How to use open source databases in analytics?

Open source databases are used for analytics to review large volumes of data so businesses can better identify business goals. Open source data software is now commonplace in enterprise IT departments across many industries. Examples of the best open source databases include the following companies:

Ford Motor Company — collects 25 GB of data per vehicle per hour for its Smart Mobility program.

Macy’s – using open source data technology to reach customers with advertising campaigns tailored to their specific tastes and needs.

Progressive Insurance — Analyzes more than 15 billion miles of driving data through its Snapshot program to offer discounts to safer drivers.

Netflix — Runs its own open source software hub as an open source database of users and contributors to see what customers like.

Closed vs. Open Source Databases

Closed source databases have private source code that cannot be accessed or modified. The code cannot be checked for errors or corrected by anyone other than the company that wrote the code. Updates or patches can take a long time to complete. Closed source software and databases also have expensive licenses that require updating.

Open source databases are free and open to anyone to use. The source code can be downloaded and modified. Users can customize the code according to their needs and freely distribute it without vendor lock-in.

What is spatiotemporal reasoning?

Spatiotemporal reasoning is what a human or robot with artificial intelligence uses to understand how items fit together in space. It does so by delineating spatial patterns. This includes visualizing a step-by-step process and how objects can be manipulated into different modes.