Book Image

Getting Started with Oracle Hyperion Planning 11

By : Enti Sandeep Reddy
Book Image

Getting Started with Oracle Hyperion Planning 11

By: Enti Sandeep Reddy

Overview of this book

<p>Oracle Hyperion Planning is one of the many products in the Oracle Enterprise Performance Management software suite, an industry-leading Business Intelligence software package. The primary focus of the Hyperion Planning product is to provide a planning, budgeting, and forecasting solution that helps you manage and coordinate all your business planning and budgeting needs.</p> <p>This book is a practical guide to implementing a Hyperion Planning solution in your organization, which addresses all your planning, budgeting, and forecasting needs.</p> <p>You will begin with the installation of Hyperion Planning and then design Planning applications as per some example user requirements. You will then learn to create the planning objects. The book moves on to explaining important concepts within Hyperion Planning such as data forms, task lists, business rules, validation rules, and workflows, with the help of many real-world examples to maximize your learning. Towards the end of the book, you will cover user provisioning and access rights and budget process management.</p>
Table of Contents (23 chapters)
Getting Started with Oracle Hyperion Planning 11
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Performance Settings


These are the settings to improve the performance of overall Planning application. There are two sections.

The following are Essbase concepts and hence we are not going into the detail about them.

  • Dense and Sparse: Defining a dimension as dense or sparse has a huge impact on the performance.

  • Order of dimensions: Even the order of dimension in an outline plays an important role in an application's performance. We'll learn what is recommended and how to change the order.

Dense and Sparse

Dense dimensions are the ones which have maximum probability of occurrence in the combinations of dimensions. Generally, Accounts and Period dimensions are dense in nature. Coming to the sparse dimensions, they have lesser probability of occurrence, the examples would be Entity and Custom dimensions. The correct combination of dense and sparse dimensions would give best performance.

What performance are we talking about?

The dense – sparse combination determines the data block size and this data...