Tech Topic

  The tech topic that was most interesting to me was IT careers. After researching this topic further there were two careers that stood out and piqued my interest. These careers were Systems Analyst and Data Scientist. Systems analysts look at design components and use their knowledge of information technology to solve business problems, whereas a data scientist analyzes and organizes data that can influence a business's decisions. Researching these careers will allow me to see if they are a fit for me to pursue as a future career. 

System analysts specialize in analyzing and designing information systems that meet the needs of businesses or organizations. This topic connects to the fundamentals of information technology and literacy because system analysts use many different components of computers when doing their jobs. Some things that they have to do are analyze business requirements, design and develop systems, test and debug systems, provide user support, maintain systems, and keep up to date with current and future technology. The article states that “Systems analysts work closely with business stakeholders to identify the organization's needs and requirements for information systems. They gather information about the business processes, data, and technology systems used in the organization to determine how technology can be used to improve efficiency and effectiveness”(CareerExplorer). The quote helps to show what system analysts do to help businesses and organizations. Systems analysts will often work in teams when developing systems and working through problems. This means that not only do people need to have experience with technology, but they also need to be collaborative and work as a team. Another example from the article is, “Systems analysts may find themselves working in diverse environments, including corporate offices, government agencies, healthcare institutions, financial organizations, or technology companies”(CareerExplorer). This helps to give an idea of the different areas system analysts might work. Another option for this is remote work which can allow for a more flexible work arrangement and it can allow for collaboration with other teams and clients from different locations. 

Data scientists analyze a business or organization's data to gain insight into how their sales will go up or down. They then use this data during meetings with stakeholders to make business recommendations. Data scientists create algorithms and models for machine learning. They then use machine learning to find and categorize data or to make predictions based on the data. These algorithms need to be continuously tested for accuracy so that when new data is collected, it works correctly. The article states that “Data scientists often use data visualization software to present their findings as charts, maps, and other graphics. Visualization techniques allow data scientists to clearly communicate their analyses to technical and non-technical audiences, including colleagues, managers, and clients”(U.S. Bureau of Labor Statistics). This allows data scientists to clearly show what their data suggests and discuss recommendations that are made for the betterment of the business. Data scientists use many different programming languages to analyze and manage large data. These include Python, R, SQL, and SAS. The data visualization programs that they use are Tableau, PowerBI, and Excel. The article states that “Some data scientists choose to focus on a particular area of work. For example, data scientists who have a strong coding or engineering background may develop or recommend systems, build machine learning algorithms, and devise ways to enhance web-browsing functions. Others conduct research for reports or academic journals. Still others focus on improving business strategy for activities such as marketing, sales, and user engagement”(Coursera). This helps to show that data scientists can have many different backgrounds.

To conclude, after researching both careers, it is clear that they both would make great careers. They both involve skills in information and technology literacy. They both involve the use of computer programming. 


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