Big Data is defined as a collection of large datasets that cannot be analyzed with normal
statistical methods. The datasets are measured in Exabytes. There are two types of big data:
structured and unstructured.
Structured data are numbers and words that can be easily categorized and analyzed. Unstructured
data can include more complex information that cannot easily be separated into categories or
analyzed numerically. Analysis of unstructured data relies on keywords, which allow users to
filter the data.
Not all of the work on big data is automated. Data scientists and data analysts are the workers
that deal with big data. The data is so complex that the workers use software specifically
designed to analyze large, unstructured datasets.
Working with big data includes:
A secondary market for big data has been created by exchanging and sharing data that is useful
for several organizations and not just one.
Big data can be used in:
Staticians and computer programmers are so important nowadays that their median annual wage
doubles the median annual wage of all workers May 2012.
The growth of big data has provided new insights but also has presented new challenges to those
who work with it.
Here is a list of challenges:
Coursework in math, statistics and computer programming prepares students to work with big
data. Workers who use big data may also need education in the industry in which they work.
Workers have to also stay updated on the fast-changing world of big data.
Different set of skill are important to work with big data: