Data Analyst, Data Scientist, Business Intelligence Analyst, Business Analyst, who are they?
based on this article.
I have actually been confused by these terms for many years, never found a way to describe them. Thanks to ChatGPT, I ask her to find a way that explains to her granny how these all works. And now, simple as it is, I can understand.
First of all, let’s compare Data analyst and Business Analyst.
Think of it as a flow chain from backend data processing to front-end business decision-making:
1. Data Analytics stands closer to the technical backend. Data analysts process, clean, and analyze raw data (e.g., using Python, SQL) to identify patterns and trends without necessarily focusing on specific business problems.
• Example: A data analyst examines customer purchase data to find trends like peak shopping times.
2. Business Analytics stands closer to the front-end, focusing on how data impacts business decisions. Business analysts use insights from data analytics to solve specific business problems, improve performance, and drive strategy.
• Example: A business analyst uses customer purchase data trends to suggest adjusting marketing strategies or store hours to increase sales.
In a flow:
• Data Analytics: Backend (processing data)
• Business Analytics: Frontend (using data for decisions and strategies)
This creates a connection from raw data handling to actionable business insights.
Now, put them all together.
From raw data processing to business decision-making:
1. Data Analyst (Backend/Raw Data Focus):
• Role: Cleans, processes, and analyzes raw data.
• Tools: SQL, Excel, Python, R.
• Goal: Identify trends, patterns, and basic insights from the data.
2. Data Scientist (Advanced Analytics/Modeling):
• Role: Builds predictive models and uses machine learning to uncover deeper insights.
• Tools: Python, R, Machine Learning libraries.
• Goal: Create advanced statistical models to predict future outcomes or automate data-driven decisions.
3. Business Intelligence (BI) Analyst (Data to Business Insights):
• Role: Transforms data into business-friendly dashboards and reports, provides actionable insights.
• Tools: Power BI, Tableau, SQL.
• Goal: Help organizations understand their data and use it for better decision-making through visualizations and reports.
4. Business Analyst (Business Strategy Focus):
• Role: Uses data and insights to solve business problems and make strategic decisions.
• Tools: Excel, Power BI, or other BI tools.
• Goal: Align data insights with business strategies and recommend actions to improve business outcomes.
Chain Flow:
• Data Analyst → Data Scientist → Business Intelligence Analyst → Business Analyst
This flow represents the progression from raw data processing (Data Analyst) to advanced analysis (Data Scientist), to generating actionable insights (BI Analyst), and finally using those insights to make business decisions (Business Analyst).
Salary
In general, among the roles of Data Analyst, Data Scientist, Business Intelligence Analyst, and Business Analyst, the highest salary is typically earned by Data Scientists. Here’s a breakdown:
1. Data Scientist:
• Highest salary: Due to the advanced skills in machine learning, AI, and predictive modeling, Data Scientists are in high demand.
• Range: $90,000 — $150,000+ per year (can go higher with experience or in certain industries like finance and tech).
2. Business Intelligence (BI) Analyst:
• Salary: BI Analysts are valued for their ability to provide insights, but their salary is generally lower than Data Scientists due to the less technical nature of their work.
• Range: $70,000 — $110,000 per year.
3. Business Analyst:
• Salary: Business Analysts earn based on their ability to drive business decisions, but their salaries can vary widely depending on the industry.
• Range: $65,000 — $100,000 per year.
4. Data Analyst:
• Salary: Data Analysts often have the most entry-level salaries due to the foundational nature of their work in data cleaning and simple analysis.
• Range: $55,000 — $85,000 per year.
Summary:
• Data Scientist generally earns the highest salary, especially in tech and specialized industries.
