Dr John Tunnicliffe

John is a well-respected designer and architect of business intelligence solutions who likes nothing more than getting his hands dirty with real life coding problems.  John is an independent consultant with extensive experience of implementing Business Intelligence solutions on the Microsoft platform across a wide range of industries including financial services, retail and professional services organisations.

John designs and builds solutions based on Microsoft SQL Server / SSAS / SSRS / SSIS delivered to the end-user through Power BI dashboards.

Pulling on his systems integration skills whereby disparate components are brought together in a coherent fashion, John has become an expert in applying continuous integration techniques to data warehouse projects, thereby ensuring code is automatically built, deployed and tested as changes are made by the development team. John is also a regular speaker at the SQLBits conference and SQL Saturday events.

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John will introduce you to Analysis Services 2008, demonstrate browsing cubes with Excel 2007, deploying dashboards in SharePoint built using Excel Services and demonstrate how PerformancePoint Services can add the glitz to your BI project.
This session will present the tools and techniques used to create OLAP cubes and supporting data marts on-the-fly from a mere set of data files and configuration metadata.
Users love flexible analytics but hate to wait for the data to be loaded into a traditional data warehouse. John will describe how to build an infrastructure to support real-time loading of your OLAP cubes so your user's get exactly what they want
Processing of SSAS OLAP databases can be a tricky business, particularly when it comes to incremental processing of dimensions. John will give you real life examples of why certain approaches work and others do not.
Data warehouse designers often ignore the specific needs of an OLAP database. In this session, John will outline the best ways to optimise your relational database to support your multidimensional OLAP cubes
Continuous Integration is not normally associated with data warehouse projects due to the perceived complexity of implementation. John will be showing how modern tools make it simple to apply Continuous Integration techniques to data warehouse projects

Blog posts RSS

Microsoft deliver on their promises, handsomely! 18 Dec 2015
At the SQL PASS Summit in October, James Phillips made a promise that everything he talked about or demonstrated in his keynote would be available by the end of the year.  Well they have delivered, handsomely!  Today SQL Server 2016 CTP3.2 has been made available which delivers mobile ...

Continuous Integration and the Data Warehouse 01 Dec 2015
I am excited to say that over the next two weekends I am speaking at PASS SQL Saturday events in Southampton and Slovenia on Continuous Integration and the Data Warehouse.  Over the coming weeks I hope to provide some supporting posts outlining exactly how to set up CI in the data warehouse ...

Supercharge your SSDT database projects using T4 to auto-generate T-SQL code! 08 Jul 2015
There are many techniques that data warehouse developers could learn from other parts of the software industry and automated code generation is one of them. Most database developers have at some point in their careers written T-SQL code to query the SQL Server catalog views to automate the ...

Dynamic Partition Creation in SSAS multidimensional using the SSAS Partition Manager 28 May 2015
<<Updated blog entry to reflect the new release of SSAS Partition Manager>> There are plenty of blog entries out there that outline how to dynamically create partitions in SSAS multidimensional databases. However, all of them suffer the same drawback: they always hard-code some part of ...

SSAS Partition Manager for both SSAS Tabular Models and SSAS Multidimensional Cubes 26 May 2015
Today I am proud to announce the release of SSAS Partition Manager that can dynamically create partitions in both SSAS Tabular models and SSAS Multidimensional cubes using a wide variety of partitioning schemes (yearly, monthly, weekly etc.).   What is more, for OLAP cubes it correctly ...