Exploring TM1 - a Chartertech Company
Search
Close this search box.

Enabling TM1 Rules via a Control Cube

A simple solution to enabling and disabling rules for different versions (or scenarios) using either an attribute on the Version dimension or a simple cube, intersecting the }Cube and Version dimensions.

Setting Dimension Order for a TM1 Cube

Dimension order within cubes in TM1 is important not only for performance, but also for usability. When should you set the order for usability and when for performance? And how do you optimise the dimension order for performance? All these questions and more are addressed in this post from ExploringTM1.

Setting the Java Virtual Machine (JVM) in Cognos

There are a few settings in Cognos BI that can dramatically improve performance in Cognos BI when using TM1 as a data source. The first of these is to stop Cognos from using the old Bluenose method of querying TM1 and force it to use the native TM1 engine. The next setting that we need […]

Tuning Cognos BI and TM1 for Maximum Performance

Cognos Business Intelligence and TM1 now work well together, however performance can be dramatically improved by changing the out of the box settings. These tuning changes are not difficult and can significantly enhance both the speed and usability of both tools. How can BI and TM1 be Integrated When used together we can use Framework […]

Forcing Cognos BI to Use Native TM1 Engine

There are a few settings in Cognos BI that can dramatically improve performance in Cognos BI when using TM1 as a data source. The first of these is to stop Cognos from using the old Bluenose method of querying TM1 and force it to use the native TM1 engine. Bluenose is the default and it […]

Multi Threaded Queries (MTQ)

Multi-threaded queries allow TM1 to automatically load balance the application of cores by executing each query on a separate core. This multiple processing can improve efficiency and processing time for large queries and rules.

Guest Post: Solving a TM1 Performance Problem – Wim Gielis

One of our major customers was facing severe performance problems. The problems related to 2 cubes, in which we wanted to execute a rather tricky elimination. Please follow along while we discuss the cube architecture. We have an allocation cube with the following dimensions: Financial code (10 n elements) Year (2008, 2009, 2010, 2011, 2012) […]