Posts by agoddard
Understanding Picklists in IBM Planning Analytics
Picklists are not a new concept. They exist in many applications, including Web pages. Perhaps you know them as “selection lists” or “drop down lists”. As a refresher, a picklist is a list of valid values for a specific element or cube cell. When you define a picklist for an element or a cell, a…
Read MoreUsing Default Views in IBM Planning Analytics
IBM defines a cube as “…the basic container for data…” and a cube view as “…the definition of how a cube’s dimensions are arranged…”. Planning Analytics cubes can each have multiple views defined and typically, each cube will have specific views designed to assist with common reporting needs. Common Views In addition to defining various…
Read MoreUsing the Modeling Workbench in Planning Analytics
The modeling workbench was introduced in IBM Planning Analytics and remains available as a beta feature (in 2.0.65). You can now open the modeling workbench from the Planning Analytics Workspace environment (in earlier versions entry was through a separate URL). You can use the workbench to do almost anything you need to do within a…
Read MoreUsing Custom Themes in IBM Planning Analytics Workspace
Did you know that you can override the standard Planning Analytics Workspace (PAW) theme with your own “custom theme” that reflects your corporate branding or culture? You can use a custom theme to: Modify the colors of the application bar Modify the colors of the navigation bar Set the corporate title that is shown on the home…
Read MoreUsing MDX to Create a Dynamic Cube View
IBM Planning Analytics (PA) subsets can be made dynamic by using multi-dimensional expressions (MDX). Doing so allows for automation and will ensure that subsets update if the dimension changes. MDX allows for many different use cases such as filtering by attributes, levels or using a wildcard search to display all elements that meet a specific…
Read MoreManaging Multiple ODBC Credentials in IBM Planning Analytics Workspace
TurboIntegrator (TI) processes in IBM Planning Analytics (PA) allow connections to various data. One option is an ODBC connection, which stands for Open Database Connectivity. This is an extremely reliable method that directly connects to an external relational database and allows you to extract data through a query. This article explains how ODBC username and…
Read MoreMaintaining Hierarchies in PAW
Planning Analytics Workspace (PAW) comes with the feature to create multiple hierarchies in one dimension. These hierarchies are generally created by the attributes of the dimension. Once a hierarchy is created, it is detached from the attribute values. Therefore, a developer should create a TI (TurboIntegrator) process to maintain the hierarchies which are built based…
Read MoreCollecting Data for Earnings Reports in IBM Planning Analytics
An earnings call is one of the most important meetings between the management team of a public company and its external stakeholders. The company prepares internal and external reports like an annual business disclosure report (10-K) every quarter. The typical timeframe for collecting data and producing the earnings-related documents is less than 60 days. That…
Read MoreIntegrating Snowflake and IBM Planning Analytics
In another post I explored how easy it is to access cloud-based Snowflake, create a database, define and then load a table with data from a local file. In this post, I investigate the steps required to integrate some Snowflake data with IBM Planning Analytics (TM1). The steps will include: Configure an ODBC Data source…
Read MoreTroubleshooting PAW Security
PAW (Planning Analytics Workspace) has four types of security: User Role, User Group, Folder Security, and Book Security. These security types are separated from the database security, such as cube security, element security and process security. A PAW administrator usually helps a user fix security issue in PAW. This article covers the common security issues…
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