Analytics has become a driving force for business development and transformation, providing organizations with the capabilities needed to create and implement new, creative strategies that improve customer experiences, enhance growth opportunities, and provide new revenue streams.
But the term analytics is so broadly used that it can be difficult to make distinctions in its purpose and applications. Data analytics and business analytics are great examples of this. The terms are often used interchangeably, yet the two are quite distinct from one another, as evidenced by the following examples.
When a business is planning their sales strategies for an upcoming season or holiday, they might use business analytics to predict product demand so they can optimize stock and ensure they’re able to meet a specific business goal.
However, with data analytics, that same hypothetical business might use data to discover that women between the ages of 18 and 24 are the most likely to buy those products—and, then personalize their marketing campaign accordingly.
Let us now begin our learning about Business analytics vs Data analytics by understanding the terms well.
A Quick, but Deep Dive into Data Analytics and Business Analytics
Both data analytics and business analytics involve the use of data to inform decision-making and ultimately prepare a business for the future. For those who are interested in a possible career in these fields, it’s crucial to understand the difference.
Data Analytics: Uncovers Trends and Insights
Data analytics is the process of analyzing and categorizing data—sorting, storing, cleansing, identifying patterns, and interpreting insights by using various statistical techniques, big data processing, and technology.
One of today’s most popular and recognizable forms of data analytics is machine learning, which processes massive volumes of data and uncovers patterns within that data to make intelligent predictions and produce unique insights that answer a particular business question or solve a specific business problem.
Data analysis is more technical than business analytics and requires the use of sophisticated analytics tools like Python and Tableau. Data findings must also be translated into meaningful information to present to different teams or to business leaders who need to be able to understand and interpret the insights easily.
Data analytics is a crucial practice for improving organizational or operational efficiencies and developing strategies to seize new business opportunities.
Business Analytics: Makes it Practical
Business Analytics, a sub-division of business intelligence, focuses on the big picture of how data can be used to improve weak areas in an existing procedure or to add value or cost optimization in a specific business process.
Business analytics focuses on creating solutions and solving existing challenges that are unique to the business and usually stays at the forefront of the data pipeline as opposed to data analytics, which is more focused on the backend.
Successful business analytics applies data-derived insights to support decision-making processes and drive practical changes throughout the organization.
Roles and Responsibilities
Business analysts are the link between the world of IT and business. They plan and communicate goals and strategies to everyone across the organization, from stakeholders to management to IT. As problem solvers, they approach situations and challenges by looking at the business as a whole so that they can create solutions using data. Responsibilities include:
- Introduce change into an organization, such as a new business model and help manage its progress
- Identifying and defining specific business requirements and communicating effectively to business leaders or stakeholders
- Defining business issues and creating solutions for the organization
Data analysts help translate data and use reporting to express data clearly in a storytelling format, and also gather data and add new sources where relevant. They help to identify new sources of useful data and seek to understand what questions and solutions business leaders are looking for, and how to use data to get the right answers. Data analysts are responsible for:
- Implementing or designing databases and performing data collection
- Acquiring and maintaining data and performing data cleansing
- Interpreting trends from complex data and communicating insights to various departments, teams or business leaders
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The Next Step in your Educational Journey
The need for skilled Data Analysts and Business Analysts is continuously growing across industries as they bring substantial value by helping organizations realize the full potential of their business designs, goals, plans, and strategies.
Learn more about Simplilearn’s new PG Program in Data Analytics, in partnership with Purdue University, and in collaboration with IBM, to unlock new skills to accelerate your analytics career. This comprehensive program provides learners with little or no experience in programming with the core concepts of data analytics and statistics and teaches you how to: analyze data using Python and R programming languages, interact with databases with SQL, and visualize the data with essential tools like Tableau and Power BI.