A data analysis methodology for measuring practical technology impact index by analyzing trends data

In the feasibility analysis of RandD program, the data used to analyze the impact/trends/level of technology derive mostly from patents and theses. However, there is limitation in reflecting the newest technology trends data based on patents and theses. That is because of the occurrence a one or two year gap time before these patents (or theses) are actually published or granted. Therefore, not only related patents and theses data collected but, the extensive trends from public websites and social networks also need to be collected and analyzed. It takes a great deal of time, manpower for these related feasibility analysis to happen successfully. To solto happen successfully. To solto happen successfully. To solto happen successfully. To sol to happen successfully. To sol to happen successfully. To sol to happen successfully. To sol to happen successfully. To solve this issue this analysis presents a methodology not only to rapidly and accurately collect data but to efficiently analyze the newest technology trend flows. application measuring model and the determination of TIIB (Technology Impact Index based on Big Data) are processed. This theses proposes that the data analysis methodology used to find out latest technology trends could also be useful for optimizing efficiency when analyzing. Moreover, the newly developed TIIB enables us to check the interest trends of technology by reading yearly changes.