About the Graduate Certificate in Data Analytics
A newer market-driven program available at the University of New Orleans (UNO), the graduate certificate in Data Analytics is geared toward the working adult or current graduate student with a strong statistical background.
Today, businesses across Louisiana and the globe have access to an almost insurmountable amount of data. Yet, yesterday’s methodology is no longer sufficient in terms of organizing, processing, and utilizing all of the available information. A business that can’t parse through related data doesn’t just get left out of the marketplace—it misses out on key decision-making information that could bring in customers and keep it ahead of competitors.
For these reasons, a data analyst proves to be an asset within plenty of organizations, and many industries are currently facing a shortage. In fact, according to figures from the Bureau of Labor Statistics’ Occupational Outlook Handbook, demand for research analysts and similar occupations is predicted to grow 26 percent from 2018 to 2028—faster than most other fields.
UNO’s graduate certificate in Data Analytics gives students a competitive advantage in today’s data-driven world. Courses help establish a solid grounding in data analysis, management, visualization, and communication, with the goal of successfully influencing an organization’s planning, products, and services. In turn, students learn to examine how data is collected, retrieved, restored, and extracted from large, unmanageable data sets and use techniques like data mining and machine learning to analyze it. Presentation plays a significant role, and classes further assist students with illustrating their findings through charts, graphs, and other methods.
As New Orleans’ only Carnegie-ranked public research university, UNO considers our courses within the context of the city’s and state’s existing communities. As a result, our graduate certificate in Data Analytics doesn’t just prepare students to enter a competitive and rapidly growing occupation; we’ve also angled coursework and class offerings toward several local industries where data analysts play an integral role, including digital media, health sciences, advanced manufacturing, waste management, energy, education, marketing, information technology, and civil engineering.
What Does a Data Analyst Do?
Simply put, data illustrates patterns about the world, the people in it, and the businesses operating within its scope. For businesses particularly, these patterns become useful for making predictions about its customers, competitors, and industry. Instead of putting together estimates or making assumptions, data aids companies in identifying and evaluating the best path forward.
Over the past decade, the amount of data available has grown to the point that standard statistical analysis methods can only examine a fraction of the volume—and aren’t always efficient. Specialized tools and software are now essential in compiling and assessing both structured data (easily categorized numbers and text from sources like smartphones, GPS, sales, sensors, and account balances) and unstructured data (a newer keyword-based, more complex form covering customer reviews, social media, photos, videos, and multimedia).
The modern data analyst not only needs to be well versed in statistical data collection and analysis methods of decades past; they must also understand the breadth and variables of unstructured data and know how to use the latest analysis and organization tools.
Coursework for the Graduate Certificate in Data Analytics—4 Courses (12 Credit Hours
The graduate certificate in Data Analytics is taken through the College of Sciences’ Department of Mathematics, yet the program’s industry-centric courses overlap with outside disciplines. Students must complete four total courses: two mathematics courses covering statistical analysis and modeling, and two additional courses focusing on the practical application of data analytics.
Core Requirement—2 Courses
Two introductory courses build on an undergraduate’s understanding of statistics. In MATH 5373, students are exposed to data analysis, collection, preparation, cleaning, visualization, management, and mining and learn to analyze numbers and other data via uncertainty, probability, variance, sampling, randomness, and other techniques. MATH 5385 progresses through major statistical learning methods, during which students apply these concepts to solve modern science-, industry-, and society-related problems.
Read full course descriptions in the Department of Mathematics’ Course Catalog.
Industry-Specific Option Courses—2 Courses
Many students seeking to earn a graduate certificate in Data Analysis already have careers and years of experience in fields of their choosing. Factoring in the working professional wanting to expand their skill set with data analytics certification and stay ahead of market trends, this program allows students to select two additional courses that focus on industry-specific applications of statistical learning and data analysis.
Three groupings cover key industries where data analysis skills are indispensable:
- Data science goes through the structure and implementation of database management systems and all required tools for data mining and warehousing.
- Management allows students to use data analysis skills to collect and analyze customer, product, and service data, touching on performance analysis methods and theories.
- Statistical learning offers insight into the importance of data in scientific and industrial settings.
- Urban research allows students the opportunity to apply their knowledge to topics like population estimation and forecasting, economic forecasting, locational analysis, and forecasting related to transportation and housing.
Career Outcomes
UNO’s graduate certificate in Data Analytics offers working professionals an invaluable credential across financial, technical, engineering, and more occupations. Newly acquired skills supplement and compound to industry-relevant experience and open up a gateway to advancement.
Regardless of field, a data analyst divides their time between conventional statistical methods and using new software programs to collect, process, and analyze large amounts of structured and unstructured data. In the process, the data analyst:
- has the technical skills to detect algorithms and identify, categorize, and store data from multiple seemingly dissimilar sources;
- compiles figures into visuals to convincingly present research; may work with developers to refine data analyzing software even further;
- analyzes and models complex datasets and draws insights from the information available to solve problems for an organization or support its direction; and
- uses several computational, statistical, and technology tools.
In today’s market climate, students can apply this group of skills across business, e-commerce, finance, government, healthcare, science, technology, and telecommunications in the following types of roles:
- Operations research analyst
- Data officer
- Information officer
- Software developer
- Actuary
- Mathematician
- Statistician
Application Requirements
Applicants interested in UNO’s graduate certificate in Data Analytics must:
- Complete an online application;
- Send an official transcript from a bachelor’s degree–granting institution to the Office of Admissions; and
- Have previously completed an undergraduate course in statistics.
Fast-Track Your Career with a Graduate Certificate in Data Analytics
The amount of data available to businesses doubles every year. UNO’s graduate certificate in Data Analytics adapts your interest in numbers and statistical knowledge to a highly sought-after position and equips you with the technical skills needed to navigate through the rising tide of information. To learn more about the graduate certificate in Data Analytics, contact the Graduate School at 504-280-6237 or fill out a request form.
Student Learning Outcomes
Student Learning Outcomes specify what students will know, be able to do, or be able to demonstrate when they have completed a program of study.