Author Title Year Program
Matira, Ramil C.
Big Data Analytics Using Mapreduce for Structured Data 2018
Master in Information Systems
ABSTRACT
Today, data comes from everywhere and any time of the day, every day. It may be from your computer at home while browsing an online store for something to buy, your mobile devices while chatting with friends, using credit or debit cards or just your mobile phone lying around the corner. Data became so digitized and flowing so fast in huge volume. Business organizations strive so hard to remain on top of the competition by leveraging the information they get from this huge data also known as big data. However, not all organization has the capacity to buy sophisticated high-end hardware and software which worth thousands to millions of dollars. They opt to buy cheaper commodity-grade hardware usually arrange in clusters running in a virtualized environment.
This project aims to create a system for analyzing big data using clusters lower-end hardware. Databases designed to be fast and efficient in processing of structured data. Data is structured when it resides in a fix fields within a record or file. However, achieving scalability comes with a great cost in infrastructure and maintenance. Implementing MapReduce framework saves organizations from big expenses but will require different approach in dealing with data. Most implementations are designed to handle unstructured data. This project created a system that implements MapReduce framework of parallel databases for analytical purposes of structured data.
