• Post Graduate Program in Analytics and Artificial Intelligence
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  • Data Science Prodegree
    Co-created with KPMG in India
    4.8 out of 5 by 6071 learners
    16 X industry demand

Big data is the next big wave that is shaping the corporate sector today. Big data gives an idea about the size of data but there are various aspects associated with it. It is also driven by various other factors apart from the size of data such as the sources of data, various formats in which it is available, chunking and extraction, etc.

Big data has managed to find space in all sectors of the market – technology, retail, telecommunications or any other broadly recognized field. It makes use of the available data to derive conclusions.

Need for Big Data

Organizations have huge data resources in an unstructured format. Mostly this data is stored in various devices and is never brought to any use. Data can prove to be a mega resource for the growth of any company as it can equip the company with numerous insights thus acting as the steering wheel of the company. Traditional tools such as Excel are not that efficient in extracting information and putting it to any relevant use. Big data comes into the picture here.

When you have a huge amount of data, it needs to be sorted and then classified under various heads so that the important fields can be easily recognized and brought to use. This space is getting bigger with every passing minute as we are becoming more and more data-oriented.

The volume of data is huge. With the increase in the number of internet users, more data and information are coming into circulation and this has given rise to the value data holds today. This data is produced through various channels like search engines, social media networks, business informatics, etc. It makes use of various tools to summarize information.

Learning Big Data and Hadoop can pave a great career path for someone who wants to have a career in data analytics.

Characteristics of Big Data

 The 4 Vs of Big Data characterize big data. Data needs to be classified and organized for better understanding. The 4 Vs of Big Data are:

  1. Volume
  2. Velocity
  3. Variety
  4. Veracity

These characteristics form the essence of Big Data. It gives insights on how the data should be dealt with and how can the insights from that data can be put to good use.

  1. Volume: Volume defines the size of the data which in today’s time is exploding and increasing exponentially. To be precise, this defines the quantity of data available for the extraction of information. Based on the volume of data, various tools are applied for the segregation of information.
  2. Velocity: Velocity refers to the speed in which the data is processed. The speed of data processing plays a very important role in Big data as a lot of data has to be analyzed and insights have to be drawn within a stipulated time frame, thus making the velocity of data an important feature of Big Data.
  3. Variety: Variety refers to the various types of data from which the relevant information has to be extracted. It is important as data collected from different sources are diverse in many aspects. Big Data makes use of various tools to integrate the diversified data and draw insights for the business.
  4. Veracity: Veracity refers to data accuracy and its relevance with the business information we require or the business decision that has to be made. Veracity helps in the identification of relevant information and hence saves a lot of time.

Conclusion

Big Data today has various dimensions and has opened a new world for data harvesting and extraction. With the help of the Big Data Analytics course, one could gain expertise and in-depth insight into the field.

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Imarticus Learning is India’s leading professional education institute that offers training in Financial Services, Data Analytics & Technology. We’ve successfully transformed careers of over 35,000+ individuals globally through our Certification, Prodegree, and Post Graduate programs offered in association with leading and renowned global organisations in the Financial Services, Data Analytics & Technology domain.
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