Working with Big Data

By: Roman Mural

Big data is normally defined as an assortment of large datasets that cannot be evaluated with normal statistical methods.
When determining the correct employee to exploit the “big data” sensation, there are four variables to consider in someone.
An employee must understand the background of big data, how to work with it, how to face the challenges within it, and have
the appropriate training and skills.

Big data can be broken down into two categories, structured and unstructured data. Structured data can be easily arranged
and examined such as numbers and words. Unstructured data is more intricate information, for example comments on social media
or customer reviews. When working with this amount of big data, The U.S. Bureau of Labor statistics (BLS) classifies the workers
as statisticians, computer programmers, or in other occupations. However, whatever their title, they study big data both conventional
and newly developed statistical methods. The workers plan methods of storing and organizing the huge amount data to create graphs,
charts, tables, or other tools to summarize the results. Each of these data analysts’ job tasks differ, depending on which area of
the big data they work in. Some examples of specific types of big data that workers find themselves working in are business, E-commerce,
finance,government, social networking, and healthcare.

As technology continues to grow, the growth of big data has provided new challenges when working with it. Due to the rapid
progression of the data, workers must understand how to overcome each task. A problem one might face is the accessibility of
funding. If the funding is unavailable than they could miss out on receiving big data analysis software, improved computing equipment,
or hiring new data analysts. Another issue when dealing with big data is its storage. The amount of data can need hundreds of
servers to process all the information needed for an association. When having the sufficient amount of storage, finding usable
data among the enormous amount of information is another task. Lastly, a related challenge that occurs is protecting and
controlling the big data. Controversy is a likely occurrence about how data can be used or shared without violating people’s privacy.
The workers are responsible for planning methods of keeping big data secure.

No worker would be the suitable candidate to exploit big data without having the appropriate training and skills. When working
with big data, it can require knowledge of statistical analysis and computer systems, and experience in the relevant field or
industry. As well as having a bachelor’s degree, most analysts have master or higher degrees in common specialties. Along with having
the training, problem-solving skills are critical when working with big data. Teamwork, curiosity, and communication skills are all
viable when being creative thinkers and problem-solvers.

In conclusion, working with big data is a complex process. A worker must understand and carry out all four variables to exploit
big data. If the analyst can do so, they will be an appropriate applicant to be hired for the job.