said that the semantic layer from those visualization tools have the problems in interoperation. These tools should be the consumer of the semantic layer, not the source.

Another very good point from this paper is that it mentioned the need of data scientists. I found that a new category of tool called “feature store”. However, what those tools said are really old BI requirements of semantic layer built for the ad hoc query. Can the semantic layer provided satisfying the needs? I think that with a set of additional features, the semantic layer from the unified data analytic platform should be the best solution.

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