Technology advancements and ubiquitous computing are spawning massive amounts of data, and we are now learning to utilize it to make better decisions. Consequently, we are seeing a significant rise of mathematicians, computer scientists, and statisticians in various industries working to make sense of all this data using analytics tools and techniques. There is no branch of business, science, and engineering left untouched by data analytics.
- About less than 0.5% of all data is analyzed and used
- By 2025, the data science analytics sector in India alone is estimated to grow by 7x to reach $16 billion
- Currently, the US leads the data science job market creating a demand for 200,000 data scientists in the next year
- 1.8 megabytes of new data is created every second—by every human on the planet
- Every second, 70,000 search queries are performed on Google, and 1.2 trillion searches are done each year
The advent of big data spurred the demand for data scientists across the globe. Their role in every industry has emerged because of the increase in the breadth and depth of data being analyzed and used. Also, emerging trends in Artificial Intelligence are creating even more demand for data analytics and science professionals.
Here are the top trends that will transform businesses in upcoming years:
- Augmented data management
- Data fabric
- Explainable AI
- Augmented AI
- Natural language processing/conversational analytics
- Memory servers
- Continuous intelligence
Let us begin our learning on the difference between a data analyst and a business analyst in terms of the career front.
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How to Choose Between a Career as a Data Analyst and Business Analyst
If you love working with data, you may find yourself at a crossroads when it comes to choosing a professional career between a data analyst and a business analyst. Just how do you choose between becoming a business analyst or data analyst? The good news is that both roles let you capitalize on your love for data. Then, what is the difference between a data analyst and a business analyst?
Read more: How to Build a Successful Data Analyst Career?
Data business analysts are all about analyzing data sets and uncovering the trends to use in making an informed decision in organizations.
On the other hand, business analyst professionals are critical thinkers, problem solvers, and excellent communicators. These professionals have a detailed knowledge of their organization's objectives and processes so they can evaluate performance, identify inadequacies, and advise and implement solutions.
If your question is, can a data analyst become a business analyst? Well, a data analyst can, over time, switch to the role of a business analyst. The same is true in reverse.
Let us now look at the difference in roles of a data analyst and a business analyst.
Business Analyst vs. Data Analyst: Roles
Both business analysts and data analysts are involved in the analysis of data. Business analysts can make strategic business decisions by using data. A data analyst collects data, manipulates it, identifies useful information from it, and interprets it, and transforms this into digestible information.
When a business requires to solve a current or future problem, it's a business analyst's job to help facilitate a solution.
Business Analysis involves many tasks like:
- Defining business case
- Analyzing business requirements
- Understanding business requirements
- Project management and development
- Validating solutions
- Making informed decisions along with stakeholders
- Performing quality testing
- Reviewing work habits, interacting with colleagues, and keeping up with changing technologies
Data analysts spend most of their time spending researching data and creating reports that show insights. The professionals present the findings to the respective teams. The individuals work more independently than business analysts.
On any given day, a data analyst might be:
- Scrubbing data
- Producing and maintaining reports for different departments
- Creating both internal and client-facing reports
Next, in terms of the skills and prerequisites let us look at the business analyst vs data analyst differences.
Business Analyst vs. Data Analyst: Skills and Prerequisites
Business analysts typically have an undergraduate degree in a business-focused field such as business administration, finance, or economics.
The requirements of business analysts include:
- Expertise with data research
- Mathematical mindset and expert analytic capabilities
- The ability to investigate and identify critical data
- Proven SAP skills
- Strong Microsoft Excel, Word, and PowerPoint skills
- SQL proficiency
- Project management experience
- Strong communication skills
Data analysts, on the other hand, are more numbers-oriented. These professionals often have an undergraduate degree in a STEM category with experience in computer programming and modeling and predictive analytics experience. Having a Master's degree is helpful.
The required skills of data analysts include:
- Pro in analytical skills, intellectual curiosity, and reporting accuracy
- A proper grasp on data mining techniques
- Fluency with emerging technologies, data frameworks, and machine learning
- SQL/CQL, R, and Python experience
- Knowledge of agile development methodologies
Let us next look at the differences in responsibilities of business analyst vs data analyst.
Business Analyst vs. Data Analyst: Responsibilities
Data analysts help companies by analyzing data and drawing actionable insights to present to business stakeholders. Data analysts also apply their expert skills to provide competitive analysis or to identify business or market trends.
They work with:
- IT departments
- Data management teams
- Data scientists
Data analysts' responsibilities include:
- Deriving insights from data using statistical techniques
- Database management
- Optimizing statistical efficiency and quality
- Acquiring data from primary or secondary sources
- Identifying, analyzing, and understanding trends or patterns in complex data sets
- Filtering data and locating and correcting code issues
- Working with management to prioritize business needs
- Defining process improvement opportunities
Business analyst responsibilities depend on the industry, but the main objective of their role is analyzing and deriving insights from data to make informed business decisions.
Business analysts' responsibilities include:
- Analyzing large amounts of complex data
- Identifying areas that need improvement
- Addressing business needs
- Working with internal teams and 3rd parties to escalate and resolve issues
- Analyzing data to evaluate the emerging trends
- Recommending possible solutions
Next, let us take a look at the difference between Business Analyst vs Data Analyst in terms of the career path.
Business Analyst vs. Data Analyst: Career Path
A bachelor's degree in a related field is needed for entry-level data analysts. For senior positions, hiring managers often prefer a graduate degree or a Master's degree in analytics.
While data analysts and business analysts both use data, the primary difference lies in what they do with it. Business analysts work with data and explore it primarily to make better business decisions. On the other hand, data analysts work with data that is related to the logistical databases of an organization.
Let us now look into the salary comparison of Business Analyst vs Data Analyst in terms of salary.
Business Analyst vs. Data Analyst: Salary Comparison
You must have pondered over the question: A business analyst vs. data analyst, which is better? The average data analyst's salary could go up to $72,250 per year. It also depends on the company, job role, and geographical location matters.
A data business analyst's salary is typically higher, averaging $78,500/year. Again, the candidate's skillset, profile, company brand, and location factor in. More qualified can hold senior positions with salaries up to $110,000/year. Therefore, a business analyst vs. a data analyst's pay is variable.
We hope that the article was useful in helping you understand the data analyst vs business analyst differences. Since both fields deal predominantly associated with data, you have to accurately evaluate your skillset and the subjective pros and cons of each profession before choosing one. However, since the two have some things in common, switching from one designation to the other at any stage is not difficult either.
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