is the process of dividing a population or set of data points into multiple groups so that data points in one group are more comparable to data points in other groups. To put it another way, the idea is to sort groups into clusters based on common traits.
Let's look at an example to see how this works. Assume you run a rental store and wish to expand your business by learning more about your clients' preferences. Is it possible for you to look into the specifics of each customer and create a tailored business strategy for them? Certainly not. However, depending on their buying behaviors, you can divide all of your clients into ten categories and use a different strategy for each of these ten groups. Clustering is the term we use to describe this.
The following are some of the advantages of clustering Intelligence Servers:
1. Increased resource availability: If one Intelligence Server in a cluster fails, the burden can be picked up by the other Intelligence Servers in the cluster. If a server fails, this prevents the loss of valuable time and information.
2. Strategic resource allocation: You can distribute projects across nodes in whatever way you choose. This saves overhead by allowing you to use your resources more flexibly because not all machines are required to perform all projects.
3. Improved performance: Having many machines allows for more processing power.
4. Greater scalability: Your resources can expand as your user base and report complexity to develop.
5. Easier management: Clustering makes it easier to handle large or rapidly expanding systems.