Читать книгу Data Science in Theory and Practice - Maria Cristina Mariani - Страница 13

Data scientists are part mathematicians, statisticians and computer scientists. And because they span both the business and information technology (IT) worlds, they're in high demand and well‐paid. Data scientists were not very popular some decades ago; however, their sudden popularity reflects how businesses now think about “Big data.” Big data is defined as a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data‐processing application software. That bulky mass of unstructured information can no longer be ignored and forgotten. It is a virtual gold mine that helps boost revenue as long as there is someone who explores and discovers business insights that no one thought to look for before. Many data scientists began their careers as statisticians or business analyst or data analysts. However, as big data began to grow and evolve, those roles evolved as well. Data is no longer just an add on for IT to handle. It is vital information that requires analysis, creative curiosity, and the ability to interpret high‐tech ideas into innovative ways to make profit and to help practitioners make informed decisions.