anchor.diff:  ====== Analyze Data Actuality and Correctness
   Especially in data concerning dynamic entities like people, organizations,
   markets, commodities etc., facts are very likely to change over time.
  -Such data might become invalid sooner or later. Other types of information
  -(like tax records, invoices or bookings on bank accounts) are created once and remain
  -intact forever).
  +Such data (_stored facts_) might become invalid sooner or later. 
  +Other types of information (like tax records, invoices or bookings on bank accounts) are created once and remain valid forever).
   
   
   [TIP]
  
positive.code: ====== Analyze Data Size
  
  * Are some parts of the data especially large?
  * Does the relation between record-size (_how large is a single record_?)
  and record-volume (_how many records exists_?) plausible?
  
  
  ====== Analyze Data Validation
  
  
negative.code: * Data Validation
  * Data Size
  * Data Actuality and Correctness
  * Data Access Protection
  * Backup
  
  ====== Analyze Data Structures
  Are data structures suited to represent the problem domain?
  