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Learn more about data science, machine learning, artificial intelligence and other Information Technology areas.
Data Science
Data Science Definition
Data science combines multiple fields, including statistics, scientific methods, and data analysis, to extract value from data. Those who practice data science are called data scientists, and they combine a range of skills to analyze data collected from the web, smartphones, customers, sensors, and other sources.
Data science is an untapped resource for machine learning. It is one of the most exciting fields out there today. It is so important because companies are sitting on a treasure trove of data. As modern technology has enabled the creation and storage of increasing amounts of information, data volumes have exploded. It’s estimated that 90 percent of the data in the world was created in the last two years. For example, Facebook users upload 10 million photos every hour.
But this data is often just sitting in databases and data lakes, mostly untouched.
The wealth of data being collected and stored by these technologies can bring transformative benefits to organizations and societies around the world—but only if we can interpret it. That’s where data science comes in.
Comparison
What’s the difference between data science, artificial intelligence, and machine learning?
To better understand data science—and how you can harness it—it’s equally important to know other terms related to the field, such as artificial intelligence (AI) and machine learning. Often, you’ll find that these terms are used interchangeably, but there are nuances.
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Transformation
How data science is transforming business
Organizations are using data science to turn data into a competitive advantage by refining products and services. Data science and machine learning use cases include: Determine customer churn by analyzing data collected from call centres, so marketing can take action to retain them. Improve efficiency by analyzing traffic patterns, weather conditions, and other factors so logistics companies can improve delivery speeds and reduce costs.
Improve patient diagnoses by analyzing medical test data and reported symptoms so doctors can diagnose diseases earlier and treat them more effectively. Optimize the supply chain by predicting when equipment will break down.
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