Automatic Identification and Data Capture (AIDC)

Automatic identification and data capture (AIDC) is the big data term that refers to a method of automatically identifying and collecting data objects through computing algorithm and then storing them in the computer. For example, radio frequency identification, bar codes, biometrics, optical character recognition, magnetic strips all include algorithms for identification of data objects captured.

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Data warehouse optimization is considered the most important big data analytics use case, and is considered critical or very important by 70 percent of businesses.
53 percent of companies are adopting big data analytics
More than 30 percent of businesses say big data and analytics have fundamentally changed business practices in their research and development departments
Data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain customers, and 19 times as likely to be profitable as a result.
40 percent of businesses say they need to manage unstructured data on a frequent basis.
29 percent of investment professionals use search trends to derive data.
61 percent of businesses that recognize the effect of data and analytics on their core business practices say their companies either have not responded to these changes or have taken only ad hoc actions rather than developing a comprehensive, long-term strategy for analytics.
People generate 2.5 quintillion bytes of data each day.
Businesses that use big data saw a 10 percent reduction in overall cost.
Only 16% of organizations can currently say that 75% or more of their employees have access to company data and analytics.

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