In this module, we are exploring the various techniques used to represent data. In every field, there is a vast amount of data that can be analyzed. For example, extensive medical records need to be stored in an efficient way that would protect patient confidentiality and pass an external audit. Management companies need to closely monitor sales data and analyze the marketing trends of their consumer demographics. Data is everywhere.

Often at the management level, you will be required to analyze data. This week we are exploring how data can be utilized by a large company, which collects sales metrics. Think now about the data you will need to analyze in your future profession. Our dataset for Milestone $1$ is particularly small. In most careers, Excel cannot maintain the vast amount of data used in the day to day operation of a business, which can span hundreds of thousands of rows... more is needed.

Take some time to research a particularly useful data analysis software in your field. Will you use Excel entirely? Will you work with database software on a regular basis $($such as SQL or Microsoft Access$)?$ Will you need to perform data analysis $($in Excel, SPSS$,$ Python, or R$)?$ What types of problems will you need to solve on a daily basis? How might the ability to visualize data be used effectively in your role?

Please write a reflection guided by these questions. In your replies be sure to observe the data your peers anticipate analyzing and expand on their own research methodology.