Data Science Tales - A Tech blog by Bia Chaudhry

In a previous blog post about data engineering, we went through several many concepts related to data engineering such as data modeling, and then we went through different types of databases, for example, relational databases and we also got a glimpse of relational as well as NoSQL databases. And in today's blog post we will be writing about data engineer applications. Which are basically the use cases of data engineering 1st let's see what data engineering applications mean; so basically when we have data and we have engineered it then there are several things that we can do with that data and these things that we can do with processed data are the use cases of the data engineering. For example: If we have filled our containers with the data then it's not of any good use if it is not clean and well-formed. If your data is well-formed and if there are no logical mistakes, missing values, and garbage then we can easily perform the use cases and applications of data enginee...

In the previous blog post, we covered Data Modeling. We have seen that data modeling is really important before jumping into predictive modeling.  In this article, we will cover the Relational Data Model (RDM). Let's start from the very basics, relational means anything which is linked with some other thing. This link is called "Relationship". In RDM or RM there are major three types of relationship cardinalities (also called Multiplicities or Cardianalities): 1. One to one 2. One to many 3. Many to many We can understand these with the help of a few simple examples;  One to one: One department has one manager. One to many: One class has many students. Many to many: Many teachers can teach many students. Okay, so we have got an abstract overview of the term " Relational ", now the next thing is " Data ", data covers everything, anything... And finally, " Model " means something in the form of a template, design, a kind of blueprint.  To store...