Adopt the Logical Data Warehouse Architecture to Meet Your Modern Analytical NeedsHenry Cook
In order to maintain and improve its position, it needs fast access to unified data and the ability to quickly deliver the resulting insights to its business consumers. What role does the logical data warehouse architecture and data virtualization play in this and how does it work in practise?
Data warehouses play a crucial role in today’s data-intensive operations. However, the physical infrastructures required forBig Dataare increasingly being jettisoned in favour of more agile solutions.Logical data warehousesadd a virtual architecture layer that sits apart from traditional data services a...
James V.Luisi, inPragmatic Enterprise Architecture, 2014 4.1.5.2Logical Data Models Logical data modelsare more technical in nature and often represent the scope of the data for a particular automation effort or project. Logicaldata modelingbelongs to the logical design phase as adata engineeringstep...
4.1.5 Data Modeling Architecture The traditional view of data modeling begins with logical data modeling. Logical data modeling is a part of the SDLC for application development and was intended to minimize data redundancy with a database design process known as normalization. It should not be con...
Figure 1 DataArts Architecture On the DataArts Architecture page, choose Models > ER Modeling in the left navigation pane. On the ER Modeling page, if no ER model has been created, the system displays a dialog box asking you to create one. If you have created ER models before, click ...
to link new data sources to the virtualization layer than it would be to incorporate them into the data warehouse, which was built to take in data from Oracle systems. For example, when IU deployed a new Salesforce CRM system, the logical data warehouse architecture "helped to ...
This section discusses extending the Data Warehouse logical schema. The architecture of the logical schema is governed by the Data Warehouse meta-model. Extending the logical schema requires detailed knowledge of the meta-model. For more information, seeData Warehouse Meta-Model. ...
Solution architects for analytics, data warehouse leads and information leaders need to evolve to the logical data warehouse, to meet the current demands for flexibility in data management solutions for analytics, or face obsolescence. Included in Full Research Introduction Key Challenges Analysis Ov...
The original writeup on data mesh explores the challenges of the existing analytical data plane architecture. Figure 2: Further divide of analytical data - warehouse Figure 3: Further divide of analytical data - lake Data mesh recognizes and respects the differences between these two planes: the ...