Dr. Elena Gortcheva is the Program Chair for the MS in Data Analytics and MS in Information Technology – Data Systems Technology in the Graduate School of the University of Maryland University College (UMUC). Her research interests focus on data mining and intelligent systems, and she teaches courses in data mining and big data analytics.
UMUC is one of the pioneering institutions in online education and has always emphasized serving the academic needs of working professionals. As a part of its mission, UMUC constantly scans the environment to detect opportunities to offer quality and innovative workforce-related degree programs. In this realm, Dr. Gortcheva is working on transitioning the MS in Data Systems Technology and MS in Data Analytics to a skills-based approach.
We caught up with Dr. Gortcheva to learn more about the Data Analytics (offered online) and Data Systems Technology programs and how they prepare students to succeed in their eventual careers.
A: Our MS in Data Analytics and MS in Information Technology with Data Systems Technology specialization are designed to help early- to mid-career professionals develop technical and analytical skills for today’s data-driven world. Those who are interested in becoming a Data Analyst or a Data Scientist can pursue the MS in Data Analytics, while the MS in Information Technology – Data Systems Technology specialization is a better fit for those interested in a Data Architect or Data Engineer career. For people specifically interested in the business domain, we also offer a Certificate in Business Analytics.
The best candidates for these programs are smart, involved, aware, and possess intellectual curiosity beyond their typical professional involvement. The ideal student possesses strong quantitative skills as well as a solid foundation in descriptive and inferential statistics. Prospective students should be comfortable learning to use new computer software as well as working with a diverse group of people ranging from operational managers to information technologists.
A: To ensure that core competencies and skills reflect those of a professional in today’s Big Data world, both programs use a skills-based approach that assess students’ learning based on how well they apply the methods/techniques to real world scenarios. The learning activities are in the form of “learning demonstrations” (LDs), which provide a guided journey for learning key concepts and processes that reflect those encountered in the real world. There are a growing number of institutions and government agencies that produce very large-scale data sets. Since most of our students are working professionals, they use public data in their areas of interest, including health care, biotechnology, finance and government, as part of their coursework.
A: For students in the MS in Data Analytics program, the most significant technical skills include statistics, machine learning and data mining. Equally important are the programming languages/packages and other tools that enable them to perform data preparation, data mining and visualization. The most important programming languages/packages and tools currently in the program include R, Python, SAS, Watson Analytics, Tableau, and distributed open source frameworks, such as Hadoop. It is very important to keep in mind that the technical skills in the second group are subject to rapid changes, so the graduate must possess the ability to transition to new languages/packages and tools rapidly and regularly.
For students in the Data Systems Technology specialization, the most significant technical skills are database modeling, design and implementation, data warehousing, and data mining. Similarly, languages and technologies, such as SQL, NoSQL, Hadoop-based technologies (e.g., MapReduce, Hive and Pig), Spark, R and Python, are essential to the program.
A: Aspiring data analysts will have to work effectively in a team with both operational managers and information technologists. They must clearly and fluently translate their technical findings to a non-technical team, such as the marketing or sales departments. Data analyst must prepare clear reports relating to data project proposal as well as drafting recommendations to upper management.
Our curriculum was designed based on the workforce needs of the industry and reflects the requirement for strong communications skills. Accordingly, all master’s degree students must take a specially developed course intended for students to exhibit both effective written and oral communications, develop presentation skills, apply collaboration tools, and utilize other business software.
A: You have chosen the demanding career of a data professional. This career is part of a rapidly changing industry, so be prepared to be lifelong learner.
Other initiatives students can take include attending industry events, joining associations, and networking with others in the field. But an important factor is to have a passion for the field.