Big data is defined as the voluminous amount of structured, unstructured or semi-structured data that has huge potential for mining but is so large that it cannot be processed using traditional database systems. Big data is characterized by its high velocity, volume and variety that requires cost effective and innovative methods for information processing to draw meaningful business insights. More than the volume of the data – it is the nature of the data that defines whether it is considered as Big Data or not.
What do the four V’s of Big Data denote?
IBM has a nice, simple explanation for the four critical features of big data:
a) Volume –Scale of data
b) Velocity –Analysis of streaming data
c) Variety – Different forms of data
d) Veracity –Uncertainty of data
How big data analysis helps businesses increase their revenue? Give example.
Big data analysis is helping businesses differentiate themselves – for example Walmart the world’s largest retailer in 2014 in terms of revenue - is using big data analytics to increase its sales through better predictive analytics, providing customized recommendations and launching new products based on customer preferences and needs. Walmart observed a significant 10% to 15% increase in online sales for $1 billion in incremental revenue. There are many more companies like Facebook, Twitter, LinkedIn, Pandora, JPMorgan Chase, Bank of America, etc. using big data analytics to boost their revenue.
Differentiate between Structured and Unstructured data.
Data which can be stored in traditional database systems in the form of rows and columns, for example the online purchase transactions can be referred to as Structured Data. Data which can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi structured data. Unorganized and raw data that cannot be categorized as semi structured or structured data is referred to as unstructured data. Facebook updates, Tweets on Twitter, Reviews, web logs, etc. are all examples of unstructured data.
What do the four V’s of Big Data denote?
IBM has a nice, simple explanation for the four critical features of big data:
a) Volume –Scale of data
b) Velocity –Analysis of streaming data
c) Variety – Different forms of data
d) Veracity –Uncertainty of data
How big data analysis helps businesses increase their revenue? Give example.
Big data analysis is helping businesses differentiate themselves – for example Walmart the world’s largest retailer in 2014 in terms of revenue - is using big data analytics to increase its sales through better predictive analytics, providing customized recommendations and launching new products based on customer preferences and needs. Walmart observed a significant 10% to 15% increase in online sales for $1 billion in incremental revenue. There are many more companies like Facebook, Twitter, LinkedIn, Pandora, JPMorgan Chase, Bank of America, etc. using big data analytics to boost their revenue.
Differentiate between Structured and Unstructured data.
Data which can be stored in traditional database systems in the form of rows and columns, for example the online purchase transactions can be referred to as Structured Data. Data which can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi structured data. Unorganized and raw data that cannot be categorized as semi structured or structured data is referred to as unstructured data. Facebook updates, Tweets on Twitter, Reviews, web logs, etc. are all examples of unstructured data.
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