Chapter 2. Challenges of the Smart Data Era for Enterprises

In the smart data era, enterprises should transform themselves from traditional product- and technology-driven enterprises into data-driven ones. Different from traditional enterprises, data-driven enterprises are characterized by the following aspects:

  • Data is regarded as an important asset for management.

  • Specific data applications are used to solve business problems. (These applications are linked to the current data systems of enterprises. Meanwhile, enterprise data—both self-owned and other business-related data—are called).

  • Specialized and structured data teams are set up inside the enterprises (problems are not solved by outsourcing).

  • A data-driven culture is built.

During the transition to becoming a data-driven entity, traditional enterprises are severely challenged by business digitalization and data capitalization. A huge amount of data is not acquired in an effective manner due to the lack of business digitalization. For example, users’ click event data on websites, the interaction data of app users, user subscription and browsing data on WeChat public platforms, customer visit data of offline stores, and other business-related data may not be acquired or used. Nowadays, the prevailing mobile phones (e.g., iPhone, Samsung Galaxy, etc.) are generally equipped with 15 or more sensors, including ambient light condition perception, acceleration, terrestrial magnetism, gyroscope, distance, pressure, ...

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