INE - European Statistics Day: BBVA Research experience using Big Data

Summary

Big data techniques help us to enrich traditional databases with high dimensional data, but there are still some challenges we have to face. Real time data, combined with historical data may end up changing the way in which economists approach empirical questions and the tools they use to answer them.

Key points

• Key points:
• Big data complements traditional databases with high dimensional data: Quantifying new trends and exploiting new dimensions Having timely answers on the impact of different events, providing early warning signals indicators. Improving our models performance at nowcasting.
• There are still some challenges: data challenges: missing data, data sparsity, data quality, etc. In most cases, there’s not enough time horizon to improve our models performance at forecasting. Legal and regulatory issues for data sharing.
• Unstructured and massive data represents a challenge to traditional techniques, making the data treatment a crucial part of the working process (and the most consuming one).
• The granularity of the information can be really valuable for the analysis.

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