Although data science is a field unto itself, the popularity of its tools and techniques means data analysis is commonly used across fields and industries. From healthcare analytics to business intelligence, investment in data analytics has broadened career paths. For example, business analytics is within the field of data analytics yet has a separate career trajectory.
A career as a data scientist differs from one as a business analyst in terms of the tools used and the expected work outcomes. While data scientists use programming and machine learning to gather insights from diverse data collection, business analysts use data analytics technologies to make better business decisions. Choosing a career as a data scientist versus a business analyst depends on your skills, interests, and industry.
What is Business Analytics?
Business analytics is the use of data analytics technologies to predict the likely future of a business. Business analytics, like business intelligence and prescriptive analytics, uses data to make informed decisions. Automation and machine learning enables business intelligence tools to crunch business data and search for patterns and trends that can be used to improve a company or client profile. This data includes information from all aspects of the business, such as sales data, advertising analytics, and consumer feedback. Data is stored in a database, such as a data warehouse, that can organize and clean data from multiple sources and structures.
In this era of data culture, business analysts use a company’s historical data to develop short and long-term goals and analyze the current success of a brand, product, or marketing campaign. They also use the data to generate reports and analyses geared toward improving the business outlook. Business analytics is also concerned with internal operations and the business’s public face and consumer base.
Business analytics plays an essential role in analyzing the business-employee relationships and using data governance tools and protocols to manage information accessibility.
The Difference Between Data Science and Business Analysis
The main differences between data science and business analysis are the purpose of study, the type of data collected, and the analysis tools. As a general field and industry, data science includes studying data using various data collection tools and techniques. Data scientists collect and analyze data relevant to their industry and field of study using the appropriate tools for the field and data type.
For example, data scientists in finance and investing collect and analyze economic or financial data using statistical software and algorithms. Data scientists in other fields or industries would likely use different data types and analytics tools.
Business analysts collect and analyze data specific to a business and are concerned with internal operations, products and services, and business market or industry. Data analysis is used to develop insights about company health and prospects and to suggest improvements to internal or external systems.
Business analysts use predictive analytics to develop projections and expectations. For example, a business analyst may use predictive analytics to develop quarterly sales goal projections. Business intelligence (BI) tools allow business analysts to share this information with key stakeholders to improve sales, daily operations, marketing, or business decision-making.
Choosing a Career as a Data Scientist vs. Business Analyst
Building a career as a data scientist allows students and professionals to explore various data and analytics types and tools. In contrast, a career in business analytics is more narrowly focused.
Choosing a career as a data scientist is a great option for data science students who want to explore various tools and techniques and develop a broader, generalized skillset. Data science students and professionals with a passion for problem-solving using business intelligence tools and data-driven decision-making should consider a career as a business analyst.
Business analysis is an applied science valuable across industries. But most business analysts choose management consulting firms, finance and investing, and information technology. Aspiring business analysts must determine the type of business that reflects their experience, training, or research interests.
Data science students can tailor their training toward a specific type of career. For example, a certificate course in financial technology benefits business analysts interested in finance. In contrast, training in data analytics technologies is more helpful in pursuing a career as a business analyst consultant.
Want to Start a Career as a Business Analyst?
Noble Desktop's data science classes include bootcamps and certificate programs that teach aspiring business analysts the skills to build successful careers. For example, the Data Analytics Certificate offers data collection, analysis, and visualization training for future business analysts and information technologies. The Data Analytics Technologies Bootcamp engages beginner students through hands-on experience with the industry's most popular data analytics tools, such as Tableau. Aspiring business analysts can also check out Noble Desktop's live online data analytics courses to stay updated with the latest business intelligence tools and technologies!