Data analysts work on a wide range of business tasks that help organizations use data effectively. Business tasks are a central part of real-world data analysis work, and understanding them clearly is essential.

Across many examples of organizations using data, a common pattern emerges: each situation involves issues to explore, questions to answer, or problems to solve. These concepts are closely related and can be easily confused, so in the context of data analytics they can be distinguished as follows:

  • An issue is a topic or subject that requires investigation.
  • A question is designed to discover information.
  • A problem is an obstacle or complication that needs to be resolved.

For example, a company may have a question about developing new products, and data analysis can provide insights into customer preferences. Another organization may face a staffing problem, which data analysis can help address by identifying more effective operational strategies. These questions and problems form the foundation of the business tasks that data analysts help solve.

What Is a Business Task?

A business task is the specific question or problem that data analysis is intended to answer for an organization. This is where much of a data analyst’s effort is focused in professional work.

Using the zoo example, the problem involved unpredictable weather making it difficult to anticipate staffing needs. A possible business task in this case could be defined as:

  • “Analyze weather data from the past decade to identify predictable patterns.”

Once a business task is defined, data analysts can plan how to collect the relevant data, analyze it, and present the results. This enables the organization to make informed decisions about daily staffing levels.

The Role of Data-Driven Decision-Making

Data-driven decision-making refers to the practice of using facts discovered through data analysis to guide business strategy. At its core, decision-making involves choosing among possible outcomes, which may be positive, negative, or a combination of both.

In the zoo example, data provided the information needed to make an informed decision that addressed the staffing problem. Without data, decisions based solely on observation or memory would be unlikely to resolve the issue over the long term. Data analytics made it possible to understand the problem more completely and identify an effective solution.

Observation and intuition are useful tools in decision-making, but when used alone they provide only a partial view of a situation. Data offers a more comprehensive perspective by revealing underlying causes and relationships, making it possible to identify solutions that might not otherwise be apparent. For this reason, data analytics plays a key role in helping organizations make better decisions.

The Data Analyst’s Contribution

Every data analysis effort begins with a business task and the question it seeks to answer. By defining the right questions, planning data collection and analysis, and presenting results clearly, data analysts enable teams to make informed, data-driven decisions. This makes data analysts an important contributor to organizational success.