Conversations with Data Warehouse Experts – Mark Tabladillo

ByMike Rabinovici Updated onNovember 1, 2023

Mark Tabladillo - Lead Data Scientist at Microsoft — Mark Tabladillo

In this episode, it is my pleasure to speak with Mark Tabladillo, Lead Data Scientist for Microsoft Services — Data and Artificial Intelligence (Chief Technology Office). He works as part of a global team with Fortune 500 companies, global leading institutions, and high-tech startups toward digital transformation using advanced analytics. Mark is passionate about educating senior executives and leaders about the best ways to integrate advanced analytics into strategic business initiatives.

Mike Rabinovici

Data Warehouse

What is a Star Schema (and why it’s important)

ByAdam Gilmore July 19, 2024July 23, 2024

A Star Schema is a data modelling technique used to model the presentation layer of a Data Warehouse. It refers to the way Facts and Dimensions in the model are related. A Star Schema is organized around a central fact table that is related to its Dimension tables using foreign keys in the Fact table….

Data Warehouse

Dimension Tables – An Introduction

ByAdam Gilmore May 3, 2024July 29, 2024

A Dimension table is one of the 3 key elements of dimensional modelling used to build a Data Warehouse. This article will give you an in-depth understanding of various Dimension table concepts. What is a Dimension Table? Conceptually, Dimension tables are database tables modelled to represent the business entities involved in business processes and events….

Data Warehouse

Slowly Changing Dimension

ByAdam Gilmore June 26, 2024July 22, 2024

What exactly are Slowly Changing Dimensions, and why should you care about them? Many people find themselves asking this question. The term “Slowly Changing Dimension” is kind of odd. I mean, aren’t all Dimensions changing? And why does the speed at which the change matter? Never fear; this article will answer your questions about Slowly…

Data Warehouse | Persistent Staging Layer

Why you need a Persistent Layer in your Data Warehouse – Top 5 Reasons

ByAdam Gilmore July 24, 2018November 1, 2023

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…

Data Warehouse

Star Schema vs Snowflake Schema

ByAdam Gilmore July 18, 2024July 23, 2024

The Star and Snowflake schemas are two types of Dimensional modelling techniques used in Data Warehousing to organize and structure data for efficient querying and analysis. How do Star and Snowflake schemas differ, and which do we recommend? Read on to find out. Overview Below is the model for a Sales Fact Star Schema vs….

Data Warehouse | Persistent Staging Layer

What is a Persistent Layer?

ByAdam Gilmore July 20, 2018November 1, 2023

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…

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