There is a lot of money in big data. As one of the fastest-growing industries in the world, companies are attempting to squeeze as much as they can out of the data they have so they can make more money and stay ahead of the competition. It is estimated that the market for big data will grow six times faster in the coming years than the general IT market.
To take advantage of the growing need for professionals skilled in big data and data science, it is recommended to earn one of the following types of online master’s degrees:
#1 Master of Science In Data Science
A master’s degree in data science helps students and professionals interested in a big data career to gain the technical, analytical and managerial expertise that are needed to address the many practical problems in the modern world that is driven by data.
In a graduate degree program in data science, you will gain the vital skills that are needed to succeed in a variety of data-intensive positions. Students learn how to use relational and document complex database systems and analytics software that is built upon such languages and systems as Python, TensorFlow and R. This type of degree program will teach you how to make highly trustworthy predictions with machine learning and traditional statistics.
Common goals of a master of science in data science are:
- Be able to articulate analytics as a major strategy in data science
- Become skilled in transforming data into insights that are actionable
- Develop sound and robust analytics solutions that are statistically sound
- Show strong leadership to data science teams
- Formulate and manage data science plans that will address common business issues
- Review constraints on how data is used in different industries
- Learn how to assess data lifecycle and structure
Typical course requirements for a master’s in data science degree include:
- Math for data scientists
- Statistical analysis
- Introduction to data science
- Decision analytics
- Practical machine learning
- Database systems and data preparation
- Project management in data science
Many data science master’s programs have specializations as well, which can vary from program to program. Common specialties are in analytics management, data engineering, and analytics and modeling. Depending upon the selected concentration, additional course requirements could be:
- Foundations of data engineering
- Analytics application development
- Regression analysis and multivariate methods
- Generalized linear models
- Accounting and finance for analytics managers
- Business leadership and communications
#2 Master of Science in Business Analytics
The purpose of business analytics is to convert big data into intelligence that can be acted upon by an organization. Business analysts with a master of science in business analytics will use many statistical and quantitative techniques, predictive models and computational tools as well as knowledge in finance and economics to make decisions that are driven by data intelligence.
Students commonly develop high levels of expertise in data mining and visualization, statistics, modeling, optimization and simulation on sets of data.
Unlike a business intelligence degree, which is commonly focused more upon previous business performance, a business analytics master’s degree is concerned more with predictive and prescriptive techniques to gauge what businesses should do in the future. A business analytics degree often centers on data mining to achieve specific business goals, such as earning higher profits.
Some of the common courses you will take in a graduate program in business analytics are:
- Data analytics programming
- Predictive modeling
- Decision analysis
- Text analysis
- Data mining
- Applied analytics
- Analytical decision modeling
- Database management
- Stochastic control and optimization
- Learning structures and time series
Some programs also will require you to take courses that are more specific to finance, including:
- Financial management
- Marketing analytics
- Supply chain analytics
- Pricing and revenue management
- Social media analytics
- Quantitative training
- Financial technology
#3 Master of Science in Business Intelligence
Business intelligence is defined as the effective extraction of insights from large amounts of raw data to help with business decisions. Business intelligence or BI is often involved in examining data from past business actions, and developing consistent matrix sets to measure previous performance and to guide planning for businesses in the future.
Today, business intelligence is able to leverage many technologies, softwares and processes to extract, identify, combine and analyze all of the data that can be produced by a day to day business. Some of the vital technologies of BI include dashboard development, analytical processing online, querying, data mining event processing, management of business performance, predictive analytics, benchmarking and reporting.
One of the hot trends in BI is self-service business intelligence and analytics. Self-service BI allows the business user to design/deploy their own analyses and reports in a supported and approved tools and architecture portfolio. The IT department for the organization sets up the data warehouse and gets the reporting tools and queries up and running, but does not have to be involved in all of the analysis.
The greater demand for data visualization on a self service basis and new business discovery tools reflects the increase in data-savvy knowledge professionals that have the skills to dig into data, instead of having someone in IT handle it.
The curriculum of a BI master’s program may include these courses:
- Foundations for business intelligence
- Concepts and practice of DSS modeling
- Enterprise data
- Introduction to data mining
- Predictive analysis
- Business analytics for business intelligence
- Database management theory
- Business process modeling
- Critical performance management
- Special topics in business intelligence
#4 Master of Science in Statistics and Data Analytics
The vast increase of data that is coming from sensors, the Internet, businesses, surveys, medical tools, social media and others is creating more need today for professionals that are skilled in data analytics and applied statistics. It is estimated there will be up to a 50% increase in the need for professional statisticians in the coming decade.
A graduate degree in statistics and data analytics will provide students with the statistical foundation and thinking skills that are needed to tackle complex business data problems. Students in this type of graduate program will learn a broad number of statistical methods and computational tools that will equip them with the skills to work in many industries, including healthcare, manufacturing, government, finance and general business.
Some of the courses that may be required in a statistics and data analytics degree program are:
- Quantitative methods for business analysis
- Decision analysis and production management
- Decision support systems for building business intelligence
- Statistical methods for business analytics
- Logistics systems management
- Demand and forecasting management
- Topics in production and operations management
- Global supply chain management
- Management and control of quality
#5 Master of Science in Computer Science
A master of science degree in computer science can also be a good background for a big data career. Students in this type of graduate program will develop skills in four core computer science areas that are relevant to data science:
- Data visualization
- Machine learning
- Data mining
- Cloud computing
This master’s degree will also provide you with highly specialized statistical, algorithmic and systems expertise so you can acquire, store, access and analyze large quantities of heterogeneous and real time data in such industries as energy, environment, healthcare, medicine, manufacturing and education.
Some of the courses you may take in a computer science master’s program include:
- Foundations of artificial intelligence
- Analysis of algorithms
- Database systems
- Advanced big data analytics
- Theory and algorithms
- Probabilistic reasoning
- Information retrieval and web search engines
- Data integration
With the great demand for workers skilled with analyzing and making business decisions with large amounts of data, earning one of the above master’s degrees can be the ticket to finding a job in the very lucrative and rewarding big data industry.
Did you know BusinessStudent.com recently released it’s list of 160+ Best Online Master’s Programs Report for 2018? Many graduate data science, analytics and technology programs are available many without the GRE requirement.
About the Author
Joseph Pickett is Senior Jobs Editor at Business Student.com. He writes on careers, trends and other topics in business and technology and many other matters for the mid-level career professional. Let’s just say he breathes tech.
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