| Sumario: | Demographers and social scientists can contribute to big data initiatives by drawing on well-developed statistical tools and techniques for assessing data quality, for example, by evaluating big data analyses using traditional data as a reference. The less frequent-and mostly experimental-use of big data in these countries to date can be attributed to limited resources and technical expertise, weak or nonexistent laws and regulations governing data use, the lack of data literacy around big data, and low demand for data for public good.72 LEGAL AND ETHICAL CONCERNS The same pathways that enable data to be used to improve lives can also create openings for inappropriate and harmful data use.73 Data not stored securely can be vulnerable to unauthorized users or hackers who leak private information to others. Although big data analysis is considered cost-effective relative to the long process of collecting data through traditional household surveys, start-up requires developing technical capacity, and the data may not meet all information needs. Either way, before meaning can be gleaned from big data, researchers must filter it using data analytics-tools and methods that convert massive amounts of raw data into "data about the data" that researchers can analyze for a specific purpose.[23] Machine learning makes this possible.
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