Learn what business intelligence architects do by analyzing their responsibilities. Also learn the preparation it takes to become one. Explore BI and what it means to be an architect.
- [Voiceover] Business Intelligence, or BI, is a process of collecting, managing and processing corporate data to provide actionable information for the leadership and employees of a company. BI is heavily technology-driven, and leverages various software applications to perform the analyses and analytics of company data. In the information technology industry, the architect job title is often given to a senior member of a technical team, such as group of software developers.
An architect is usually a person who is at the pinnacle of a technical career. This person is a seasoned veteran who leads a major technology initiatives of a company. Therefore, an architect position is by no means considered to be an entry level position in most companies. With this understanding of what is BI and what it means to be an architect, let's explore more the job of BI architect. One of the core responsibilities of a BI architect is to design and implement system architectures to maximize the potential of a company's data assets.
To make this happen, the BI architect needs to be able to build a system that links various standalone IT systems throughout a company to pool relevant and useful information for strategic decision-making.
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
Learning Data Science: Understanding the Basicswith Doug Rose1h 16m Appropriate for all
1. Define Data Science
6. Future of Data Science
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