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Is there any future for data science?
You can think about the data increase from IoT or from social data at the edge. If we look a little bit more ahead, the US Bureau of Labor Statistics predicts that by 2026—so around six years from now—there will be 11.5 million jobs in data science and analytics.
Where did data science come from?
The term “data science” has been traced back to 1974, when Peter Naur proposed it as an alternative name for computer science. In 1996, the International Federation of Classification Societies became the first conference to specifically feature data science as a topic. However, the definition was still in flux.
What year did data science start?
A trip into the history of data science reveals a long and winding path that began as early as 1962 when mathematician John W. Tukey predicted the effect of modern-day electronic computing on data analysis as an empirical science. Yet, the data science of today is a far cry from the one that Tukey imagined.
What is a data scientist and how to become one?
Big data is useless without analysis, and data scientists are those professionals who collect and analyze data with the help of analytics and reporting tools, turning it into actionable insights. To rank as a good data scientist, one should have the deep knowledge of:
How will computers learn from data in the future?
Meanwhile, experts believe that computers’ ability to learn from data will improve considerably due to more advanced unsupervised algorithms, deeper personalization, and cognitive services. As a result, there will be machines that are more intelligent and capable to read emotions, drive cars, explore the space, and treat patients.
How big is the global datasphere going to get?
In its Data Age 2025 report for Seagate, IDC forecasts the global datasphere will reach 175 zettabytes by 2025. To help you understand how big it is, let’s measure this amount in 128GB iPads. In 2013, the stack would have stretched two-thirds of the distance from the Earth to the Moon. By 2025, this stack would have grown 26 times longer.
What are the biggest issues facing data science today?
A big issue right now is that while more and more companies are committing more heavily to data-driven product development and their data teams, there are very few examples of folks deep in their careers who are pure data scientists, particularly when you exclude people in management.