摘要： The journey of data analytics began with simple descriptive (review of past events) and diagnostic (analysis of past events) exercises and moved to the more sophisticated predictive and prescriptive genres,where advanced data models have enabled accurate future forecasts and actionable intelligence. And now cognitive computing has further strengthened the actionable predictive power of the machines by making the machine act like the human brain. For example, in addition to deciphering “words” in a piece of text, a cognitive analytics system can also interpret the context of the written material.
The journey of data analytics began with simple descriptive (review of past events) and diagnostic (analysis of past events) exercises and moved to the more sophisticated predictive and prescriptive genres,where advanced data models have enabled accurate future forecasts and actionable intelligence. And now cognitive computing has further strengthened the actionable predictive power of the machines by making the machine act like the human brain. For example, in addition to deciphering “words” in a piece of text, a cognitive analytics system can also interpret the context of the written material.
According to Ulster University research, 90 percent of the data floating around in the digital world today “has been created in the last two years.”This data is the “oil of the 21st Century Digital Economy.” Thus, it is easy to understand why data analytics is becoming an increasingly important driver of global businesses and soon many spheres of human activity will be governed by data-driven decision-making.
Over the years, data analytics has played a key role in corporate decision-support systems. Data-driven information, insights, and predictions — all have contributed to the competitive edge of global business operations, making data the most prized asset of enterprises in the digital age.
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