Innovation is an essential topic in every economic segments. Understanding the mecanisms that promote support is an interest of Industry, Universities and Governments. The uses of data science as a way to explore big quantities of data is a normal activity in many sectors of Economy which focus on products innovation, services and processes, generating efficiency in produtivity and bigger winnnings in this field. Thus, this research is composed by two articles and it craves reviewing systematically what the studies about economic development were, taking as a reference the innovative process and data science. Besides that, it focuses on analyzing the aspects that contribute to the success of an innovative enviroment by 119 socioeconomic indicators of historical development, which were made available in several databases from 1960 to 2020. Furthermore, these indicators have been associated to thirty-two economies which are featured in the Global Innovation Index (GII) 2020 report. The adopted methodology was based on the following idea: in the first article, the researcher looked for communications on SCOPUS®, Web of Science® and Science Direct® bases, considering aspects of innovation, economic development, countries and data science. Afterwards, in the second article, the main goal was analysing thirty-two selected countries, by taking as reference, their 119 socioeconomic indicators of historical development and using the J48 consolidated algorithm. Considering the systematic view that leaded the first article, thirty-three studies were related to the research and associated to 5 economic fields that used resources of data science which were craved on innovation. In the second article, the results come up with indicators such as “Death rate crude (per 1000 people)”, “Fertility Rate Total (births per women)”, “Population Age 15-64 (% population total)”, “RegulatoryQuality, Governmenteffectiveness” and “High & médium high tech manufactures (% total)”. Concluding, we can consider that, in the first article, the systematic revision revealed the most reported economic segments in scientific research, all of them related to “economic development”, “innovation” and “data science”, considering the period from 2007 a 2021. In the second article, the outcomes evidence a relation between demographic control, labor availability, high and low technology productivity of goods and quality of market regulation, craving the development of the private sector and government efficiency, which are notorious aspects in the innovation process. A lot of research contributed to the found results, highlighting how data mining can be an important resource in public policy elaboration, learning processes for building business models and decisions making in economic development.
Keywords: Innovation; countries; economic development, data mining; J48C.