18 Key Data Analyst Skills To Get You Hired in 2023

Updated August 6, 2023

Data analysts are experts who use, organize and assess data to make inferences and guide business decisions. These analysts use both interpersonal skills and technical skills to succeed in their roles. If you're a data analyst or you want to become one, learning more about the key skills for the role can help you choose which of your own abilities to improve.

In this article, we explain what a data analyst is and review a list of the most important skills they can use for success.

What is a data analyst?

A data analyst retrieves, organizes and analyzes information to help a company improve production, efficiency or another valuable aspect of its operations. Data analysts work in all industries, from retail to academia. Often, they use the data they gather to create reports that summarize patterns and offer solutions to stakeholders in the form of updated systems, procedures or protocols. Companies use data analysts specifically to improve outcomes like productivity or profits or to understand employee or customer needs.

Common responsibilities for data analysts include:

Finding patterns in data
Writing reports
Collaborating with stakeholders
Presenting their findings
Creating systems

What skills does a data analyst need?

Data analysts benefit from developing certain skills. Here are some of the top skills for data analysts to acquire for success in their field:

Technical skills

These are some technical skills for data analysts:

1. SQL

Structured Query Language, or SQL, is a spreadsheet and computing tool capable of handling large sets of data. It can process information much more quickly than more common spreadsheet software. SQL is a valuable tool for data analysts, so knowledge of its functionality is key. Data analysts can also work with NoSQL, which is a similar database that scales horizontally instead of vertically.

2. Spreadsheets

While SQL is often the preferred software for data analysts, knowledge and understanding of traditional, widespread spreadsheet tools is necessary. Some companies may prefer reports or data sets presented through traditional spreadsheet tools. Data analysts may use programs like Microsoft Excel, Quip, Zoho Sheet or WPS Spreadsheets.

3. Statistical programming languages

Some data analysts choose to use statistical programming languages to analyze large data sets. Data analysts are familiar with a variety of data analysis programs to prepare them for the tools their company has available. These are some languages you can use as a data analyst:

R: This language is especially helpful for statistical computing.
Python: Data analysts can use Python to make visualizations of data and build machine learning algorithms.
Java: Java is an object-oriented language that can help create software that's compatible with many devices and platforms.
Scala: This language uses functional programming and object-oriented programming to help create programs that are free of bugs.
MATLAB: Using MATLAB allows analysts to plot data and implement new algorithms.

4. Data visualization

After gathering, analyzing and compiling the data, analysts share their findings with the company. Creating an easy-to-understand data analysis visualization is vital. Often, data analysts use visuals like graphs or charts to help their colleagues understand what the data shows quickly and clearly.

5. Machine learning

Some companies that use highly technical machines to complete tasks require their data analysts to have knowledge of how machine learning works. Machine learning, or artificial intelligence, is the use of algorithms and data to imitate human productivity. It's growing as technology advances, so it's wise for data analysts to develop this skill.

6. Data warehousing

Data warehousing is the creation of virtual storage and organization systems for a company's data. Often, they're managed by data analysts whose main job is to monitor the data and maintain safeguards and access. Data warehouses help with management, which allows companies and organizations to collect, organize, protect and use data efficiently.

7. Data prep

Data preparation, or data prep, is converting a data set from a large batch of information into a well-sorted and easy-to-understand report. This can include identifying errors or duplicate entries and remedying them prior to date analysis. They may also complete data cleaning to ensure information is streamlined. Data analysts usually complete data prep before data visualization so that the most important information and takeaways are easy to convert into a graph or chart.

Analytical skills

These are some skills that can help with data analytics:

8. Critical thinking

Companies often task data analysts with both collecting data and interpreting the data for a specific purpose. Knowing what data to collect and how to process it to obtain the right information is a critical thinking skill that's vital for data analysts to develop.

9. Problem-solving

Data analysts often encounter technical issues while completing their job-related duties. Establishing effective solutions for stakeholders through problem-solving is a necessary skill.

10. Attention to detail

Data analysis requires precise focus. Analyzing code or other technical details involves reading and assessing intricate coding or technical structure. Close attention to detail is a vital skill for data analysts to ensure they sort and analyze code correctly.

11. Statistics

Data analysts use statistics to assign meaning to large data sets. Statistics help data analysts understand large sets and find useful, relevant information to apply to the issue facing the company.

12. Domain knowledge

Domain knowledge for data analysts refers to the domain in which the data they're assessing lives. Sometimes the data's domain can offer useful insights into the data and provide analysts with helpful information with which they can more easily deconstruct and make sense of the data.

Communication skills

These are some communication skills data analysts can use:

13. Public speaking

Presenting data analysis is an important part of a data analyst's job. Besides compiling the findings in a clear manner, data analysts also explain both verbally and in writing why the data is important and what the company can do to respond to the findings.

14. Verbal communication

Data analysts communicate with a variety of people during the course of their work, including other data analysts, IT representatives and colleagues not directly related to data or technology. They can use verbal communication to explain complex ideas and present information in a way that common viewers can understand.

15. Collaboration

Collaboration with internal and external stakeholders is a frequent responsibility for data analysts. Respect and appreciation for teamwork help data analysts and other members of the company's team complete their work.

Industry-specific skills

These are some business and industry knowledge skills data analysts can use:

16. Writing

While data analysts primarily work with numbers, creating written reports is an important part of their job responsibilities. Strong writing skills help data analysts clearly and accurately explain their findings in written reports.

17. Project management

Project management involves overseeing and tracking all elements of a project, including the team members and their work. Some data analysts regularly manage a group of other analysts or information technology staffers.

18. Research

Sometimes data analysts may conduct research. They may determine solutions for technical problems or evaluate new processes based on data analysis. Both of these tasks require research for information or possible solutions.

Please note that none of the companies mentioned in this article are affiliated with Indeed.