The Big Data

Big Data basically refers to a collection of data from multiple sources. These sources are characterised by volume, variety and velocity (the 3Vs).

Big Data can also be defined as (too) large or complex data sets that cannot be conveniently dealt with by the traditional data-processing application software. Greater statistical power can be obtained from data with many fields while on the other hand, there’s a higher possibility of obtaining false discovery from a more complex data.

Examples of Big data include transaction processing systems, documents, medical records, customer databases, social networks as well as Internet clicks clickstream logs.

The 6 Vs of Big Data

We have three types of big data namely structured data, unstructured data and semi-structured data.

• Structured data:  this type of data can be processed, accessed, and stored in a fixed format. It is the most straightforward data to work with while handling big data. Its coordination involves measurements which are usually described by setting parameters.
• Unstructured data involves the arrangement of data with unfamiliar structures such as audio files, image files, and log files.  All these files are incorporated under unstructured data.
• Semi-structured data: this involves data that contain both structured and unstructured formats. These types of data may contain essential information but are not arranged under a specific database.

The importance of big data

• Big Data provides better customer insight which can be used by companies to refine their advertisements to boost engagement rates.
• Helps companies in improving operations and customer service.
• Brings a more insightful market intelligence to companies
• Companies that adopt big data are highly competitive, have smarter targeting and receive better recommendations

BY Mollie Atieno