This article has four main sections that talk about big data and people who are dealing with it. The first section will talk about the different types of data and what is the difference between them. The second section will show who can deal with this data and how they will deal with it in different fields. The third section will clarify the challenges that workers could face when they are working with a set of data. Finally, the last section will explain how people can prepare themselves to be able to deal with big data. What is big data? It's a huge number of datasets that cannot be analyzed with normal statistical methods. This data can be numbers, videos, pictures, maps, etc. There are two kinds of data: structured and unstructured data. Structured data can be numbers and words, that data can be categorized and analyzed easily. Unstructured data has more complex information that makes it very hard to separate into categories or analyzed numerically. Working with big data Data scientists, computer programmers, and workers who are dealing with data are using some software to collect, aggregate, store, organize, and clean the data to make it easier to analyze it. Then they create graphs, charts, tables, or other tools to summarize the results. Big data by field The workers who are dealing with data have different areas in which they can work in. Here are some examples of specific kinds of big data and how workers are involved with them. Business. In general, businesses need workers to collect and analyze data by looking at purchase data and customer reviews to decide what step they should take to reach their goals. E-commerce. In this field, the data analysts will study the customer reviews, comments, and suggestions to help the company to improve their customer services. Finance. They are studying the transaction data to look for fraud and other security breaches. Government. They are collecting a lot of data about their constituents to help government serve their constituents better and improve policy decisions. Healthcare. They are recording the patient's information electronically to give him/her easier treatment. Science. Analysts collect data from the experiment data then ship them off to another lab to be analyzed. That procedure can be used for all different sciences. Social networking. Analysts are collecting the data from social networking then store these data to get more targeted advertising and better customer services. Telecommunications. They are studying the smart phones data to provide their telecommunications services to the customers. Challenges presented by big data People who work with big data will face big challenges. First, availability of funding. Second, storage; nowadays, we are trying to save all the information that we think itís useful electronically to be able to get it any time we want. Third, accurately measuring. Finally, protection and controlling the data; Most data have privacy information so analysts should share the data without violating peopleís privacy. Preparing to work with big data People who work with huge data should have experience in the relevant field or industry beside their knowledge of statistical analysis and computer system. Education and training Most analysts have a masterís or higher degree beside the bachelorís degree. Courses. Math, statistics, and computer programming prepare students to work with big data. Other training. Analysts need education in the industry, especially in highly technical industries, like physics and healthcare. Skills Communication skills. Itís very important for analysts to be able to explain their result to other workers. Teamwork. Since everyone has different skills, working together as a team will help us to get a perfect project. Curiosity.