|
.: .:
.:
.:
|
|
|
.: .:
.:
.:
.:
.:
.:
|
|
|
|
Data Processing Solutions
Data Processing revolves around the data flow within the organization and how it moves between the inventory
(storage) points to the applications, processes and people that require it. Both in the front-end where data
ideally is converted into Information as well as the back-end where data is being manipulated for administrative
purposes like back-ups, archiving, etc. Typical solutions in the Data Processing area are:
- Data Migration solutions
-
This solution revolves around moving data from one type of storage, application or environment to
another and is multidirectional in nature. It does not make presumptions on the nature, type or age of
data. Just the fact that the data is moving (migrating) from one environment to another.
- Data Archiving solutions
-
This is a form of data migration, but it is one-directional. Data Archiving takes into account the
age of the data and its diminishing importance and chance of becoming information over time. This implies
that over time the need for immediate access decreases and the allowable recovery time increases. This allows
for storing the data on cheaper and typically slower media. A Data Archiving solution also assumes that data is
stored in a tiered environment. The process of moving data from Higher Tiered Storage to lower/cheaper Tiered
storage is considered archiving.
- Data Reduction solutions
-
Refers to the process of cleaning data of duplicate, excess, redundant and un-allowed data and thereby reducing
the amount of data and the resources it uses. Typical applications in this area use technologies like Single
Instance storage and Data Deduplication. File and e-mail assessment tools
for un-allowed types of data as defined by company policies (e.g. MP3’s) are also very popular methods to reduce the data set.
- Data Disposal solutions
-
Refers to the process of getting rid of data when it is no longer required, needed or desired to be around or, in other words,
when data needs to disappear. Compliance regulation requires keeping data for a certain period of time, but keeping data longer
than required can actually work against the interest of the organization.
- Data Virtualization solutions
-
Refers to emulating data sets, applications and sometimes whole environments. Typical solutions revolve around virtualizing
servers where multiple server platforms are being reduced to one and the server functions are being taken over by so-called
virtual servers and, to the client, it still looks as if multiple servers were available.
- Data Transition solutions
-
These solutions refer to the process of data being converted from one state of type to another. This also encompasses
the more abstract function of data being converted into information, but this is something only the actual recipient determines
and we don't go into detail on when the data is being considered information or not. Solutions in this category revolve around
the nature of certain datasets and its specific requirements for processing like E-Mail, OLTP, Multi-Threading, etc.
For additional information or for a customer tailored solution please contact Zibiz Data Management today: 631-738-1100 or you
can also contact us about Data Processing Solutions
by filling out our contactform.
|
|
|
|
|
