Data is business. The pace at which an organization can process data improves its ability to react to business events in real time.
Today, organizations are bringing together new types of data from a variety of internal and external sources for analytics, often in real time. They often explore new architectures, such as next-generation data lakes, information hubs and real-time streaming architectures to process and gain value from this data and build machine learning models in their path to artificial intelligence (AI). There is a growing need to develop capabilities that can effectively feed data into landing zones or information hubs and thereafter quickly process large data sets for quick responses to changing business events.
According to the third Gartner Chief Data Officer survey in 2017, chief data officers (CDOs) are not just focused on data, as the title may imply. Their responsibilities span data management, analytics, data science, ethics and digital transformation. In the 2017 survey, 86 percent of respondents ranked “defining data and analytics strategy for the organization” as their top responsibility, up from 64 percent in 2016. This reflects a need for creating or modernizing data and analytics strategies within an increasing dependence on data and insights within a digital business context.
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Source: https://www.ibmbigdatahub.com/blog/real-time-business-value-comes-real-time-data