Thriving in the Era of Data: A Deep Dive into Data Analytics and Business Analytics Careers

Mark Talmage-Rostron
November 30, 2023 · 10 min read

We live in the era of data. Every day, humanity generates an incredible two-and-a-half quintillion bytes of data. Google alone processes more than 20 petabytes of data every day, which includes around 3.5 billion search queries. As if these figures weren't astonishing enough, the OECD report reaffirms that data analysis skills are now more crucial than ever and continue to be in high demand in a variety of industries. But what is the difference between data analytics and business analytics?

Defining Data Analytics and Business Analytics

Business analytics and data analytics are related fields that focus on extracting insights from data. However, although they share common ground, they wholeheartedly differ in their scope, objectives, and applications within an organization.

Data Analytics (DA) refers to the process of examining, cleansing, transforming, and interpreting large sets of data to uncover valuable insights, patterns, and trends that can aid in making informed business decisions or solving problems. It involves various techniques and tools to explore and analyze datasets, extract meaningful information, and derive conclusions or predictions. Its primary purpose is to discover useful information from data which can be used for descriptive analytics, predictive analytics, and prescriptive analytics.

On the other hand, Business Analytics (BA) involves the use of statistical analysis, data mining, predictive modelling, and other analytical techniques to gather, interpret, and transform data into actionable insights. Its primary objective is to identify patterns, trends, and relationships within data that can help organizations make informed decisions and improve their performance across various functions.

These fields share an overlap, as illustrated in this simple visual comparison.

The devil is in the data

Data plays a pivotal role in making informed business decisions due to several reasons. It provides factual evidence and insights based on real information rather than intuition or assumptions, it helps businesses to identify trends, patterns, and correlations within their operations, market, or customer behavior, and it allows businesses to understand customer preferences, buying patterns, demographics, and sentiments to tailor products, services, and marketing strategies to meet customer needs effectively, thereby improving customer satisfaction and loyalty. That said, there are differences as to how data is used in DA and BA.

DA primarily deals with the analysis of raw data to uncover patterns, trends, and insights and involves processes such as data cleaning, transformation, and statistical analysis to derive meaning from datasets, whilst BA has a broader focus on applying data-driven insights to solve specific business problems or improve business processes, because it involves using analytical techniques to drive strategic decisions, optimize operations, enhance performance, and create business value.

Applying BA and DA

Organizations should strive to create a synergy between data analytics and business analytics, as they are interconnected and both contribute to leveraging data effectively for business success, but knowing how to apply one or the other is critical to targeted business outcomes.

DA is more commonly used in various fields, including healthcare, finance, science, and technology, for understanding trends, making predictions, and gaining insights from data. It is foundational in providing the raw material for business analytics. Within these fields, you might encounter job titles such as Data Analyst, Business Analyst, Data Engineer, Data Scientist, or Business Intelligence Analyst. As you gain experience, you could climb the ladder to positions like Senior Data Analyst, Principal Analyst, or Analytics Manager.

BA is specifically tailored to meet business objectives. It's utilized across industries for applications such as market analysis, customer segmentation, risk management, supply chain optimization, performance improvement, and strategic planning.

Is BA more important than DA?

The adoption of business analytics and data analytics has been steadily increasing across industries, but specific percentages of businesses using these practices might vary widely based on industry, region, company size, and other factors.

A significant percentage of businesses have been utilizing some form of data analytics. The adoption rate has been growing steadily across industries, with many companies recognizing the importance of leveraging data for insights and decision-making.

In a survey conducted by NewVantage Partners in 2021, 97.2% of executives reported investing in or planning to invest in big data and AI initiatives. Another survey by Gartner in 2020 indicated that around 54% of enterprises had already invested in big data analytics, showing a consistent trend of adoption.

In comparison Business Analytics adoption might be slightly more prevalent in comparison to Data Analytics, as BA involves using data insights for strategic decision-making and solving business problems. In fact, a survey conducted by Dresner Advisory Services in 2021 revealed that about 60% of respondents said their organizations considered Business Intelligence and Analytics as critical, or very important to their business.

Skills shortages prevail in Business Analytics and Data Analytics

Whilst it has been identified that BA and DA are two completely different practices that drive business growth and profitability, they do share common ground in that both areas lack skilled individuals to get the job done. The shortage of skilled professionals in Business Analytics and Data Analytics is an ongoing challenge, and efforts to bridge this gap through education, training, and collaboration between academia and industry are crucial for meeting the increasing demand for these skills.

In a recent Forbes article, it was stated that as the demand for data expertise has grown, so too has the gap between the number of people with these skills and the comparatively huge number of roles to fill. The article went on to outline that this global shortage has significant consequences for all industries. By 2030, the labor shortage in the technology, media and telecommunication sector could cause the U.S. to lose roughly $162 billion, according to a report by Korn Ferry. Globally, the digital skills gap could result in 14 G20 countries losing $11.5 trillion of cumulative gross domestic product growth, Salesforce estimated.

Job Growth in Data Analytics and Business Analytics

The Bureau of Labor Statistics projects analytics jobs will grow by about 35% by 2031, as every sector understands the power and importance of data for driving business success. A study by Accenture found that 79% of executives feel that companies not embracing data analytics will lose their competitive position, emphasizing the rapid growth in open job roles in this area.

The skills shortages in Business Analytics and Data Analytics share many similarities due to their interconnected nature, but there are also nuanced differences in the specific skill sets required for each field, which might influence the shortages differently. Both fields require strong analytical abilities, including critical thinking, problem-solving, and the capability to derive meaningful insights from data. However, in business analytics, there might be a greater focus on applying analytical insights to solve business problems and make strategic decisions.

