One which creates canonical models, provides data stewardship & governance and ultimately a kick-ass consumption layer for analytics.

Another way to look at it, according to Donna Burbank, Managing Director at Global Data Strategy: People used to (and occasionally still do) build a new enterprise data model that’s comprised of every field and value in their existing enterprise, across all silos, and then map every silo to this new model in a new data warehouse via ETL jobs. The Curated Zone in a data lake contains curated data that is often stored in a data model, which combines like data from a variety of sources (often referred to as a canonical model). My favorite one is the idea of establishing canonical data model (CDM) for all of your interfaces.
Data model emphasizes on what data is needed and how it should be organized instead of what operations need to be performed on the data. The Canonical Data Model is the heart of the warehouse and ideally contains a single, normalized, fully integrated and enterprise-wide representation of all the data in the warehouse – though those of us familiar with data warehousing know that this is rarely the case in reality. The Canonical Data Model (CDM) is a data model that covers all data from connecting systems and/or partners. Canonical Data Model: A canonical data model (CDM) is a type of data model that presents data entities and relationships in the simplest possible form. The “modeling” of these various systems and processes often involves the use of diagrams, symbols, and textual references to represent the way the data flows through a software application or the Data Architecture within an enterprise. Common Data Model is influenced by data schemas that are present in Dynamics 365, covering a range of business areas. Finally, there is the mapping of the different data model elements (along with the associated physical artifacts) to the business terms in the business vocabulary. In some cases, depending on the data model tooling used, it may also be possible to create mappings between these reverse engineered physical models and the canonical logical models. A data lake is a system or repository of data stored in its natural/raw format, usually object blobs or files. Expand your knowledge of how to properly build a #hadoop or #NoSQL data lake. Semantic data model (SDM) is a high-level semantics-based database description and structuring formalism (database model) for databases. 2 IBM Models and the overall data lake landscape This chapter briefly describes the main component areas of the data lake and describes the most likely associated integration points that IBM Industry Models would have with the data lake. This does not mean the CDM is just a merge of all the data models. Data Modeling refers to the practice of documenting software and business system design. The Business Data Lake is not simply a technology move.

Canonical data models are a type of data model that aims to present data entities and relationships in the simplest possible form in order to integrate processes across various systems and databases. The way the data is modelled will be different from the connected data models, but still the CDM is able to contain all the data from the connecting data models. In traditional DWH architecture, we must first understand the data, model it and then load it in. OverviewData virtualization uses a simple three-step process—connect, combine, consume—to deliver a holistic view of enterprise information to business users across all of the underlying source systems. It is generally used in system/database integration processes where data is exchanged between different systems, regardless of the technology used. The Canonical Data Model is the heart of the warehouse and ideally contains a single, normalized, fully integrated and enterprise-wide representation of all the data in the warehouse – though those of us familiar with data warehousing know that this is rarely the case in reality. If you are a customer or a partner using Dynamics 365, you are already using Common Data Model. Semantic data model (SDM) is a high-level semantics-based database description and structuring formalism (database model) for databases. They address such areas as when and when not to use models for defining data lake repositories, the different data model development lifecycles associated with data lakes and the different normalization approaches across the data lake. Common Data Model in action.

It does this within a single environment – the Business Data Lake. In the meantime, explore how the IBM Watson Data Platform can form the foundation for your enterprise data lake. This Zone may be used to feed an external data warehouse or serve as the organization’s data warehouse. In a data lake architecture, we load data first in raw for and decide what should we do with it.