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This is Chapter 1.8, in the INSEAD/Cornell/WEF report on Big Data. The contribution focuses on the social and economic value of data, but from the point of view of use and purpose rather than volume. As it has become axiomatic that more data are produced every year, commentators have been driven to call this revolution the “age of big data.” However, what is commonly known as “big data” is not a new concept: the use of data to build successful products and services, optimize business processes, and make more efficient data-based decisions already has an established history. Moreover, the term big data is ambiguous: the main features of big data (quantity, speed, variety) are technical properties that depend not on the data themselves but on the evolution of computing, storage, and processing technologies. What is important about big data is not its volume but how it may contribute to innovation and therefore be used to create value. This is why this chapter uses data-driven innovation to frame the discussion.High-value solutions that may not have quantifiable economic value are being developed using data, and many sectors, from businesses to governments, benefit from data-driven innovation. Apart from producing and using data for better policymaking processes, the public sector can also play its part in promoting and fostering data-driven innovation and growth throughout economies by (1) making public data accessible through open data formats, (2) promoting balanced legislation, and (3) supporting education that focuses on data science skills.
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Stored only when both papers are in the corpus — 8 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.