Data modeling stands for the process of developing a descriptive diagram that demonstrates relationships between different types of information which are to be stored in a database. It’s a theoretical presentation revolving around data objects and associations between different data objects. Data modeling is an important skill for every data science professional, whether one is architecting a new data store or doing research design for his/her organization. To excel in this key component of data science, one needs to have the ability to think systematically and clearly about the major data points to be stored as well as retrieved, and how they need to be related and grouped.
Data science is an extremely dynamic field where a significant number of aspects keep on changing on a regular basis and we can expect them to bring even more value in the upcoming future. Despite the omnipresence of data science professionals in almost all business sectors these days, the field is still in its nascent stage. While it’s true that the extensive use of this field is currently limited to a few fields, over the next few years, we can expect it to start powering a lot of fields in a similar way. In this post, we’re going to explain why data science is being considered the future of the tech field.