SQL Data Warehouse Design Patterns
There are clear rules of modelling an OLTP relational database developed by Boyce–Codd before I was even born. However, dimensional modelling patterns are still rather vague and modellers are faced with some
tough decisions in real world of complex data relationships, tricky/absent reporting requirements and various aspects of performance and ease of use. I would like to present a set of design patterns to use when tackling common DW modelling problems and challenges: when to use star or snowflake, junk and mini dimensions, bridge tables and other data warehouse modelling tricks.
There are many books on DW terminology and general theory, so I will assume you have at least a grasp of common lingo: dimension, fact, slowly changing dimension types, star and snowflake schemas, etc.
Patterns I present aim to follow one common structure:
Problem (What?) -> Solution(How?) -> Reasons (Why?)->Consequences (Why not?)
The idea is not just presenting a common framework for sharing what works and what doesn’t, but also explain why that is the case and what happens when the patterns are not followed.
These patterns are equally applicable for a Kimball or Inmon religion, so both camps are very welcome to attend.
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Dmytro Andriychenko's Summary
I am a keen data and systems integration professional who enjoys a challenge of both technical and personal nature. I am particularly interested in projects involving novel clashes of technologies prompting unusual approaches or organisational challenges. I love performance tuning and optimising IT system infrastructures.
These are main areas of my technical expertise:
- SQL Server Development, especially Enterprise Data Warehouse and OLAP design and implementation
- Microsoft BI: complete stack of SSIS, SSAS, SSRS and SharePoint BI
- SharePoint administration, configuration and development including Kerberos configuration and troubleshooting
I also have experience of designing BI systems end to end from hardware and application tiers to systems integration, requirements engineering, database and ETL design and development. I am also keen to learn other BI technologies having had experience of Microstrategy, Business Objects, Tableau and even Open Source tech like Pentaho, MySQL, MariaDB, Cassandra etc.
Data Integration, Data Warehousing, OLAP, Data Mining, SQL Server Tuning, Systems Architecture, Data architecture, Database development, Design, Development and maintenance.
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