By: Raul Cruz
Dr. Vladimir Bugera, founder of Big Data Realty and adjunct faculty in the Department of Journalism and Media Management, previewed his fall course, Applied Data Analytics for Journalism and Media Management, for the members of the Media Management Association. Between 2004 and 2020, he worked as an algorithm developer for American Express and then as a data scientist for BankUnited.
Bugera began his presentation by defining what data analytics is–the process of analyzing raw data to find trends and answer questions.
“The techniques and processes of data analytics help to convert data collection, analysis, and decision making into automated tasks to save time, reduce costs, and do more [than anticipated].” He emphasized that data analytics is important for communication students because this analytical process affects all industries, including the media sector.
Next, Bugera discussed the meaning of big data, which is a very complex concept with no single definition. That complexity is largely due to a mix of three factors: the immense volume of data, which cannot fit on a single hard drive; its high velocity, which often happens in real-time as in the case of social media; and its variety, which can be structured, semi-structured, or unstructured. Semi-structured and unstructured data require more pre-analytical processing than structured data.
Bugera went on to elaborate further about the process of data analytics, which he described as a pipeline with four phases: project planning, data preparation, data modeling or analysis, and follow-up, in which the final project model is presented and later revisited if needed. He also detailed the various job opportunities that are available with studying data science, which range from the less technical level, such as data/business analysts (which the class will mostly focus on), to the more technical level, such as programmers or data engineers. Both paths could eventually lead to the position of senior data scientist.
Another concept in data science that was explored was programming, which Bugera described as the process of creating a list of instructions, which themselves can be viewed as an algorithm. He referred to the colorful algorithmic example of putting a giraffe into a refrigerator in three steps; first, the refrigerator must be open; second, the giraffe must be placed in the refrigerator; and finally, the refrigerator must be closed. When it comes to learning programming, Bugera recommended the Python programming tool because it is a relatively easy-to-use language for beginners. Students will learn the basics of Python and how to apply libraries to relevant situations in his course.
After the presentation, Bugera addressed the general misconceptions that come with understanding data science/analytics. While the topic of data science/analytics can be complex, it has become more accessible and easier to use thanks to modern technology. Finally, he concluded that data science is becoming a vital skill set to learn for people in the industry and that people must at least gain a simple understanding of data analytics as technology moves forward.
JMM 463/663, Applied Data Analytics for Journalism and Media Management, will be offered in the fall semester on Mondays from 6 to 8:45 p.m. It will introduce undergraduate and graduate students to the procedures used for extracting, processing, and analyzing datasets on web and social media sites. No prior knowledge or experience is required.