Big Data Technologies - Machine Learning Online Course - SimpliDistance

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Distance MBA

• SimpliDistance

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Why Care for Big Data Distance MBA in AI and ML
- SimpliDistance

• We live in the connected world where more than
  3.7 billion humans are connected to internet. We
  use many digital gadgets daily. Communicate with
  our friends and the world by posting messages,
  likes, forwards on Facebook, twitter, through
  emails, mobile apps like Whatsapp and so on.
  Millennial are recording every event of their
  life using photos and videos of what food they
  are eating, which movie they are watching, on
  which airport they are waiting for the flight
  etc.

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• What we are doing is generating humongous amount
  of data with our interactions.  Internet search
  engines are inseparable part of our daily life.
  Google processes 3.5 billion searches a day!

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• Why should we care about this? The challenges to
  handle such large amount of data seem to be very
  daunting. Does it even makes sense to attempt to
  embark on such an arduous task? Let us assume
  that we are interested in knowing how a
  particular disease is spreading across a country.
  This as it can cause epidemic. We are interested
  in this because we can take some action to
  prevent the outburst. As a part of the solution,
  one may try to communicate with all the hospitals
  and private medical practitioners to get some
  head start on the information. With this data,
  aid can be provided to crisis hit areas. However,
  this would be a huge effort and would also be
  time consuming.

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• Another way to look at this issue is with the
  help of search engines. Observe which search
  queries are related to the disease or medicines
  are being seen on the search engine. How many of
  them are as recent as one week or 15 days.
  Analysis of such data would be very useful in
  tracking how such disease is spreading. This will
  be very quick, almost real time. Hence it makes
  lot of sense to process such data.

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3 Vs of Big Data

• Let us see what characteristics the data need to
  satisfy so that it can be called as big data.  At
  start, typically three qualities volume, velocity
  and variety, popularly called as 3 Vs, were used
  to qualify anything as big data.

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Volume

• Very large volume is the first characteristics of
  big data. Here are some sample statistics about
  number of users which produce large volume of
  data everyday using comments, posts, photos,
  videos, likes etc on different platforms on
  social media. Here are examples of large volumes.
• Facebook 2000 million users.
• Google 111 million users.
• Instagram 1000 million users. etc.

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Velocity

• Velocity refers to the speed with which data is
  generated from human interactions with social
  media, mobile apps, websites etc.
• It is very peculiar characteristics of big data.
  One should be able to handle this velocity to get
  insights and use it for the competitive
  advantage.

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Variety

• Variety refers to different types of data. We
  generate different types of data like text files,
  PDFs, excel sheets, emails, photos, databases,
  videos  and data generated by sensors,. This
  includes structured data like database records
  and unstructured data like comments, likes etc.
  The unstructured data cannot retrieved using
  structured Query Language (SQL). Hence, a
  different type of databases known as NO-SQL
  databases are used to handle such data. MongoDB,
  CouchDB are example of such databases.

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Veracity, Validity, Volatility

• Dictionary meaning of word Veracity is
  conformity to facts or accuracy. In data
  processing the bigger challenge in cleanliness of
  the data. As data is gathered from multiple
  sources, chances of getting lot of noise or bad
  data are very high. If you use this so called
  dirty data without cleaning it, predictions and
  analysis would not be useful or may be sometimes
  grossly wrong.  Accuracy or cleanliness of data
  refers to Veracity. Along with veracity, validity
  of data in the context is also equally important.

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• Volatility refers to how long the data would be
  valid in the business context. For example,
  comments of Facebook about a movie being released
  recently may not have longer impact. User
  sentiments may keep on changing every week.
  Processing the data quickly and taking corrective
  actions faster is required.

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Volume

• It makes sense to process this big data only if
  it has value. Extracting value becomes difficult
  due to velocity and volatility.
• Big Data Technologies are designed to handle
  these challenges. Tools used in Hadoop
  eco-systems like Map Reduce, PIG, HIVE, HBase,
  Sqoop, Spark, Storm etc. are popular for big data
  processing. 

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• There are NO-SQL database like MongoDB are also
  used. Distance MBA in AI and Machine Learning
  Online Course would cover some of these
  technologies along with analytics. After
  completion of the distance MBA program, in a data
  science job role, you would use technologies and
  overcome these challenges.

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Conclusion

• SimpliDistance helps to visitors in career
  mapping personalized guidance experience with
  the use of technology suggest suitable courses
  to upgrade their knowledge/skills to grow in
  their career.
• SimpliDistance is the best Distance Learning
  Portal in India.

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Thank You