What is a Fact table (and why you need them)

In the context of a data warehouse, a fact table represents a business process/event and contains the measures and metrics you want to analyze for that business process/event. There are three types of facts corresponding to three kinds of business events. A Fact doesn’t exist in isolation. It is related to a set of Dimensions….

What is Dimensional Modeling (introduction)

Dimensional modeling is a data modeling technique used to model the presentation layer of a data warehouse. It focuses on delivering simplicity and query performance for the end user. It allows users to easily understand and navigate the data available for reporting and ad hoc analysis. A dimensional model supports high-performance aggregated queries and performs…

What is a Data Warehouse (and why you need one)

A Data Warehouse is a database that supports enterprise reporting and analysis. A well-designed data warehouse uses accepted data modelling and management techniques to provide an integrated data source that makes it easy to build reports and analyses. A data warehouse should exhibit the following four characteristics: At the heart of a data warehouse is…

Designing an Enterprise Data Warehouse – where to start?

When faced with a new Enterprise Data Warehouse development, it’s hard to know where to start. Many people make the mistake of starting with some reporting requirements. Unfortunately, this leads to narrow silos that can’t accommodate new requirements. Initially, it’s better to anchor your high-level design to the core business processes of the business. If…

How to prioritize Data Warehouse development

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…

What is a Data Warehouse Bus Matrix? (and why you need one)

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…

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What is a Semantic Layer? (and why you need one)

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…

Metadata Driven Data Warehouse (MDW) vs Traditional ETL tools

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…

We believe in the power of a Data Warehouse!

“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…

Azure Synapse Analytics- Alternative for @@ROWCOUNT or ROWCOUNT_BIG – Quick Tip

This quick tip describes how to get Row Count in Azure Synapse Analytics (formerly Azure Data Warehouse).  Azure Data Warehouse doesn’t support @@ROWCOUNT or ROWCOUNT_BIG. The link offers an alternative. This article modified that alternative to return the row count value as an OUTPUT parameter so a variable can be set to the row count value….