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Data engineering involves a lot of decisions. And with the dozens of database solutions that we have currently, choosing a database or data storage platform is certainly one decision to make with the right knowledge and competence.
NoSQL databases offer different paradigm and capability totally different from what we know in traditional relational database management systems (RDBMS). Also, data decision are made usually during application development until when getting the value of the data it becomes an issue.
In this Hackerday, we want to go through all the classes of NoSQL that is and pick an example of the lot. This Hackerday is not an intensive review into each of them but we will do well to mention what can be offered in each example.
We will begin with the traditional or popular RDBMS, discuss the features, functionalities, and limitations. In the light of that, we will walk through all the various classes of NoSQL database and try to establish where they are the best fit.
At the end of this Hackerday, students will be able to adequately make a choice of database type given a required business specification and non-functional requirement. Also, students will be able to take on any interview to show their wide knowledge of the different database solutions in the market.
In this hadoop project, we are going to be continuing the series on data engineering by discussing and implementing various ways to solve the hadoop small file problem.
In this big data project, we will look at how to mine and make sense of connections in a simple way by building a Spark GraphX Algorithm and a Network Crawler.
In this big data project, we will continue from a previous hive project "Data engineering on Yelp Datasets using Hadoop tools" and do the entire data processing using spark.