Power BI: high-performance data modeling

Introduction

What this guide covers

A comprehensive analysis of in-memory relational database design, VertiPaq engine optimization, dimensional topologies, and advanced context formulation in DAX for enterprise architectures.

Overview

Topics covered

• Introduction
• Power BI: Analytical Data Modeling
• The VertiPaq Engine: Physiological Storage Architecture
• Memory Engine Compression Algorithms
• 2.1 Value encoding (value-based encoding)
• 2.2 Dictionary Encoding (Dictionary Encoding / Hash Encoding)

Related concepts

Main connections

• Relational joins & entity integrity
• Data granularity & row semantics
• SQL & relational data modeling
• Supervised machine learning
• Mean & expected value
• Data types & schema specification

Compatible notation

Mathematical sample in LaTeX

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