A deep dive into data analytics

What is data analytics and what career paths are available or opening up in this field?

Melissa Zgola, faculty chair for the master’s-level IT programs in Capella University’s School of Business and Technology, provides answers to some common questions about data analytics, plus skills you need to be successful.

Q. What is data analytics?

A. Data analytics is the science of collecting, organizing, and analyzing very large sets of data in order to identify patterns and draw conclusions.

For example, let’s say that the executives of a national fast food chain are looking to add a new fresh food item to their menu. A data analyst could collect and examine data on all fast food purchases over the past 5 years. In doing so, they could identify trends and patterns in the data that would suggest the most popular fast food items being sold by competitors. This analysis can help executives make decisions about the best new food item for the menu. If examined a bit further, the data could also help executives choose specialty food items for different demographic regions.

Data analytics is used in many different industries to support initiatives that are most important to an organization and to help guide critical decisions.

Q. What are the differences between data analytics and business analytics?

A. Business analytics and data analytics are often used interchangeably throughout the industry. There is great debate and much diversity of opinion about the distinctions because there is great similarity between the two functions. Both business analytics and data analytics involve the collection and analysis of data, and both conduct their analysis in order to improve an organization’s effectiveness and decision-making.

However, business analysis focuses much more on the functions, processes, operations, and overall architecture of an enterprise. It is the practice of enabling change by identifying business needs and determining solutions to those business problems. Business analysts work across all levels of the organization and can be found focusing on things such as strategic planning, translating project requirements, and developing policy all in an effort to support an organization’s ongoing technology and process maintenance.

Data analysis focuses on the process of collecting, cleaning, analyzing, reporting, and presenting data. Analysts in this area break down the data and take the necessary steps involved in converting raw and messy information into clean and usable knowledge. Data analysts focus on the tools and statistical methodology and can often be found working with management, translating data, interpreting results, and testing hypotheses.

Where a business analyst might attempt to predict future business performance using past business performance, a data analyst would compare an organization with its competitors, identifying trends and patterns that could impede or encourage success.

Q. Who would be interested in studying data analytics?

A. Analytics is such a diverse field. People are joining the field from a large number of different areas and backgrounds. We are seeing self-motivated and curious individuals who are analytical by nature and have an interest in helping guide strategic decisions for organizations.

Our students typically enjoy the investigative nature of analyzing data and the creative process involved in identifying innovative solutions for organizations.

Q. What characteristics or traits should someone in data analytics have to be successful?

A. A fundamental knowledge of technology, programming, and statistics is necessary for someone to succeed in this field, but soft skills are equally as important.

Some of these include:

Curious and self-motivated. Constantly asking questions and persistent in finding answers.
Creative and flexible. Able to consider new and fresh perspectives to solving problems.
Strategic and collaborative. Recognizing the importance of working as a team to solve issues from a big-picture perspective.
Effective communicator. Able to translate numbers into actions and tell compelling stories that lead to success.

Q. Capella offers a Master of Science in Analytics. What is the focus of the program?

A. Capella’s Master of Science in Analytics degree prepares data analytics professionals to work with, understand, and transform data to develop solutions that resolve applied problems while effectively providing insights and communicating results to the organization.

Throughout the program, students develop skills in data sources, statistics, data mining, applied analytics and modeling, leadership reporting, forecasting, and visualization in order to solve problems within a variety of industry domains. Additionally, students strengthen their collaboration, communication, presentation, and negotiation skills.

Several unique and innovative components have been built into the program to prepare students for the real world of analytics.

The data analyst virtual internship, developed in conjunction with industry leader SAS, allows students to take on the role of a data analyst working for a major health care system. In each course, students address real-world problems specific to health care. From resolving unclean data issues and analysis of unstructured data to creating solutions based on analysis of big data sets, students will be asked to tackle challenging interactive activities and will experience first-hand the complexities of investigating complex data sets, choosing analytic tools, and presenting findings to leaders in a succinct, powerful visualization.
Creativity is an important attribute for any successful data scientist, as they are often asked to address complex problems in unique and creative ways. This is also an attribute that employers look for in their potential candidates. Throughout the program, students will encounter spontaneous real-time analytics exercises that call for inventive strategies and solutions. These impromptu assessments are designed to help develop students’ creativity and offer experience working on today’s most current and relevant analytics puzzles.
Students can also earn an SAS certification along with their degree. The coursework provides the skills and knowledge needed to take exams for four different SAS certifications, plus vouchers are provided to take the exams for free: SAS Base Programmer for SAS 9, SAS Certified Advanced Programmer for SAS 9, SAS Certified Statistical Business Analyst Using SAS 9, and SAS Certified Predictive Modeler Using SAS Enterprise Miner 13.

Q. What types of careers are available for data analysts?

A. The related job titles below represent a range of options for professionals with this degree and specialization. While some titles represent entry-level positions, others may require previous experience in the field.