Big Data
is the very essential part in business field because it is the only technology
that utilizes all kinds of data. Big Data analytics will help to have
clear vision over the solution for any problem, it could be used to have
different solutions for different perceptions of a problem. Big data has high
potential to decode the essentials of any sector, it is especially used to
upgrade the customer experience in business sector. The methods of big data is
disciplinary, interesting, reliable and highly classified.
It deals
with the data that is in big size so hence, Big data. It contains the process
of gathering data from various different platforms, analyzing the gathered data
and to taming down the big storms of it into solution. The methods of
gathering, analyzing and evaluating happens in a very sophisticated manner of
steps.
As the
India's very own IT-hub, pursuing a Big Data Analytics course in Bangalore will
be beneficial in many technical ways.
Let me
start with the BD’s organised way of dealing with all of our data. [ Data in
here refers every kind of data that happens over the internet, even a simple
search in any browser will also considered as a data ] When all kinds of data
gets gathered it will be difficult to differentiate between the useful data and
non useful data. To solve this issue, Big Data has is very specific, it
differentiates data as, Structured data, Unstructured data and semi
structured data.
1. Structured
data: Some data are obvious, static and easily fits into some category. For
example, if a electronic transaction has happened using Gpay it will
specifically fall into its location of file. Usually structured data will be very
important among all the data and it is also very easy to work with because such
data will be generated by a easily detectable source of application.
2. Unstructured
data: This data is completely unpredictable and random. Sometimes the data of
this category will be considered useless. For example, if a search topic is
misspelled then there will be no intention behind that search, such search
could not be decoded because it doesn’t has no foundation. But on the other
side of the coin, the unstructured data also conceals some unseen treasure.
Sometimes among the unstructured data there lies a pattern that will clearly
represents the expectations, needs, necessities of people. This may not happen
everytime but when it happens, it gives a big deal out of it. Hidden patterns
and correlations between the data says lot than the expected.
3. Semi
structured data: It is half of both structured and unstructured, so it contains
both static data and random data. Semi structured data can be highly useful in
many different business sectors because it mostly possesses truthful data which
could be relied upon. For example, If any college university is searched then
such data will be of semi structured data. It cannot be decided whether the
user has searched the topic to lead onto it or it was a search to compare
between other topic.
Similar
type the data will be analysed in ML, some of Machine Learning courses in Bangalore.
The above
mentioned are the way how data is categorized, now let’s see what will be done
with such categorized data, how it the process of Big Data is handled. There is
a special 3 V’s in Big Data: Volume, Velocity, Variety. In
meantime, another V is added to it, which is Veracity.
Volume: Volume
determines the size of the data. Did you know the fact that every day 2.5
Quintilian data is generated? In which I, You have also contributed,
because if you are reading my content then you must be reading it by any
electronic device with the facility of internet connection, even this will be
contributed to the total number of generating data. Handling such number of
data is nearly impossible and irritable only for one day, to handle it for
everyday is a task of its own. Big Data has the powerful Data base platform
which apparently is handling every data generated data.
Velocity: Big
Data Velocity deals with the pace at which data flows in from sources like
business processes, machines, networks and human interaction with things like
social media sites, mobile devices, etc. The flow of data is massive and
continuous. This real-time data can help researchers and businesses make
valuable decisions that provide strategic competitive advantages.
Variety: Variety
refers to the many sources and types of data both structured and unstructured.
We used to store data from sources like spreadsheets and databases. Now data
comes in the form of emails, photos, videos, monitoring devices, PDFs, audio,
etc. This variety of unstructured data creates problems for storage, mining and
analyzing data.
Veracity: Big
Data Veracity refers to the biases, noise and abnormality in data. Is the
data that is being stored, and mined meaningful to the problem being analyzed.
Inderpal feel veracity in data analysis is the biggest challenge when compares
to things like volume and velocity. In scoping out your big data strategy you
need to have your team and partners work to help keep your data clean and
processes to keep ‘dirty data’ from accumulating in your systems.
Upon the
information of such different types and category of data, Big Data specialists
uses languages like Apache Hadoop, Cassandra, etc, to find a valuable
information out of all these data.
Big Data
is interesting, organised, classified and big. If you think you would fit into
the field of Big Data then help yourself by registering in Learnbay. It is an institute that provides Big Data
analytics training in Bangalore and Machine Learning courses in Bangalore.
Learnbay is recommended because it do gives good coaching
upon the subject, after the completion of the course the students will be
certified by IBM, which will weigh as high recommendation during the
placements.
