anchor.diff:  * <<Analyze Data Access, Data Access>>
   * <<Analyze Data Size, Data Size>>
   * <<Analyze Data Validation, Data Validation>>
  -* <<Analyze Data Actuality and Correctness, Data Actuality and Correctness>>
  +* <<Analyze Data Actuality and Correctness, Data Actuality and Correctness>> (which covers integrity issues as well)
   * <<Analyze Data Access Protection, Data Access Protection>>
  +* Analyze Data distribution, replication and syncing, 
   * <<Analyze Backup, Backup>>
   
   ====== Analyze Data Structures
  
positive.code: 
  [[Data-Analysis]]
  ==== [pattern]#Data-Analysis# 
  
  ===== Intent
  Analyse and inspect the data created and manipulated by the system for its content, structure, quantity and size. 
  
  ===== Description
  
  
negative.code: * Peoples' address typically changes something between 2-10 times during
  their lives.
  * Empirical studies show that between 5 and 10% of business or job email addresses
  become invalid every year.
  --
  
  * Which parts of the data are subject to (what kind of) changes?
  * Are parts of the data known to be invalid or contain invalid portions?
  * Does the System handle potentially wrong or invalid data appropriately?
  * Are there (organizational or technical) processes in place that deal with
  data inconsistencies or faults?
  
  ====== Analyze Data Access Protection
  
  * Is there an overview what kinds of data need which level of (access) protection?
  * Is there a security concept in place covering protection against unauthorized access?
  ** How are users/roles/organizations _allowed_ to access data managed?
  ** Is there a process in place to revoke access for outdated users/roles/organizations?
  * Is there a plan what shall happen in case of security breaches or data theft?
  * How is data theft recognized?
  