Agile Data Science - NoSQL & Dataflow Programming



There are times when the data is inaccessible in relational format and we need to keep it transactional with the assistance of NoSQL databases.

In this section, we will concentrate on the dataflow of NoSQL. We will also learn how it is operational with a mix of agile and data science.

One of the significant reasons to utilize NoSQL with agile is to increase the speed with market competition. The following reasons show how NoSQL is a best fit to agile software methodology −

Fewer Barriers

Changing the model, which at present is going through mid-stream has some genuine costs even in case of agile development. With NoSQL, the users work with aggregate data instead of wasting time in normalizing data. The main point is to get something done and working with the objective of making model perfect data.

Increased Scalability

Whenever an organization is creating product, it lays more focus on its adaptability. NoSQL is constantly known for its adaptability but it works better when it is structured with horizontal adaptability.

Ability to leverage data

NoSQL is a schema-less data model that permits the user to readily utilize volumes of data, which incorporates several parameters of variability and velocity. When considering a decision of technology, you should always consider the one, which leverages the data to a greater scale.

Dataflow of NoSQL

Let us consider the following example wherein, we have demonstrated how a data model is focused on creating the RDBMS schema.

Following are the various requirements of schema −

  • User Identification should be listed.

  • Each user should have mandatory at least one skill.

  • The details of each user’s experience should be maintained appropriately.

users_experience

The user table is normalized with 3 separate tables −

  • Users

  • User skills

  • User experience

The complexity increases while querying the database and time utilization is noted with expanded standardization which is not good for Agile methodology. The same schema can be planned with the NoSQL database as mentioned below −

complexity_increases

NoSQL maintains the structure in JSON format, which is light- weight in structure. With JSON, applications can store objects with settled data as single documents.





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