In today’s digital world, people create data with almost every business transaction they make. This information—purchasing choices, spending amounts, and so on—provides insight into consumer behavior and the motivations behind it, which can range from public health concerns to cultural trends. Consumers and businesses can both benefit from data analysis. Consumers may have better access to products that are tailored to their wants and needs, and businesses can decide which product lines to invest in.1
Analytics, which are a vital aspect of our society, can include data analytics and business analytics. This article will explore the definitions of each one, what the differences are between them, and what professional skills are needed for each.
What is Business Analytics?
Business analytics is the process of collecting and analyzing data, using statistical and computational methodologies and technologies, for the purpose of improving business decision-making. Business analytics uses both internal data and publicly available data to answer questions that can drive effective business strategy.2 There are several types of business analytics, including descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
- Descriptive analytics tells business leaders what happened based on historical data. It can, for instance, help businesses understand what their sales were last year.
- Diagnostic analytics is often used to dive deeper into the results of descriptive analytics by helping business leaders get to the root cause of an event. If sales dropped significantly last quarter, descriptive analytics can help uncover what specific sales metrics fell short, and diagnostic analytics will help identify why the decrease occurred.2
- Predictive analytics uses historical data to identify patterns and make predictions about what might happen in the future. Businesses can use predictive analytics to make decisions about, for example, when equipment will need to be repaired so they can implement a proactive maintenance schedule.2
- Prescriptive analytics helps business leaders decide what they should do based on existing data. If a company has historically increased its inventory of cold-weather supplies but this winter is expected to be unseasonably warm, prescriptive analytics may help leaders decide to reduce inventory instead.2
What is Data Analytics?
Data analytics involves working with large datasets to identify patterns, trends, and correlations in data, and to interpret the meaning behind them. Data analysts use mathematical techniques and computer science to analyze and visualize data trends. Almost all organizations, not just businesses, use data analytics. Government organizations, educational institutions, scientific institutions, and healthcare organizations use data analytics to understand trends as well as make predictions and discoveries.3
Data Analysts vs. Business Analysts: Key Differences
Although the fields of data analytics and business analytics overlap significantly, there are some notable differences between the role of a data analyst and the role of a business analyst. A data analyst’s primary job is to collect data for others to use in making decisions, while a business analyst has a more hands-on role in making decisions about data.4
A data analyst is often responsible for gathering, monitoring, and presenting data to stakeholders. These stakeholders will then use the data to inform business decisions and engage in strategic planning. A data analyst's responsibilities can include determining what tools and techniques will be most effective for gathering data, checking data for accuracy and completeness, and identifying trends and patterns in data.4
Business analysts use data to drive informed and effective business decisions and strategies. Their responsibilities can include identifying business needs, finding inefficient processes, and creating reports for shareholders that explain data.4
Skills Required for Business Analysts vs. Data Analysts
While both types of analysts require strong analytical skills, there’s a difference in the level and types of skills needed for each role. A business analyst needs a deep understanding of factors that influence business in general, such as market trends and customer behavior, as well as the processes and operations of their specific business.5 This individual draws on these skills to contribute to high-level business strategies and objectives.
While business analysts need to understand how to query data and derive actionable insights from it, they don’t need the data manipulation skills that data analysts do.5 Instead, business analysts need to be able to identify business challenges and opportunities. They also need effective communication skills so they can work with stakeholders and understand their needs.6
Data analysts work more directly with data and less with business strategy. They need to understand business goals so they can make decisions about what data collection methods will provide the most valuable data to meet those objectives. However, their day-to-day responsibilities are more technical, often involving cleaning, transforming, and modeling data to support business objectives rather than define them.5
Data analysts need to be proficient in structured query language (SQL) so they can extract and manipulate data from structured databases. They also need to understand statistical concepts and programming languages such as Python.6
The Right Path: Business Analytics or Data Analytics?
Whether a career path as a data analyst or a business analyst would be better for you will depend on the area in which you’d prefer to specialize. Both roles require excellent analytical and communication skills. Business analysts will need strong business skills while data analysts will need strong technical and mathematical skills.6
If you’d enjoy using data to drive business strategies and playing a role in determining the course of a business, then a career in business analytics will probably be a better fit for you. If you enjoy the technical challenges of working closely with data and setting up models, you’d probably thrive as a data analyst.6
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- Retrieved on September 16, 2024, from oracle.com/business-analytics/what-is-analytics/
- Retrieved on September 16, 2024, from ibm.com/topics/business-analytics
- Retrieved on September 16, 2024, from avenga.com/magazine/data-science-in-healthcare/
- Retrieved on September 16, 2024, from indeed.com/career-advice/finding-a-job/business-analyst-vs-data-analyst
- Retrieved on September 16, 2024, from pecan.ai/blog/business-analyst-vs-data-analyst/#how-to-select-the-right-role
- Retrieved on September 16, 2024, from sprinkledata.com/blogs/data-analyst-vs-business-analyst-a-comprehensive-guide-to-help-you-choose-the-right-career-path