In the last decades of data
management and process it out there is a large number of theories and practical
experiments has been done by different authors and writers. The Big Data is a
concept of managing a large amount of data in the terms of useful data out of
the raw data. It is a most challenging factor to process and smoothly manage the
data in a large amount, therefore for this task is to be done most of the
theories are being produced. The big data is a potential and valuable standard
in the data management technologies, as it has worth for the business universe.
There is no doubt of theoretical potential of Big Data optimistically the Big
Data is becoming renowned for its space, volume limit and other factors of
processing it. During the analysis of data set it is hard to determine that what
you had gained from the data set either it is useful for industries standards or
other business use of these types of data sets. It became in experience and
practices that the Big Data emits signal waves but not the noise.
These Data Management Systems enable your company to reduce data-collection
time, increase accuracy and simplify the record retention/retrieval process.
Reporting & Maintenance Training & Maintenance Data Collection Data
Management
For the fast process of data retention and retrieval throughout the above
mechanism is a structural way that industries and organizations should follow
for accuracy and concurrent data processes.
There are 3Vs. used to characterize the Big Data.
Volume: defines the size of the data that can be into megabytes, gigabytes,
terabytes or petabytes etc.
Velocity: it comprises for grouping and integration of data from different
resources.
Variety: it involves formatting and modeling of data, mixed mode or it also can
be unformed data.
- Larger space for data storage
The space is a major issue to store the large amount of data into ware houses
and in databases, if the space is less than the data is stored so it would be
too complicated to work the data properly
- Optimized performance for data processing
When the data is being processed or it is in under operation, then it should be
optimized for fastest and reliable performance because no matter how much the
data is but the thing is that while performing any operation over the data it
should be fast applied over it then of course the data would be safe and fast.
- Accessibility of data
There is too many tools to access the data, while accessing the data if there is
chances to loss the data from a damaged resource then it should be
pre-determined for recovery and restoration of that important data for you
organization as it is a wrathful record for your company.
There are different means of data that is available on the web in different
capacities i-e social networking sites, corporate and business sectors,
industrial process and manufacturing sites has larger volume of data on the web.
There is a meaningful importance of volume, velocity, variety and complexity of
data in today’s business market, and it has been challenged in corporate and
Enterprise Application vendors as well as private firms that built around online
applications, to setup the online business requires much more space storage for
their business contents.
Volume comprises for that storage the online business holders can do that,
velocity is about the integration of contents or data from different resources
that are meaningful for the business runners, the variety of data can be differ
from each other as the data is rough and unstructured but it can be converted
into useful information and also can be utilized in different capacities,
complexity of the data is that the operations that are being performed over the
data may be difficult or hard to determine the desired results of the data over
the operations.
The most scalable challenges of big data:
There are other different challenges have been produced by different IT
scientists and researchers but some major challenges are described here as
under:
• Accuracy of data and Accurate use it
The accuracy matters in the salvage of large industries while processing and
managing the data and all other information related to the organization. The
accurate use of the data depends upon the accuracy of data set that is coming
from the different resources.
• Accessibility and Connectivity
The data should be easily reachable while accessing it from multilevel
databases, the less the data in size, there is short time to access it although
the data is in large amount or the size is increased in it takes too time to
access it. The check in balance should be properly applied before accessing the
data because of there may be some connectivity issue in the database so firstly
it should be determined that there is no connectivity issues in the database.
• Optimization & Performance
In large organizations, industries and all other business & corporate sectors
wants that the data should be reliable in the means of fast accessibility, there
is most techniques are being produced towards optimization and fast performance
of data because if the procedures that are applying on the data or datasets are
optimized then the data would be accessed accurately and through a fast process.
• Data Protection
The security of data and information is one of the biggest challenges of Big
Data, Protection of the data is best achieved through the application of a
combination of encryption, integrity protection and data loss prevention
techniques, therefore different algorithms and methods has been produced to
secure and encrypt the data i-e MD5 Hash, Ciphertext stealing, Common Scrambling
Algorithm, Crypto++, CryptGenRandom and so on.