Big Data

Now a days many people are talking of big data,hadoop,etc.Well I thought let me enlighten what is it after all it is one of the most talked about topic by people(I mean technicians) nowadays.

1) What is big data?

Big data is high-volume, high-velocity and high-variety information asset that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. So to do so this data analysis people use software solutions such as hadoop.

2) What is big data made up of?

Well the answer is simple it is a set of 5 v’s.

  • Volume
  • Variety
  • Velocity
  • Variability
  • Veracity

These all terms together mean a large amount of data in the range of Exabyte which makes no sense to the human mind (that’s why variety), created at tremendous speed do you to many users. Veracity means the accuracy of the data can’t be authenticated.

3) Data analytics in big data

Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include different types such as structured/unstructured and streaming/batch, and different sizes from terabytes to zettabytes. Analyzing big data allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or unusable. Using advanced analytics techniques such as text analytics, machine learning, predictive analytics, data mining, statistics, and natural language processing.

4) What is to be gained from this?

Big data provides business insights beyond traditional data from transactional systems. These insights offer valuable perspectives on human behavior, sentiments, interactions, and utility usage trends from a business-to-consumer model, insights into contracts, compliance, legal and financial trends from a business-to-business perspective.

5) Why is it still a growing bubble (Problems faced)?

Adoption of big data is slower than expected in traditional enterprises. Executives lack an understanding of (and thus sponsorship of) big data, which also brings processing complexities that create additional stress on IT teams (in terms of maintenance) and business teams (in terms of adoption and usage). In these times of tight budgets, IT teams simply do not have the necessary bandwidth to implement yet another new system or technology. Big data analytics company projects are complex to plan and execute. The complexity stems from your need to perform data discovery before you can document a single user requirement. If you lack clear business requirements, you cannot plan the remaining project logistics, including team, skills, execution steps, rollout, and training.

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