Главная
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1
Introduction
2
Prerequisites
3
Main Problem
4
Agenda
5
Best Practices
6
Customer Cube Example
7
Enterprise Features
8
Compression Settings
9
Demo
10
Cluster Compression
11
Row Compression
12
Questions
13
Partitioning
14
Physical Partitioning
15
Demo Physical Partitioning
16
Incremental Processing
17
QA
18
Multiple file groups
19
Disable compression
20
File groups
21
Creating cube partitions
22
Compression limitations
23
Bridge dimension
24
Slides scripts
25
Thank you
26
Outro
Description:
Explore strategies for optimizing data warehouse processing time in this 58-minute conference talk from PASS Data Community Summit. Learn how to leverage Analysis Services features and database engine capabilities to significantly improve OLAP processing performance. Discover best practices, enterprise-level features, and practical techniques such as compression settings, partitioning, and incremental processing. Gain insights from real-world examples, demonstrations, and expert advice on aligning SSAS and database engine features to achieve up to 200% improvement in processing time for large-scale data warehouses.

Optimizing Your Data Warehouse for OLAP Processing

PASS Data Community Summit
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