BI-TAGS

# du -a /var | sort -n -r | head -n 10

find /path/to/dir/ -printf '%s %p\n'| sort -nr | head -10 find . -printf '%s %p\n'| sort -nr | head -10

GL_JE_BATCHES (je_batch_id)                                   => GL_JE_HEADERS (je_batch_id) GL_JE_HEADERS (je_header_id)                                  => GL_JE_LINES (je_header_id) GL_JE_LINES (je_header_id,  je_line_num)                      => GL_IMPORT_REFERENCES (je_header_id, je_line_num) GL_IMPORT_REFERENCES (gl_sl_link_table, gl_sl_link_id)        => XLA_AE_LINES (gl_sl_link_table, gl_sl_link_id) XLA_AE_LINES (application_id, ae_header_id)                   => XLA_AE_HEADERS (application_id, ae_header_id)  XLA_AE_HEADERS (application_id, event_id)                     => XLA_EVENTS (application_id, event_id)    XLA_EVENTS (application_id, entity_id)                        => XLA.XLA_TRANSACTION_ENTITIES (application_id, entity_id) 

The source_id_int_1 column of xla.xla_transaction_entities stores the primary_id value for the transactions. You can join the xla.xla_transaction_entities table with the corresponding transactions table for obtaining additional information of the transaction. For e.g you join the xla.xla_transaction_entities table with ra_customer_trx_all for obtaining receivables transactions information or with mtl_material_transactions table for obtaining material transactions information. The entity_id mappings can be obtained from the XLA_ENTITY_ID_MAPPINGS table

Next, open VMWare and select Create a new virtual machine Select “I will install the operating system later” Make your OS selection about the OS that’s currently on the vmdk you will be using. (The guest OS, not the host OS). Later on, you will have the option to use an existing vmdk image as your virtual hard drive. Do so. You should now be able to finish setup and boot your converted disk image.

The best practice in business intelligence delivery is always to build a data warehouse.

Pure transactional reporting is problematic. There are, of course, the usual performance issues. Equally troublesome is the difficulty in distilling a physical model down to a format that is easy for business users to understand. Dimensional models are typically the way business users envision their business: simple, inclusive structures for each entity. The standard OLTP data model that takes two of the four walls in the conference room to display will never make sense to your average business user.