[MUSIC] If you want to convert your thoughts into action, you need your brain and body to work together. Similarly, in data analysis you need memory and processor to work together in order to produce information that you can use. Memory and processor are the two basic components of computational platform. The memory stores data, whereas processors transforms data into information. The quality of memory can be gauged by how much data it stores. For example, megabytes, gigabytes, or terabytes. Similarly, performance of processor is measured in terms of how fast they can transform data into information. Gigahertz is one unit that is used for processor performance measurement. There are four steps involved in how memory and processor interact with each other to convert data into information. First, the data is stored in memory. Second, the processor assesses the stored data. Third, the access data is converted into useful information by the processor. Finally, the generated information is stored back into the memory. In a nutshell, processor is a thinking machine for the entire data handling operation. It receives the input information on how to handle the input and then produces the required output as defined by the user. Scalability and performance are two important concepts of advanced analysis. Think of a startup company that wants to invest in computers. Let's say that their data storage and processing needs are minimal. Chances are, they will start off with a computer that has just enough memory and just enough processing speed. Now consider time passing by and the business grows. There's greater storage needs, and how fast they need to process data into information also grows. They might consider moving from 10 megabytes to 20 terabytes in memory. And 1 gigahertz to 200 gigahertz in processor speed. This is the concept of scalability and performance. Scalability is the characteristic of a system or model that has the capability to cope and perform when faced with expanding workload. This is an important attribute of a system. The trick is to think about scalability and performance when you make your first investment. The system you put in place, first, must allow for scalability when you need it at a later stage. Otherwise, you may not be able to build on your initial investment. Rather, you may have to start over again and that might be financially expensive and operationally risky. The performance can be described as the amount of work accomplished by the system with it's available resources.