DEV EPM

Before we glue it all together in ODI, let us organize the data that we just got from Essbase. In the last post we saw that we gathered all the information we needed inside a generic stage table. Although a generic table is great from an extract perspective, we may decide to split, organize, and load this information in some kind of “historical DW tables” which will help us to analyze the data better over time.

For this series of posts, we have 3 different kind of information: DB Statistics, File Statistics and Outline Statistics. Their structure are very different, so we will generate one historical table for each kind of statistic.

Since we created a generic table to hold all extracted information in rows, now we need to PIVOT the data into columns and load it into the historical tables. This can be easily achieved with a SQL like the one below:

First, we define the columns to be pivoted and use a consolidation function on the data column, like (SUM, AVG, MIN, MAX, COUNT…). Then we specify the data to be pivoted and this data must be a constant in the “IN” clause. Finally, this data is loaded to the DW table using a Control Append approach, since we want to keep adding the current statistics to a historical table for an analysis over time.

If we follow this approach for all three metrics that we retrieved from Essbase, we will end up with three DW tables, like the ones below:

File statistics:

Outline statistics:

DB statistics:

That is all for today! See you!

This entry was posted on February 17, 2021 at 2:12 pm and is filed under Essbase, Java, ODI with tags Essbase, Java, ODI. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.