Python 3.7.6, Flask 1.1.2, JupyterLab 2.26, VS Code 1.51.1 MongoDB 4.4.2 HTML5, Bootstrap 3 The purpose of this project is to build a web application using Flasks framework, as a custom interface to ...

Relational databases such as MySQL, Oracle, PostgreSQL can be queried and extract using SQL whereas NoSQL databases, most have native support for JSON as an import format. This means you can export ...

Extract, transform, and load (ETL) is a common process for moving data from one source to another, often for analytical purposes. However, ETL can be challenging when dealing with NoSQL and graph ...

While “Big data” has brought good tidings in terms of easy accessibility to voluminous data, we are faced with challenges too. The existing Knowledge Discovery in Database (KDD) processes which have ...

Using big data to extract value from your data is one thing. However, using NoSQL can increase your technical debt and put your enterprise at risk of data integrity and the lack of resilience.rn.

When archiving data, depending on your data and NoSQL database, you may have a variety of options. For instance, some NoSQL databases, such as MongoDB and Cassandra, offer native features like TTL ...

Ontology-driven entity extraction: Continuing the process of making MarkLogic semantically aware of your data, MarkLogic 9.0-5 introduces ontology driven entity extraction.

McCauley then listed relevant strategies for data migration to NoSQL databases: Use DMS or your favorite Extract, Transform, Load tool. Write and run custom scripts to gain experience with bulk loads.