The data science field encompasses a wide scope, ranging from collecting data to data management, analysis, and visualization. Pulling all these areas together, a data scientist can gather information from obtained data and create visualizations to communicate results.
Collect and organize data
The collection and organization of data is arguably the most important factor within the data science field. You cannot do anything without having data to work with, so you must have a method of collecting data. This can be done independently/on your own, for example scraping the web or applications or even conducting a survey for respondents to take. You may also have access to data that has already been collected either by open source repositories, or sites such as Kaggle. You may get the data from a separate team within your company, but either way, the data will still need to be organized.
Identify patterns in data
Visualization, statistical analysis, and data mining are processes that can be used either individually, or in combination, to detect patterns within data.
Develop alternative strategies based on the data
Data patterns can be incredibly useful when developing business plans or new strategies. People tend to have bias and opinions on strategies they believe will be the best route to take, while data is just data, no bias or opinions
Develop a plan of action to implement the business decisions derived from the analyses.
Data scientists need to be able to turn findings derived from their analysis into an actionable plan. They should always look for the reason why or how and use this to provide a new path or as a reason to stay committed to the current one. During this time, you should also look for efficient ways to implement the business decisions provided. One idea would be to add automated reports built similarly to the analysis completed, so as the decisions are made one can monitor the effect it has.
Data scientists must always be aware of their audience and how to efficiently communicate with different groups. One needs to understand what individuals need information. While creating a web-based business intelligence tool, you should not be going into great detail with the employee creating the user interface (UI) because it is redundant information for them. On the other hand, working with the Statistician about the color design is not a good use of time either.
Ethics / Privacy
Information privacy is a very sensitive subject as people are becoming more aware that companies are collecting their information. Both in collecting and working with data you must be aware of any laws such as GDPR.