Databases Reference
In-Depth Information
Collect
Process
Capturing
transaction data
Collection of data
from subsystems
Data collection
on forms and
portals
Manage
Classify
Tr ansform
Sort / Merge
Calculations
Summarize
Generate
Storage
Retrieval
Archival
Governance
Advanced
Compute
Format
Present
FIGURE 3.1
Data processing cycles.
Data processing techniques
There are two fundamental styles of data processing that have been accepted as de-facto standards:
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Centralized processing
. In this architecture all the data is collected to a single centralized storage
area and processed upon completion by a single computer with often very large architectures in
terms of memory, processor, and storage.
●
Centralized processing architectures evolved with transaction processing and are well suited
for small organizations with one location of service.
●
Centralized processing requires minimal resources both from people and system perspectives.
●
Centralized processing is very successful when the collection and consumption of data occurs
at the same location.
●
Distributed processing
. In this architecture data and its processing are distributed across
geographies or data centers, and processing of data is localized with the federation of the results
into a centralized storage. Distributed architectures evolved to overcome the limitations of the
centralized processing, where all the data needed to be collected to one central location and results
were available in one central location. There are several architectures of distributed processing:
●
Client-server
. In this architecture the client does all the data collection and presentation, while
the server does the processing and management of data. This was the most popular form of
data management in the 1980s, and this architecture is still in use across small and midsize
businesses.
●
Three-tier architecture
. With client-server architecture the client machines needed to be
connected to a sever machine, thus mandating finite states and introducing latencies and
overhead in terms of data to be carried between clients and servers. To increase processing
efficiency and reduce redundancy while increasing reusability, client-server architecture
evolved into three-tier systems, where the client's processing logic was moved to a middle tier
of services, thereby freeing the client from having to be tethered to the server. This evolution
