Applications of Data Engineering

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 engineering.

The basic application of data engineering includes  Data warehousing. It is the collection of data, which is not ordinary data but it is cleansed & processed.  

When we got the data in a data warehouse then we can generate many reports from that and then we can also get several insights from it and we can use those insights in the real-world applications and products, for example, it can be used in many data science projects e.g.  Information Extraction, Sentiment Analysis, Call center data analysis, and so on. 

When we have data then we cannot do anything (ethical) with that data if it is not being engineered, engineering is very important when it comes to different applications of data engineering products, there are many companies like Teradata, contentstudio.io, etc. using the data to generate reports on the daily basis and these reports are not just generated on daily basis but also on the basis of seconds and milliseconds i.e. near real-time, this was one of the applications of data engineering that we have just discussed so let's see some other use case of data engineering that we can think of is the use of data in IoT, Machine Learning tasks, AI-oriented systems, and the list goes on.

That's it for today, hope you have enjoyed this short and a well pending blog post, I literally posted any such blog post after around 8 months or so. 

Happy Learning :)