Horizontal Scaling

Horizontal scaling, often referred to as scaling out, is a method used in data analytics and business intelligence to increase capacity by connecting multiple hardware or software entities so they work as a single system. Imagine your favorite restaurant gets more customers than they can fit, so instead of just expanding the existing building, they open up new locations. In the same way, horizontal scaling involves adding more machines to a system, like servers or databases, to manage increased workloads or growing amounts of data.

This approach is particularly useful for businesses dealing with huge volumes of data that need to be processed quickly because it allows for more flexibility and resilience. If one server goes down, the others can pick up the slack, ensuring that there’s no single point of failure. This is great for data-heavy tasks like real-time data processing or handling large numbers of simultaneous transactions, which are typical in business intelligence applications.

In essence, horizontal scaling helps to accommodate growth and improve performance in business operations. It’s a scalable and cost-effective strategy for managing big data, as businesses only add resources when needed. This ensures that systems remain efficient and responsive, even as demand fluctuates or increases over time.