Have you ever wondered what a day in the life of a data analyst looks like? Are you curious about the day-to-day roles and responsibilities of one of the fastest-growing fields of work today? With businesses generating more data than ever before, companies need qualified data analysts to help them collect, analyze and interpret key information about their businesses.

If you are interested in starting a career in data analytics, you may want to learn more about what a data analyst does on a daily basis. In this article, we will take a closer look at a day in the life of a data analyst and examine how data analysts use their technical and non-technical skills to help inform important decision-making within a company.

A day in the life of a Data Analyst

Millions of companies – in virtually every industry – can benefit from the help of a skilled data analyst. According to the Bureau of Labor Statistics, data analytics employment opportunities are rapidly rising, with jobs expected to grow by over 25% in the next ten years.

Data analysts do things like:

  • Help large retailers analyze their supply chain and identify ways to generate more revenue  
  • Support non-profits in maximizing donation campaign results
  • Assist Healthcare providers with improving patient outcomes and lowering the cost of care

Data analysts do this by gathering clues (aka data) to uncover and interpret patterns and trends occurring within a business. With the help of data modeling and visualization tools, analysts then present their discoveries to stakeholders and business leaders. In communicating these insights, analysts help businesses inform decision-making processes, optimize business procedures, and predict future trends.

A typical day in the life of a data analyst varies based on the industry they’re working in and the type of data being collected. However, regardless of industry or data, a data analyst can expect to spend most of their workday performing a series of tasks to reach their conclusion successfully. These tasks include:   

  • Identifying or diagnosing a problem to analyze
  • Collecting appropriate data from various sources  
  • Cleaning and preparing the data for analysis
  • Analyzing the data for insights, patterns, or trends
  • Interpreting the results of the analysis with reports and dashboards
  • Collaborating with stakeholders and presenting key findings
data analysis

What are some common data analyst responsibilities?

A day in the life of a data analyst isn’t as simple as putting numbers on a spreadsheet. As the gatekeeper of an organization’s vast amount of data, a data analyst plays a critical role in informing strategic business decisions and improving the overall health of a business.

To be successful in a career in data analytics, analysts must have a combination of strong analytical, technical, and communication skills. Below is an overview of some of the common data analyst day-to-day responsibilities.

Identifying the problem

Before a data analyst can begin collecting and interpreting any data set, they must first identify and define the business problem or objective. To do this, analysts need a strong understanding of the businesses’ inner workings, processes, and goals. Analysts often collaborate and brainstorm with other departments to identify existing business challenges or isolate new opportunities for improvement. Once identified, analysts can begin gathering data to understand the problem better.

Defining data quality criteria

Data quality criteria are used to determine whether a system’s data is accurate, complete, consistent, and reliable. Defining data quality criteria is essential for a data analyst’s data collection process. Bad data can significantly impact a business’s operations and decision-making processes. Companies can make poor decisions or ineffective strategies if inaccurate or incomplete data is collected. That is why data analysts must define data quality criteria before continuing their analytical process.

 Establishing data processes     

Establishing processes for completing a task efficiently and effectively is necessary for nearly every type of job. Just as a chef uses a process to create a recipe, so does a data analyst for collecting and organizing data. Data analysts rely heavily on their ability to efficiently manage and manipulate large quantities of data to achieve their objectives. Often, the data is complex and requires the analyst to establish a framework or “process” for breaking down the information into usable, insightful information. Data analysts often work with other people, such as engineers and data architects, to implement process improvements, make system modifications and develop more thorough documentation methods.  

Cleaning Data

Cleaning and preparing data are a large part of any data analyst’s workday. To ensure credibility and accuracy in their findings, analysts must clean the data collected by removing any duplicates, errors, or outliers. Data cleaning is an invaluable skill for data analysts to master. It is one of the most critical steps to preparing accurate models for analysis. Just as mentioned above, bad data leads to incorrect or misleading conclusions. Because of this, proper data cleaning skills are crucial to a data analyst’s success.

 Analyzing data

The term “data” refers to a business’s large, diverse data sets. This data type is often too large or complex to process with traditional data analysis methods. That is where the data analyst comes in. The data analyst is responsible for using their knowledge of programming languages, like Python or R, to handle this type of data and perform complex equations. In addition to programming skills, analysts need strong critical thinking skills to process and analyze big data sets. Analysts use critical thinking to uncover hidden patterns, identify correlations, and extract insights beyond just numbers themselves.  

With data analytics, an organization can harness the knowledge of these complex data sets and identify new opportunities to improve its end-user experience.

Generating reports

Generating reports is a primary responsibility of a data analyst. Once the data analyst has gathered the data, cleaned it, and analyzed the results, it’s time to present their findings to the appropriate parties. To do this, analysts build reports that help comprehensively illustrate their analysis results. Data analysts also generate reports to identify patterns and make predictions. Reports allow the data analyst to describe what is causing the business problem and provide usable, actionable solutions to inform improvements. 

Data analysts use various reporting tools to achieve their presentation objectives. Extensive knowledge of reporting tools like SQL, Excel, Tableau, and Python is essential to the success of any data analyst. Learn more about advancing your data analytics skills with a Tableau Data Analytics Certificate here.

data report

How often do you collaborate with team members?

The success of a data analyst depends on their ability to work with others. Whether it’s helping the Marketing team identify ways to improve their social media conversion rates or assisting the Sales team in gaining insights about the customer experience, data analysts frequently collaborate with other departments. Data analysts also work closely with other data-specific team members like peer data analysts, data scientists, and database developers to execute their work and improve data processes.  

Strong communication and presentation skills are essential to a data analyst’s ability to collaborate with team members. Often, data analysts present their findings to people who do not have a data analysis background. That is why analysts frequently use reporting tools like Tableau to help visualize the data and present their findings compellingly and concisely.

A skilled data analyst can perform robust data analysis and effectively communicate their findings to others in an accessible way. 

Ready to start a career in data analytics?

Does the typical day in the life of a data analyst excite and intrigue you? Are you ready to take the next steps in pursuing one of the fastest-growing career paths today? If you answered yes, the first step in starting your career in data analytics is learning the requisite analytical skills required for any data analyst position. In addition to traditional educational pathways, many professionals take certification programs in specific data analytics tools like SQL or Tableau to make them more competitive applicants for jobs.

In the Pathstream Tableau Data Analytics Certificate program, you will learn to understand, visualize, and analyze raw data sets. This 21-week certificate program is 100% online and built for busy professionals who want a personalized yet flexible approach to career development. The course curriculum features hands-on projects that mirror the ones you’ll have to complete in a data analytics job. For example, you’ll conduct real-world data analysis, run SQL queries, create dashboards, and present insights using Tableau.

When you finish the program, you will be ready to apply for thousands of available data analytics jobs with companies like Facebook, Whole Foods, Target, and more. Learn more about starting your data analytics with Pathstream today.

Was this helpful?

Thanks! What made it helpful?

How could we improve this post?