Learn the various foundational technologies that make data science possible, such as cloud computing, machine learning, data mining, and visualization.
- [Voiceover] There are a number of underlying technologies…that make data science a reality.…These include data infrastructure, data management,…and visualization technologies.…Data infrastructure technologies support…how data is shared, processed and consumed.…One of the most popular data infrastructure technologies…data scientists use today is distributed computing…in general and in particular cloud computing.…
There are key underlying technologies…that enable cloud computing.…Virtualization is one of them,…distributed file sharing is another.…In particular, redundant array of independent disks or RAID…and Hadoop distributed file system…or HDFS are prominent ones.…Data Management is handled by…database management systems or DBMS.…
Data Science requires highly scalable, reliable,…and efficient ways to store, manage, and process data.…Which is why DBMS plays a critical role…in data science.…As big data becomes mainstream,…unstructured data is also becoming more prevalent.…In fact, the majority of…business related data is unstructured.…
Jungwoo Ryoo is a professor of information science and technology at Penn State. Here he reviews the history of data science and its subfields, explores the marketplaces for these fields, and reveals the five main skills areas: data mining, machine learning, natural language processing (NLP), statistics, and visualization. This leads to a discussion of the five biggest career opportunities, the six leading industry-recognized certifications available, and the most exciting emerging technologies. Along the way, Jungwoo discusses the importance of ethics and professional development, and provides pointers to online resources for learning more.
- A history of data science
- Why data analytics is important
- How data science is used in fraud detection, disease control, network security, and other fields
- Data science skills
- Data science roles
- Data science certifications
- The future of data science
Skill Level Beginner
Insights on Data Science: Lillian Piersonwith Lillian Pierson, P.E.23m 51s Intermediate
1. Define Data Science
6. Future of Data Science
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