In the field of data sources, the region faces substantive challenges to be able to measure real progress in the process of achieving the objectives and goals of the development agendas. In this context, the population and housing censuses appear as an essential tool that must be taken into account to face these challenges of essential information for the calculation of the indicators. Its universal scope makes it possible to obtain information for both houses, households and people in a country and thus to know the living conditions of the population, for smaller geographical areas and specific population groups.
In addition, we started the 2020 round, which despite the pandemic has continued with its planning and some countries are already beginning this year with their census operation. Once the censuses are carried out, it will allow a comparison of the indicators in each decade. Censuses make it possible to build indicators with different breakdowns and see the evolution of the components of demographic change, among others as indicated in SDG 17.18 on capacity building to significantly increase the availability of timely, reliable, and quality data broken down by income, gender, age, race, ethnicity, immigration status, disability, geographic location, and other characteristics relevant in national contexts.
Redatam is a free software for statistical processing, developed by CELADE–Population Division of ECLAC, which offers key features for managing censuses, such as a hierarchical data structure that allows very fast and efficient processing, an interface friendly to easily program indicators online or on the desktop, and at the same time, it allows geographically disaggregated analyzes for specific population groups given the universality of the censuses.
In turn, the display of statistics through maps and their various ways of representing their spatial distribution are an advantage for transmitting and making visible the social inequity that exists in the region at the national and subnational level. This is why we will dedicate several sessions to mapping with the QGis tool.
