While working with small data such as the size of data that fits on a desktop or laptop, processing speed is impacted by several factors, such as the speed of the processor or processors, the amount of memory, and the size of the usable disk space. While it is important to optimize the resources at the desktop level to ensure the best response times and the amount of work that can be done, it becomes vital in working with big data to have the proper analytic processing environment setup using the proper configurations and options.
This will ensure a team of architects, data scientists, and business analysts can prepare, analyze, and most importantly, actually put the results of analytics into production as fast as necessary to gain value or provide a competitive advantage.
It is the overall enterprise architecture that allows for big data analytics to process efficiently and to succeed in providing value, or else it becomes a bottleneck that needs to fixed. Analytical insights...