What are the different
forms of data entry?
Product catalog to web
data entry:
Transforming printed
catalogs into online
catalogs. Converting
all the relevant data
and digitize all the
images and upload to
your desired location.
Online cataloguing
makes it easy to
search for products
and updating is also
made easier.
PDF document indexing:
Lot of data is lost
because of the
unavailability of
readers of old format
data, specially
microfilms and its
variants. Converting
document, microfilm,
microfiche or image
format data into PDF
documents. Conversions
like this require a
lot of attention to
details.
There are many image
formats that can be
changed into PDF
including.
PAPER to PDF
TIFF to PDF
MICROFICHE to PDF
MICROFILM to PDF
GIF to PDF
Online data capture:
Collecting data
from online sources
and then converting it
accordingly to one's
specifications. This
include:-
Gathering data from
different websites and
entering it into an
excel spreadsheet.
Searching the web and
creating all the lists
of targeted websites.
Gathering precise and
updated information
about competitors’
pricing.
Other Customize
requirements related
to above.
Data Warehouse:
A data warehouse is
a repository of an
organization's
electronically stored
data. Data warehouses
are designed to
facilitate reporting
and analysis.
However, the means to
retrieve and analyze
data, to extract,
transform and load
data, and to manage
the data dictionary
are also considered
essential components
of a data warehousing
system. Many
references to data
warehousing use this
broader context. Thus,
an expanded definition
for data warehousing
includes business
intelligence tools,
tools to extract,
transform, and load
data into the
repository, and tools
to manage and retrieve
metadata.
Data Mining:
It is the process
of sorting through
large amounts of data
and picking out
relevant information.
It is usually used by
business intelligence
organizations, and
financial analysts,
but is increasingly
being used in the
sciences to extract
information from the
enormous data sets
generated by modern
experimental and
observational methods.
It has been described
as "the nontrivial
extraction of
implicit, previously
unknown, and
potentially useful
information from data"
and "the science of
extracting useful
information from large
data sets or
databases." Data
mining in relation to
enterprise resource
planning is the
statistical and
logical analysis of
large sets of
transaction data,
looking for patterns
that can aid decision
making.
Data cleansing:
It is the act of
detecting and
correcting (or
removing) corrupt or
inaccurate records
from a record set,
table, or database.
Used mainly in
databases, the term
refers to identifying
incomplete, incorrect,
inaccurate, irrelevant
etc. parts of the data
and then replacing,
modifying or deleting
this dirty data.
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