What is Data Archiving?

In this blog, we’re looking at Data Lifecycle Management (DLM) and particularly the latter parts of data management which address data retention, data archiving and data deletion.

We are a 100% JD Edwards software house, hence the majority of what follows relates specifically to Oracle JD Edwards EnterpriseOne and World systems.

What is Data Archiving?

Data Archiving is the process of moving end of life data from your JD Edwards Production Environment into an Archive Environment. Data Archiving with Purge-it means you don’t need to set up and maintain a separate archive environment. Archive data is accessed through Purge-it archive applications.

As system users enter data into an Oracle JD Edwards ERP, then data volumes increase.  Gradually over the years and subsequent decades, the build-up of data can become significant.

We know we are adding data records to our JDE system on a regular basis but we don’t necessarily take time to consider the size of that data build-up.  The four points below illustrate what typically happens in a JD Edwards system:

1. Data is created and acquired into your JD Edwards EnterpriseOne
2. Data is modified and reported over whilst it is an active transaction
3. Data is analysed
4. Data remains in the database

Following on from point 4, ‘Data remains in the database’, the next step is usually Data Archiving and sometimes Data Purging.  Archiving and purging (if required) form a crucial part of Data Lifecycle Management (DLM).

Want to understand more about Data Lifecycle Management (DLM) and the stages of DLM?

Take a look at this useful information published by HPE.
⇓  We’ve posted some of the words from the HPE Glossary directly onto the bottom of this page  ⇓

Data Retention

There is no requirement that an organization keeps all its records and information indefinitely.  Instead, once an organisation no longer needs a record to meet operational or legal requirements, then the organization is free to dispose of that record or piece of information.

The business utility of most records diminishes rapidly after their creation and use, and commonly drops to zero within a few years.  The vast majority of legally mandated retention periods are well under 10 years.  It’s important to note that country and industry specific legislation will apply to organizations.

Data Retention Policy

A meaningful Data Retention Policy will help define the amount of data that is kept within the live JD Edwards system, the amount of data that is kept within the archive JD Edwards system and how old that data has to be before it is ultimately destroyed.

What’s the difference?

Data Archiving versus Data Back Up

"Data archives can be thought of as a data repository for data that is infrequently accessed but still readily available.  Backups, on the other hand, are part of a data recovery mechanism that can be used to restore data in the event that it is corrupted or destroyed. Backup data often consists of important information that must be restored quickly when lost or deleted." *

* Source: https://www.techtarget.com/searchdatabackup/definition/data-archiving

Data Archiving versus Data Deletion

Data archiving describes the process of moving JD Edwards E1 or World data from the JDE production system but still retaining the data.  With the Purge-it data archiving solution, this archive data is accessible via the Purge-it Archive Applications.

Data deletion addresses completely removing the archive data.  Once the data is no longer required, it is purged from the archive.

Full Data Lifecycle Management using Purge-it

Reasons to Archive or Purge (permanently remove) JD Edwards Data

• Reduce database size
• Better system performance
• Improve User Experience
• Easier system upgrades
• Help address legal compliance
• Improve disaster recovery times
• Identify open, incomplete or unprocessed transactions
• Support active data management

Hewlett Packard Enterprise has published some useful general information about Data Lifecycle Management (DLM).  Here’s some extracts from their ‘What is Data Lifecycle Management? Glossary’ *

“What is Data Lifecycle Management?”

“Data lifecycle management (DLM) is the policy-driven approach to managing data from its point of origin to its eventual deletion. Today’s enterprises generate information at a phenomenal pace—more than doubling in volume every two years. Making meaningful use of that data requires a deliberate, directed process for gathering, maintaining, protecting, and applying it. Effective DLM provides structure and organization for business information, ensuring that it supports business objectives, rather than just consuming space.”

“What are the stages of data lifecycle management?”

“…The stages of data lifecycle management may vary from one organization to another, but most will fit into the following general framework.”

Stage 1: Create and Collect 

Stage 2: Store and Manage

Stage 3: Use and Share

Stage 4: Archive 

Stage 5: Destroy

* Source: https://www.hpe.com/uk/en/what-is/data-lifecycle-management.html