No matter the type of business or organization, the importance of data and having employees skilled in data literacy grows by the minute. In fact, data is the language of business.
Boise State University’s Online Master of Business Administration in Business Analytics provides students with the tools to make data-informed decisions that lead to impactful, real-world results.
Increasing data literacy skills and confidence by using analytical tools to solve financial problems is a key part of the design of the business analytics emphasis.
The emphasis area includes three courses — Digital Marketing Management, Financial Analytics and Modeling and Data-Driven Decision Making.
- Digital Marketing Management: With an emphasis on the tools of digital marketing and how to combine them for maximum effect, this course connects those tools to common marketing metrics to monitor promotion effectiveness and maximize return-on-investment (ROI).
- Financial Analytics and Modeling: Concentrating on bringing classic financial theory into practical settings, this course covers the cost of capital, financial statement modeling, valuation, portfolio models and the efficient set, option pricing and bonds. It also gives students a framework to enhance their analysis of complex financial issues faced by real-world managers and to become proficient in solving those challenges with financial modeling.
- Data-Driven Decision Making: This course introduces data analysis techniques in managerial decision-making processes with a focus on uncovering patterns in data and identifying underlying drivers. It also explores sources of structured and unstructured data for business intelligence and examines tools to clean and leverage data for actionable insights and descriptive and predictive analytical methods, including visualization and machine learning.
What is data literacy?
Data literacy is the use of data in a meaningful way through exploration, understanding and communication. Businesses expect employees at every level to have basic data literacy skills.
A company culture focused on data literacy can lead to better decision-making, clearer understanding of ROI and attribution, increased employee satisfaction and retention and better customer experience and satisfaction.
Data-driven organizations produce data-literate employees who contribute more to their roles and help businesses sharpen their competitive edge in an aggressive global economy. There are two types of data literacy skills: technical and non-technical.
Non-technical skills
- Critical thinking: Question your assumptions, using logic to work through problems and diversifying where you obtain information.
- Research: Develop this skill by learning how to evaluate sources, narrow your search and spot implicit or explicit biases.
- Communication: Practice active listening, work on your public speaking and seek feedback from trusted peers can help you sharpen your communication skills.
- Domain knowledge: Expand your data knowledge by reading books, following blogs and researching trends to stay on top of a rapidly-evolving business world.
Technical skills
- Analysis: Data analysis that includes collecting, formatting, cleaning and processing data and interpretation.
- Visualization: The graphical representation of information in different forms, like charts, graphs and maps.
- Management: The process of collecting, vetting and storing data, includes data cleaning, mining and warehousing.
- Mathematics: Learning about statistics, linear algebra and calculus. Having even a conceptual understanding of each will further your knowledge.
- Programming languages: Key to building dashboards or complex data analysis programs, including Python, R and SQL.
Data Analytics vs. Business Analytics
So, what’s the difference between data analytics and business analytics? The two are often confused. Business analytics is the exploration of an organization’s data, with a focus on applying statistical analysis techniques to drive innovation and financial performance.
Data analytics is the broader process of collecting and examining raw data, like sales figures, market research, logistics or transactional data, to recognize patterns in a dataset that may indicate trends, risks, or opportunities.
The importance of data literacy will likely increase over time, so having the necessary skills to apply its concepts has long-term value.
More About Boise State’s Online MBA in Business Analytics
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