Category Archives: Uncategorized

Amplify Data Analytics with the Lighthouse Data Analytics model – Part 2 – CoE’s key functions

Part 2 of the Lighthouse Analytics Model, this post covers the Key Functions of the Data Analytics CoE. This is a rather short summary post, no need to spell out the details , rather highlight the key functions. The Data … Continue reading

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Amplify Data Analytics – Decentralise and embed into the business

Intro Data is the new water for today’s organisations. It is essential for their survival and growth, as it nourishes every aspect of their operations and strategy. It needs to flow to all users enabling them in making informed decisions … Continue reading

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Relative Period Modelling Part 2 – SSAS Multidimensional & ZERO MDX!

My second post of the Relative Period Modelling – detailing how to use the Relative Period database design in a SSAS (SQL Server Analysis Services) multidimensional cube. Remove the need to write a SINGLE MDX code for relative periods! Note, this … Continue reading

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Relative Period modelling for multiple platforms

There are a lot of write-ups on relative periods, and different methods exist for a variety of tools. Interestingly each platform requires special handling, e.g. COGNOS Transformer & TM1 handles relative periods differently to SSAS multidimensional, and again differently to … Continue reading

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COGNOS Cube reports–slow performance

This week, I took on optimising a cube report which I had authored recently. This was a not too complex burst report working off an SSAS 2008 cube. The report was taking around 1 minute per burst, with around 500 … Continue reading

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COGNOS 10 Upgrade from 8.3

Currently in the process of performing a COGNOS BI upgrade from 8.3 to 10.1. Instead of performing a big bang approach upgrade on the existing server, have deployed a new server, and performed a clean install of 10.1. Setup the … Continue reading

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About me

My name is Dharmesh Kalyan, and I am Data Professional loving all things Data and Business Intelligence. Have been working with Data for a number of years from small analytical databases to large scale Data Lakes and Data warehouses supporting … Continue reading

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