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College of Information Technology and Engineering

Data Analytics Degree Specializations: Finding Your Niche in the World of Big Data

May 22, 2024
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College woman on laptop working on big data for future career.

We have officially entered the era of big data, and with it comes a new set of expectations for how businesses will function and how professionals will navigate the evolving workforce.

Data analytics represents a rapidly growing field, and there is no denying that employers are eager to find workers with strong data-based competencies and, in general, a data-driven mindset.

Employers have certain expectations for how data-driven professionals will uncover actionable insights and how they will convey these findings. Targeted applications may call for data analysts to develop specific skill sets and a thorough understanding of their sectors’ nuances and challenges.

Degreed analytics programs promise to bridge the gap. All data analytics students must develop foundational skills such as programming languages and database management. Still, through specializations, they can hone in on applications that align with their unique career goals. Continue reading to learn what these specializations involve and how they relate to top careers in data analytics.

What Is Data Analytics?

Data analytics translates raw data into meaningful insights by leveraging advanced computer systems or artificial intelligence. The term ‘data analytics’ is broad in scope, encompassing the vast array of tools, technologies, and methodologies that play into these efforts to collect and examine data.

Although it can take many forms, data analytics is a goal-driven practice that relies on large data sets (and the patterns they uncover) to drive improved decision-making. Often, this is broken down into distinct phases or categories, such as:

  • Descriptive analytics – Accurately conveying what has occurred
  • Diagnostic analytics – Determining why something happened
  • Predictive analytics – Forecasting what might happen in the future
  • Prescriptive analytics – Recommending steps to be taken in the future

How Data Analytics Differs from Data Science & Business Analytics

Practices such as data analytics, data science, and business analytics are often confused and misused. Though these concepts hold much in common, numerous distinctions are worth noting.

Data science: Leverages statistical analysis to extract meaningful insights of great value in complex applications. Often centered around raw, unstructured data, this practice identifies patterns within large data sets, typically via data mining, data cleaning, and predictive modeling.

Business analytics: This field applies data analytics tools and techniques to the business sector, drawing on the power of data-driven insights for strategic planning. The actionable insights from business analytics initiatives promote a better understanding of consumer behavior and can be leveraged to improve operational efficiency.

Data analytics: Focuses on visualizing and interpreting data sets, typically to address specific questions or concerns. Many data analysts develop niche understandings to fulfill particular roles within their organizations. As such, analytics careers can be highly compelling for those who enjoy working with data but feel drawn to specific fields.

Exploring 10 Degree Specializations in Data Analytics

As the roles in data analytics expand, so do the opportunities to seek a targeted skill set tied to specific sectors or applications. The right choice can provide valuable preparation for a rewarding career in data analytics, but first, it’s important to understand which options are available if seeking a data analytics degree online.

Below, we have identified 10 of the most notable specializations within the broad field of data analytics, along with career opportunities that these specializations can promote.

Data Science

We have already outlined the primary differences between data science and data analytics, but these practices are often closely aligned. Because data analysts and data scientists must develop similar competencies (such as mastering multiple programming languages), training in one area can translate to job opportunities within the other. Plenty of successful data scientists begin as data analysts but eventually shift their focus to predictive modeling.

Machine Learning

Machine learning drives powerful automation opportunities, which, in turn, can help organizations make sense of today’s vast data sets. As a branch of artificial intelligence, machine learning empowers systems to uncover patterns and learn from data, often with minimal human guidance or interventions.

The result? Greater efficiency and scalability, plus the chance to uncover trends or patterns that might go unnoticed by humans. Some data analysts design or implement ML algorithms to improve workflows, freeing them up to focus more on the implications of uncovered data insights.

Business Analytics

As we’ve discussed, business analytics represents an applied branch of data analytics in which data-driven insights center around organizational decision-making initiatives. Business analysts must possess a strong technical skill set and elite communication and problem-solving abilities. Their goal is to translate the insights generated through analytics into impactful business decisions. These decisions can result in greater operational efficiency while driving innovation.

