Product Content Management - PowerPoint PPT Presentation

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Product Content Management

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The process of data normalization involves reducing data to its canonical form i.e. standard form of expressing all the data available. Often, especially in software security, malicious input can be entered that could make the whole database vulnerable. This issue can be mitigated with normalized input that ensures that encoding is eliminated and input data is converted into a common character set. One can be totally assured that the online interfaces like Questudio’s Online Catalog Software - WebCat is made free of any sort of malicious activity. The database organization that inherently takes place because of data normalization also allows reduction of redundant data. This becomes vital for services like Product Information Management, omni-channel publishing, product content management etc. – PowerPoint PPT presentation

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Title: Product Content Management


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Product Content Management A solution to
manage your data efficiently
2
Product Content Management - A solution to manage
your data efficiently
The process of data normalization involves
reducing data to its canonical form i.e. standard
form of expressing all the data available. Often,
especially in software security, malicious input
can be entered that could make the whole database
vulnerable. This issue can be mitigated with
normalized input that ensures that encoding is
eliminated and input data is converted into a
common character set. One can be totally assured
that the online interfaces like Questudios
Online Catalog Software - WebCat is made free of
any sort of malicious activity. The database
organization that inherently takes place because
of data normalization also allows reduction of
redundant data. This becomes vital for services
like Product Information Management, omni-channel
publishing, product content management etc. More
often than not organizations can find themselves
entrapped in the data mire and data search
becomes an equally monstrous task. Data
normalization poses to solve many of such data
involving problems.
3
  • Data Management
  • Normalization gives rise to smaller tables with
    smaller rows, thus accommodating more rows per
    page. This in turn leads to use of less physical
    space and cache leading to more efficient
    systems. Data integrity is yet another advantage
    of normalized data as there is no redundant and
    neglected data. This helps in gaining the
    confidence of the omni-channel customer as same
    data is reflected across all the channels that he
    cruises.
  • 2. Search and Sort
  • The database tables get narrower after
    normalization which speeds up searching, sorting
    and creating indexes. This is crucial for
    functioning of PIM software dealing with volumes
    of data and for any sort of search query. Index
    searching gets faster as index is short also
    leading to effectual sorting of data. More often
    than not an omni-channel customer likes to weigh
    all his options before making his final choice.
    With paucity of customer browsing time it is
    logical to provide him with all his alternatives
    in the shortest possible time. Questudios
    omni-channel Publishing makes sure that the
    customer can make an informed choice in less time.

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3. Physical Space Physical placement of organized
and reduced data becomes more structured. Disk
space reduces considerably. This in turn helps in
reducing the costs involved in creation and
management of disk space. Product Information
Management hence becomes a cost effective
procedure. 4. Data Modification With
normalization, better control of data can be
achieved as databases becomes more compact.
Faster updates in terms of adding, deleting and
editing data can be done. Catalog Creation
Software implements this principle of allowing
quick addition or deletion of products according
to the organizations instantaneous decisions and
market conditions. The probability of errors
reduce considerably as multiple copies do not
exist. Multiple users can modify data at
different instances and at different locations
without the fear of incongruent data being
entered. Concurrent resolution of data happens
automatically with data normalization in place.
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