1. Designing Complex Tabular Models
Bob Duffy
Database Architect

2. Speaker - Bob Duffy 20 years in database sector, 250+ projects
Senior Consultant with Microsoft
One of about 25 MCA for SQL Server globally (aka SQL Ranger)
SQL MCM on SQL 2005 and 2008
SQL Server MVP 2009+
SSAS Maestro
Database Architect at Prodata SQL Centre of Excellence

3. Thanks to our platinum sponsors :
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PASS SQL Saturday – Holland

4. Thanks to our silver and gold sponsors :
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PASS SQL Saturday – Holland

5. What we will cover What is difficult in tabular models ?
Introducing the SCOM Data Warehouse
Modelling Components
Managed Entities (Parent Child)
Groups (Many to Many Versioned Parent Child)
Discovery (Versioned XML EAV Pattern)
Real Time Processing

6. What is Complex for Tabular Models
Highly relational Data Source
Many to Many
Parent Child
Versioned Fact Tables
Semi Additive Measures
Pivoted Data or XML
Analytical Dimensons
Real Time Processing
Clean Star Schema
Simple Joins
Basic Calculations (SUM/AVG)
Full Processing
Basic Analytics

7. The SCOM Data Warehouse Model
Managed Entities
Rule
Performance
Alert
State
Discovery
Source:

8. Managed Entities and Hierarchies
How Many Computers do I have ?
How Many SQL Databases do I have ?
Computer
CPU 1-n
DISK 1-n
SQL Instance
SQL Database
SQL DB Engine
SQL Agent
SQL Job
File Group
SQL Data File
SQL Log File
Computer

9. What did we learn about P/C
Perfectly “do-able” in tabular
Needs to be flattened
TSQL Naturalization best for recalc performance
Use of Path functions best for agility
Ragged Hierarchies possible
Dax approaches gets too complex
HideMemberIIF not supported and can crash

10. Many to Many (P/C Versioned)
How many SQL 2005 Databases are there?
How many Servers does Bob manage ?

11. Lessons on M2M Lots of work on optimising them from SQLBI
We used helper “measures” to simplify
Roll on SQL 2016 with native support
Versioning and Parent-Child do-able with DAX
Performance better than expected
See

12. Performance of M2M

13. Discovery (EAV XML Design Pattern)
Classes in SCOM have custom “tables” in OLTP
100s of tables created dynamically on demand
The data warehouse converts all these into XML
Think hybrid of Entity Attribute View and XML

14. Lessons Learned on Discovery Attributes
Dimensional design is better for “fixed” schema
Performance on lots of attributes not great
Improvements with separating numeric values
Attributes “can” be in facts instead of dimensions
We need to promote into columns to slice on attribute
Leaving as measures is more flexible version wise
LENE Needs Date AND Time in one column

15. Performance Counter Expressions

16. Semi Additive Measures with LENE

17. Real Time Processing How to Process large model every 15 mins?
Need ProcessAdd & Change Tracking
No Updates or deletes allowed to tables

18. ProcessAdd Mechanism TSQL Query locates last watermark in DWH
DAX Query locates last watermark in cube
Stored Procure retrieves only new data

19. Almost Real Time Processing

20. Thank You Special Thanks to: Carmel for rubber ducking
Esteban for Processing Framework
Michael for early prototyping
Alberto for helping review the model
SQLBI for their
Advanced DAX course
DAX Formatter / Studio input
DAX Patterns

21. Please review the event and sessions
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PASS SQL Saturday – Holland