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In today’s data-driven world, organizations are constantly seeking ways to extract valuable insights from their data assets, especially when collaborating with their partners. Companies across industries such as advertising, healthcare, media, entertainment, finance, insurance, and others rely on insights generated from first- and third-party datasets to develop new products and services, improve business decision-making, assess the impact of marketing campaigns, and increase revenue opportunities. For example, a pharmaceutical company might want to analyze patient data with an academic hospital to assess the efficacy of new drugs, or an auto insurer might want to help complement insurance policies with market insights about a driving population. These datasets often contain information about individuals that can be extracted by comparing aggregated statistics. In the advertising industry, for example, an advertiser who is querying ad impressions data from a publisher can learn which users viewed an ad by adding or removing users from their analysis one by one and finding the difference in query results.
In this blog post, we outline what differential privacy is, the applications of this proven framework, and challenges to applying it effectively. You will learn about AWS Clean Rooms Differential Privacy, how this new capability makes it easy for you to apply differential privacy and protect the privacy of your users, as well as common use cases across industries.