This periodical provides evaluation and interpretation of the current phenomenon known as “big data”. It outlines what big data is, an overview of big data work, some of the challenges that can occur when dealing with big data, and also how to prepare for such challenges. With the recent technological advances, there has been more data recorded than ever before. As the International Year of Statistics, it is vital to understand the existence of “big data”.

Within big data, there are two main types of data, structured data and unstructured data. Structured data is data that can be easily analyzed such as Global Positioning Systems. Unstructured, however, is data that includes more complex information like comments and reviews.

There are many occupations and workers who deal with big data. Some of the occupations include:

·         Managers

·         Postsecondary teachers

·         Software developers

A large number of fields also work with “big data” quite a bit. A few of these fields include (but not limited to):

·         Business

·         Ecommerce

·         Finance

·         Government

·         Healthcare

·         Science

·         Social Networking

·         Telecommunications

·         Other (politics, utilities, appliances…)

Sometimes, data from one of these fields can be applied to that of another. Workers dealing with these types of big data try to find any usable information within data. After analyzing the data, these workers often put the data into graphs, charts, tables, or other tools to summarize the results. Often times, developing computer software programs and coding are part of the work dealing with big data. These programs are used to analyze the data. Even though these codes are complex and specific to each project, they make the analysis of big data much easier and more efficient. Workers who use big data will be in higher demand than ever before in the upcoming decade. The use of big data is spreading to many fields and occupations.

                Unfortunately, there are several problems when dealing with this new phenomenon. The funding for further examination into this field is very low due to a slow economy. Another problem associated with big data is the storage of said data. Since the data is so big, many servers must be used to store the information. Another large problem that is often run into is extracting usable data from unstructured data sets. Turning comments and reviews into usable information can often be a difficult task. Also, ownership rights as well as how to protect and control data once collected is becoming a problem. There is much controversy within the aspect of ownership and the use of data.

                There is certain preparation necessary in order to be a successful analyst working with big data. Courses that work with big data include math, statistics, and computer programming. Often times workers dealing with big data are recruited from the engineering field because of their train of thought. Another important aspect of training is hands on experience. Education in the industry in which a person works in is an important part of their latency to use big data. It is very important to keep up with the latest developments in big data.

                There are various skills which can be important for working with big data.  Problem-solving skills are important in that new developments are constantly being made. Communication skills come in handy when explaining results of an examination. Teamwork is a very useful skill because the ability to collaborate is important while working with big data. Working with team members can accomplish a lot more with more effective results. It is also very useful if the analyst is curious and intellectual. Many new developments are made in exploration as a result of curiosity.  Developing new ways to analyze big data is very important in any field.