Big Data- Down to the Tidbits

Big Data- Down to the Tidbits


Any data difficult to process or store on conventional systems of computational power and storage ability in real time is better known as Big Data. In our times the growth of data to be stored is exponential and so are its sources in terms of numbers.

Big Data has some other distinguishing features which are also popularly known as the six V’s of Big Data and they are in no particular order:

  • Variable: In order o illustrate the variable nature of Big Data we may illustrate the same through an analogy. A single item ordered from a restaurant may taste differently at different times. Variability of Big Data refers to the context as similar text may have different meanings depending on the context. This remains a long-standing challenge for algorithms to figure out and to differentiate between meanings according to context.
  • Volume: The volume of data as it grows exponentially in today’s times presents the biggest hurdle faced by traditional means of systems for processing as well as storage. This growth remains very high and is usually measured in petabytes or thousands of terabytes.
  • Velocity: The data generated in real time by logs, sensors is sensitive towards time and is being generated at high rates. These need to be worked upon in real time so that decisions may be made as and when necessary. In order to illustrate we may cite instances where particular credit card transactions are assessed in real time and decided accordingly. The banking industry is able to better understand consumer patterns and make safer more informed choices on transactions with the help of Big Data.

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  • Volatile: Another factor to keep in mind while dealing with Big Data is how long the particular data remains valid and is useful enough to be stored. This is borne out by necessity of data importance. A practical example might be like a bank might feel that particular data is not useful on the credibility of a particular holder of credit cards. It is imperative that business is not lost while trying to avoid poor business propositions.
  • Variety: The variety of data makes reference to the varied sources of data and whether it is structured or not. Data might come from a variety of formats such as Videos, Images, XML files or Logs. It is difficult to analyze as well as store unstructured data in traditional systems of computing.

Most of the major organizations that are found in the various parts of the world are now on the lookout to manage, store and process their Big Data in more economical and feasible platforms so that effective analysis and decision-making may be made.

Big Data Hadoop from Apache is the current market leader and allows for a smooth transition. However with the rise of Big Data, there has been a marked increase in the demand for trained professionals in this area who have the ability to develop applications on Big Data Hadoop or create new data architectures. The distributed model of storage and processing as pursued by Hadoop gives it a greater advantage over conventional database management systems.