Big Data Technologies

Data analytics solutions are crucial within today’s big data landscape. It is through advanced data analytics tools and techniques that we can make sense of the dizzying array of information, which, without effective analysis, would function more like excessive noise. The Forbes Technology Council cautions against assuming that more data is better, as this can leave us “swimming (more like drowning) in data we can’t harness.”

Big data analytics draws on larger volumes of data to ensure that, no matter how vast the data set, valuable insights are made available. This analytics niche heavily draws on artificial intelligence and automated solutions to deal not only with the unprecedented volume of data, but also, its increasing complexity; this means training high-level machine learning models.

Cybersecurity Analytics

Cybersecurity analytics utilizes data proactively to combat today’s most devastating cyberattacks. It delves into the details of traffic analysis, network and system logs, and other resources to identify threats in real-time. The resulting analysis may reveal vulnerabilities or the earliest signs of compromise. All networks produce extensive data, but with cybersecurity analytics, this information can play heavily into threat detection, incident identification, risk mitigation, and more.

Healthcare Analytics

The modern healthcare system produces an unimaginable wealth of data, including everything from transaction information to metrics tracked by wearable devices.

This information could have huge implications for patient outcomes and satisfaction. Furthermore, data-driven strategies promise to help reduce the cost of care. First, however, this ever-increasing scope of healthcare data must be collected, organized, and studied. An analyst must complete these tasks in accordance with ethical standards and current legislation, including, most notably, the Health Insurance Portability and Accountability Act (HIPAA).

Marketing Analytics

Today’s digital landscape provides many opportunities to improve consumer awareness and engagement. Marketing analytics can blend creative aspirations with technical tools. This can lead to impactful outreach, getting consumers more invested in brands or ideas. Success can lead to dramatic improvements in campaign return on investment (ROI), along with greater innovation.

Key tasks completed by marketing analysts involve competitor analysis and customer segmentation. These professionals work closely with marketing teams to determine which strategies are backed by data.

Environmental Analytics

From weather patterns to watershed databases, the natural world produces a wealth of data just waiting to be collected and analyzed. The growing field of environmental analytics strives to utilize this abundant data better while supporting ecological initiatives.

Drawing on a blend of geographical and ecological knowledge, plus advanced skills in statistical analysis, environmental analysts are passionate about their work and determined to make a difference.

Financial Analytics

Dedicated to helping organizations manage their resources, financial analysts collect and organize large volumes of external and internal financial data. This information may produce significant takeaways regarding cash flow, sales forecasting, or even shareholder value. The goal is to drive businesses towards factual, data-driven decision-making rather than relying on intuition.

Sports Analytics

Sports analytics brings data-driven insights to a variety of athletic events and activities. This can play into coaching strategies, injury prevention efforts, fan engagement, and more. As passion-driven professionals, sports analysts understand the power of data to impact every facet of the sports industry.

Choosing the Right Specialization for You

Given the dizzying array of data analytics possibilities, it can be easy to feel overwhelmed when investigating potential careers in data. The sheer scope of this field means that data analytics roles can look dramatically different between sectors or niches.

Ultimately, this decision should come down to a blend of personal interests, skills, and anticipated opportunities. If you are passionate about (or have experience in) a particular field, you could be uniquely positioned to make a difference as you apply data analytics tools and techniques.

Demand may also inform this decision, and while the outlook is strong across the full scope of data analytics, some areas (such as data science) show elevated demand or stronger growth potential. By seeking a data analytics degree, you can gain greater exposure to these in-demand fields and better insight into which career paths you prefer.

Specializing in Data Analytics at Baker

As you look ahead to exciting opportunities in data analytics, commit to building your technical skill set, along with competencies such as communication and collaboration.

One of the best opportunities for developing a strong foundation? Baker College’s Bachelor of Science in Computer Science. This program provides the opportunity to earn a concentration in data analytics.Along the way, you’ll dive into essentials like database administration and database programming. You’ll also find plenty of opportunities to choose electives that align with your interests. Get in touch to learn more about our data analytics degree or, if you’re ready to take the next step, start your application now.

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