Attempting to deliver your Data Warehouse in a single iteration, “waterfall” style, would be very difficult. Today’s agile development process demands that the tasks be broken down into smaller iterative phases that incrementally deliver value. This means you need to prioritize your Data Warehouse development. In the case of a Data Warehouse, the business value…
A “Data Warehouse Bus Matrix” describes the high-level design of a Data Warehouse. At a glance, it shows all the facts and dimensions of a data warehouse and their relationships in a table-like ‘matrix’. It’s useful as a tool to design, plan, estimate and communicate your data warehouse. The “Data Warehouse Matrix” comes from the…
What is a Semantic Layer A semantic layer exists to present data to users as a set of related and commonly understood business entities, terms and metrics. A semantic layer is typically the “top” layer of a data warehouse/lakehouse. It is accessible to end users and report developers, who use it as the source for…
Here at Dimodelo Solutions, we are passionate about data warehouses and the benefits they can bring an organisation. But we are equally passionate about the art and practice (the how) of building these critical information assets. This is why we developed our Metadata Driven Data Warehouse tool “Dimodelo Data Warehouse Studio” (formally Dimodelo Architect). What…
“The report of my death has been grossly exaggerated.” – Mark Twain. Have you heard “The Data Warehouse is dead”? This claim appears from time to time, usually accompanied by the latest next big thing in Data processing (Self Service BI, Big Data, Data Virtualization etc). However, what these claims fail to understand is a…
This post is the second in a series of detailed cases studies discussing the ETL strategies that can be used when a Persistent staging layer is included in your Data Warehouse. It’s intended as a reference for developers using Dimodelo Data Warehouse Studio, our Data Warehouse Automation tool to quickly build a Data Warehouse. It’s most…
Why you Need a Persistent Layer 1. All history, all of the time, instead of some history some of the time Including a persistent layer in your architecture is a paradigm shift in how you see the data warehouse. In the popular Kimball methodology, without the persistent layer, the data warehouse layer was responsible for…
The persistent layer contains as set of persistent tables that record the full history of changes to the data of the table/query that is the source of the Persistent table. The source could a source table/file, a source query, another staging table or a view/materialized view in the transform layer. In a persistent table there…
This post is the first in a series of detailed cases studies discussing the ETL strategies that can be used when a Persistent staging layer is included in your Data Warehouse. It’s intended as a reference for developers using Dimodelo Data Warehouse Studio, our Data Warehouse Automation tool to quickly build a Data Warehouse. It’s…
In this episode, I had the pleasure of speaking with Chris Webb, a well respected independent consultant based in the UK. He specialises in Analysis Services, MDX, Power Pivot, DAX, Power Query and Power BI in general. He is a widely read blogger having authored more than a 1000 posts over the last 10 years. …
