Semantic Layers – A Critical Component of the DV2 Solution

If you or your business users are expecting to derive true value from a data analytic solution of any kind that solution must be built from both the business perspective and the business understanding of how data flows through the various business processes. In short it means that you must build from the Semantic Layer. In a Data Vault 2.0 implementation this semantic layer is critical to  your success it lies at the very core of the Data Vault 2.0 methodology. This is why we say “Data Vault is has been and always will be about the Business!”

A properly designed DV2 solution starts with the understanding of the business terms and their related business processes. This allows the practitioner to gain insight to the way data flows through the business in and through any number of enterprise source systems . This is what DV2 calls  an “integrated view” of the data. This also how semantic layers operate and interact they align complex data with familiar business terms in the form of a map. The map links the semantic layer to the business terms to provide a consolidated and unified view of the complex organizational data into familiar business terms.

Innovations on Data Vault 2.0

The versatility of a properly designed Data Vault 2.0 solution lends itself to a myriad of innovations in applied sciences engineering frameworks and analytic solutions. In this track we will explore a number of innovations and applications that are based upon or are perfectly supported by a Data Vault 2.0 approach. Among the topics we will discuss are: how to build an operational or application source system on top of a DV2 and the business benefits of doing so why Data Vault Methodology fills in the gaps of a Data Mesh conceptual framework to become its perfect complement “How To’s” and Lessons Learned of implementing on various technical platforms and the symbiotic relationship that can be nurtured between AI / ML / NLP and your Data Vault solution.

Business Analytics and Getting Data OUT of Your Data Vault Solution

Technical and data engineering teams seem to be focused on getting data IN to the Enterprise Data Warehouse but what about getting data OUT of the warehouse? These sessions are focused on the tasks approaches and teaming practices designed to get information out of the warehouse and into the hands of the business consumers. We will discuss the importance of collaboration with the business the business analysts and the data scientists required to bring true value to the business and transform your data warehouse from a being cost center to a profit center.