Technical skills

Business Analytics: While technical skills are also important in business analytics, there might be a higher emphasis on skills related to using data insights for strategic decision-making, understanding business processes, financial acumen, and domain-specific knowledge.

Data Analytics: Skills in data cleaning, manipulation, statistical analysis, data visualization, and proficiency in tools like Python, R, SQL, or data mining techniques are crucial in data analytics.

Communication and business acumen

Business Analytics: Strong communication skills are particularly important in business analytics as professionals need to translate complex data insights into actionable recommendations for business leaders. Understanding business processes, market dynamics, and financial implications of decisions is crucial.

Data Analytics: While communication skills are also vital in data analytics, there might be a slightly higher emphasis on technical proficiency and data manipulation compared to business-specific knowledge.

Advanced analytics and AI

Business Analytics: While these skills are valuable, there might be a greater emphasis on using existing data insights for strategic planning and decision-making rather than developing advanced analytical models.

Data Analytics: Proficiency in advanced analytics techniques like machine learning, predictive modelling, and AI applications might be more emphasized in data analytics due to its focus on extracting insights from vast datasets.

Industries with high demand for data and business analysts

Data and business analysts are in high demand across various industries, with banking and finance being one of the most prominent. Data is everywhere, and every sector recognizes its significance in driving business decisions and success.

Data and business analysts can be found not only in IT departments but also across functional teams. This is due to the growing organizational trend of DataOps, which involves the integration of data specialists—data analysts, data developers, data engineers, or data scientists—within the company's structure to collaboratively develop data flows and facilitate the continuous use of data across the organization.

To excel in data analytics or business analytics, professionals need to develop certain core skills:

  1. Advanced analytical skills and statistical knowledge

  2. Data management and data visualization expertise

  3. Proficiency in programming languages like R, Python, or SQL

  4. Strong problem-solving and critical-thinking abilities

  5. Effective communication skills for relaying complex data insights to colleagues and stakeholders

What can be done to bridge the growing Business Analytics skills gap?

As with most vocations across the world that are experiencing skills shortages in the workforce, education is the key to closing the gap. Universities will play a pivotal role in bridging the business analytics skills gap by offering specialized programs, curriculum adjustments, and fostering an environment that aligns with industry needs. Courses and resources are readily available to help aspiring analysts develop these skills, such as the Google Data Analytics Professional Certificate or other online learning platforms.

Specialized Programs: Universities can develop dedicated degree programs or courses in business analytics, data science, or related fields. These programs should cover topics such as data manipulation, statistical analysis, predictive modeling, machine learning, data visualization, and business acumen tailored to the needs of modern industries.

Hands-on Experience: Integrating practical, hands-on experience into the curriculum through internships, capstone projects, or collaborations with industry partners allows students to apply theoretical knowledge to real-world scenarios. This practical exposure helps students develop practical skills and gain industry experience.

Updated Curriculum: Universities should regularly update their curriculum to keep pace with the evolving technological landscape. This involves incorporating the latest tools, techniques, and trends in business analytics, including AI, big data technologies, and advanced analytics methodologies.

Industry Collaboration: Partnerships between universities and businesses will enable the design of relevant programs, guest lectures by industry experts, internship opportunities, and joint research projects. These collaborations will ensure that educational offerings align with the current needs of employers and provide students with exposure to industry practices.

Professional Development and Certifications: Offering continuous education programs, workshops, and certifications geared toward working professionals helps bridge the gap for individuals already in the workforce. These programs allow professionals to update their skills or transition into the field of business analytics.

Encouraging Analytical Thinking: Universities can foster analytical thinking and problem-solving skills among students across disciplines. Incorporating analytical thinking into general education courses encourages a broader range of students to develop these essential skills.

Supporting Research and Innovation: Universities conducting research in areas like data analytics, AI, and machine learning can contribute to advancing knowledge and practices in the field. Research outcomes can also inform curriculum updates and industry best practices.

By implementing these strategies, universities can significantly contribute to narrowing the business analytics skills gap, ensuring that graduates are well-equipped with the relevant knowledge and skills demanded by the industry, and thereby preparing a workforce ready to excel in the field of business analytics.

Universities can also help many organizations to find top talent or upskill their workforce as there is an urgent need for data analytics skills, and the talent availability is limited. The World Economic Forum reports in the Future of Jobs 2023 Report that Big Data Analytics is one of the top drivers of job growth globally. According to business leaders in Fintech and other high-growth sectors, one of the biggest challenges in recruitment is finding qualified talent for data analytics positions. That’s why highly sought-after candidate for thousands of global jobs are signing up for programs to gain the skills and expertise required to fill those roles and break into the lucrative field of Business Analytics.

Time to master Business Analytics

There isn’t a one-size-fits-all educational path into analytics. Depending on your preference, you can consider bachelor’s or master’s degrees, specialized certifications, or even online courses to kickstart a career in data or business analytics.

A Master's degree is the new norm for analytics careers and an essential requirement for advancement. With an MSc in Business Analytics graduates can expect to earn substantially higher median salaries than those with only undergraduate degrees or certificates, and they can unlock access to the highest-paying and most influential analytics-related positions.

To help learners to get the job done, a Master of Science in Business Analytics (MSBA) program provides the skills to analyze data and make strategic decisions which is critical to success in the modern workplace. The MSc in Business Analytics from Nexford empowers learners with the technical and business skills needed to lead organizations and unlock the true potential of data.

But remember, mastering Business Analytics is an ongoing journey that requires dedication, continuous learning, practical application of skills, and a proactive approach to staying updated with the evolving landscape of data-driven decision-making.

About the author
Mark Talmage-Rostron
Mark Talmage-Rostron

Mark is a college graduate with Honours in Copywriting. He is the Content Marketing Manager at Nexford, creating engaging, thought-provoking, and action-oriented content.

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