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Gartner points out the importance of a semantic layer in their report “How to Use Semantics to Drive the Business Value of Your Data”: The semantic layer provides business users with an easy way to understand the data. What exactly is a semantic layer? A semantic layer is a business abstraction derived from the technical implementation layer – a model layer that uniformly maintains business logic, hierarchies, calculations, etc. This frees business users from concerns about the technical complexity and implementation of the underlying data source. A data consumer (no matter his/her data literacy) needs to be able to easily discover, understand, and utilize the data. What is missing between the business user and the data warehouse?Ī great solution to this problem of data management is a semantic layer. Technical metadata such as table name, column name, and data type are often meaningless to business users, and so data warehouses aren’t sufficient on their own to enable businesses to carry out data analysis. If enterprises carry out their data management initiatives without first addressing these issues, they end up wrestling with data silos.Įvery data warehouse practitioner understands how challenging the data in the warehouse is for business users to understand.
Enterprise bi tools full#
There are no unified data and business definitions, which makes it difficult for enterprises to effectively take advantage of the full value of their data assets. One major challenge is that many valuable enterprise data assets are isolated in local servers, data centers, and cloud services. However, this unprecedented data volume and distribution has created many challenges when it comes to enterprise data management. Data is at the cornerstone of every business decision today, and an increasing number of enterprises are using technologies such as data lake and cloud computing for their digital transformation.