Learn what business intelligence architects do by analyzing their responsibilities. Also learn the preparation it takes to become one. Jungwoo explains what is 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 soft 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 analytics, explores which markets are using big data the most, 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 four 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 analytics is important
- How data science is used in social media, climate research, and more
- Data science skills
- Data science certifications
- The future of big data