There are a ton of reasons to convert a planning load file to an Essbase load file.  Maybe you are migrating a file from one environment to another, or simple want to load the file faster, but there are reasons to use the Essbase format. Read more


I don’t normally write up monthly updated, but this month there are a number of intriguing changes/updates/enhancements that are important to know.  Some may change existing processes.  This is not an exhaustive list, but these are things I think all of us should take note of. Read more


No, But Can It Solve Yours?

I received a lot of positive feedback on the Groovy Series and have been asked a many great questions.  People are excited about the improvements but are still a little hesitant to buy in to the hype.  They question, and rightfully so,  Read more



When moving data in PBCS with Data Maps or Smart Pushes, they have limits on how much data can be moved.  The amount of data can be seen in the logs, and look something like this. Read more



With the introduction of Groovy Calculations this summer, one of the things I use most, especially for applications with data forms that include a large sparse dimension in the rows with suppression on, is the option to loop through cells and identify only the POV on the cells that have changed.  Read more


What Is Groovy

Recently, Groovy scripting was added to ePBCS business rules as an option instead of the GUI, or the go-to scripting for you old-timers who still refuse to change.  These are defined in the Business Rule editor as Groovy calculations.  So, what is Groovy? Read more


The generic rule in Essbase is that calculations FIX on sparse members because sparse members are what define the number of blocks.  When you want to limit the members of the block on which the calculation is executed, an IF statement is appropriate. Read more


The introduction of Hyperion 11.1.2 has some fantastic improvements.  Many of these have been long awaited.  The next few articles on In2Hyperion will describe some of the enhancements to Hyperion Planning, Hyperion Essbase, and Hyperion SmartView.

XREF Background

If you have been developing Planning applications, you are probably very familiar with the XREF function.  This function is used in business rules, calculation scripts, and member formulas.  It provides a method to move data from one plan type (Essbase database) to another plan type.  It is executed from the target database and pulls the data from the source.  XWRITE was actually introduced in later versions of 11.1.1.x, but is very stable in 11.1.2.x.  XWRITE is executed from the source and pushes data to the target.  This function is a huge improvement over XREF.  Read more


There are times when planning and forecasting databases grow for apparently no reason at all. The static data (YTD actuals) that is loaded hasn’t changed and the users say they aren’t doing anything different.

If you load budgets or forecasts to Essbase, you probably do what I’m about to tell you. If you are a systems administrator and have never seen how finance does a budget or forecast, this might be an education.

The culprit? Read more


The format of the data that is loaded to Essbase is often an after-thought.  But, should it be?  When requesting the data file from a source system, it is more important than you may think to have it sorted to mirror your outline.

Assume an outline has the following dimensions.

  • Period [DENSE]
  • Account [DENSE]
  • Region [SPARSE]
  • Category [SPARSE]
  • Product [SPARSE]
  • Organization [SPARSE]

The most efficient way to receive a data file would be to have it sorted by Organization, Product, Category, Region, and then Account.  Data files load faster when the columns that hold the sparse members are sorted in reverse order of the sparse dimensions that exist in the outline.

The reason the data loads faster is because it opens a block of data only one time.  If the data was sorted by the dense members first, then every block would have to be opened multiple times.  If the same sparse member combinations have 3,000 dense members with data, the block would be opened up to 3,000 times.

There are some more important benefits of doing this, however.  When the block is opened multiple times, the database becomes far more fragmented than it needs to be.   Fragmentation causes calculations to be slower and retrieving data can also be impacted, which can lead to frustrated customers.

By not sorting the data when loaded, every time a data load occurs, any performance issues that may exist are exacerbated.  So, anytime possible, sort the data load files by the last sparse dimension in the outline, the second to last sparse dimension in the outline, and so on.  You may be presently surprised at the benefits.