Data processing is the transformation of raw data into meaningful output. Data can be done manually using a pen and paper, mechanically using simple devices e.g. typewriter or electronically using modern data processing tool set computers. It follows some step that are
1)Data collection
It involves getting the data/facts needed for processing from the point of its origin to the computer. Data collection is the first step in data processing. Data is pulled from available sources, including data lakes and data warehouses.
2)Data Preparation
Once
the data is collected, it then enters the data preparation stage. Data preparation, often referred
to as “preprocessing” is the stage at which raw data is cleaned up and
organized for the following stage of data processing. During preparation, raw
data is diligently checked for any errors. The purpose of this step is to
eliminate bad data ( redundant , incomplete, or incorrect data) and begin to create
high-quality data for the best business intelligence.
3)Data Input
The collected data is converted into machine-readable
form by an input device, and send into the machine.
4)Processing
It is
the transformation of the input data to a more meaningful form
(information) in the CPU.During this stage
Processing is done using machine learning algorithms, though the process itself
may vary slightly depending on the source of data being processed (data lakes,
social networks, connected devices etc.) .
5)Data
Output/Interpretation
Output
is the result of the required information, which may
be input in future it is translated, readable, and often in the form of
graphs, videos, images, plain text, etc.).
6)Data
Storage
The
final stage of data processing is storage . After all of the data is processed, it is then stored
for future use. While some information may be put to use immediately, much of
it will serve a purpose later on.
What is ISRS (information storage and retrieval system)?
An
information storage and retrieval system (ISRS) is a network with a built-in
user interface that facilitates the creation, searching, and modification of
stored data. An ISRS is typically a peer-to-peer (P2P) network operated and
maintained by private individuals or independent organizations, but accessible
to the general public. Some, but not all, ISRSs can be accessed from the
Internet. (The largest ISRS in the world is the Internet itself.)
Characteristics of an ISRS
include lack of centralization, graceful degradation. The lack of
centralization helps to ensure that catastrophic data loss does not occur because
of hardware or program failure, or because of the activities of malicious
hackers. Graceful degradation is provided by redundancy of data and programming
among multiple computers. The physical and electronic diversity of an ISRS,
along with the existence of multiple operating platforms, enhances robustness,
flexibility, and adaptability.
A significant difference
between an ISRS and a database management system (DBMS) is the fact that an
ISRS is intended for general public use, while a DBMS is likely to be
proprietary, with access privileges restricted to authorized entities. In
addition, an ISRS, having no centralized management, is less well-organized
than a DBMS
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