Big Data Analytics — What Do We Know?

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Big Data Analytics What Do We Know?
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• Big Data is the very essential part in business
  field because it is the only technology that
  utilizes all kinds of data.
• BD( 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.

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• Big Data 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.
• Similar to Big Data Analytics, Data Science
  certification is also a very trending course of
  the decade, you may check for the course at the
  end of article.

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• Let me start with the BDs 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.

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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 doesnt has no foundation.
• But on the other side of the coin, the
  unstructured data also conceals some unseen
  treasure.

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• Sometimes among the unstructured data there lies
  a pattern that will clearly represents the
  expectations, needs, necessities of people.
• This may not happen every time but when it
  happens, it gives a big deal out of it.
• Hidden patterns and correlations between the data
  says lot than the expected.

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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.

• The above mentioned are the way how data is
  categorized, now lets see what will be done with
  such categorized data, how it the process of Big
  Data is handled.
• You can learn all this methods through a good Big
  Data Analytics training in Bangalore, details is
  given at the end of the blog. 

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• There is a special 3 Vs 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.

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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.

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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.

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• 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.
• Learnbay is one of the helpful institutes of Data
  Science certification and Big Data Analytics
  training in Bangalore for affordable and helpful
  price schemes.
• Learnbay teaming up with IBM is striving to flash
  the opportunity of effective and easily
  affordable courses to the technical aspirants.

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Thank you

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