Top 10 Data Analyst Skills Employers Need to See in 2023

SQL, which stands for Structured Query Language, is the standard language used to communicate with databases. This domain-specific programming language is often thought of as the “graduated” version of Excel that makes retrieving data possible, and it provides analysts with a way to access and manipulate large amounts of information in a relational database.

NoSQL is a term used to describe nonrelational databases — that don’t use SQL or the SQL programming language exclusively. Because of their simple horizontal scalability and flexibility, NoSQL databases are frequently preferred within an organization.

Statistical programming languages, like R or Python, enable you to run advanced analyses in ways that Excel is unable to. When working with large data sets, these powerful statistical programming languages are utilized to perform advanced analyses and predictive analytics.

If you have a solid foundation in probability and statistics, you’ll be better able to recognize patterns and trends in the data, avoid biases, fallacies, and logical errors, and create accurate and reliable results.

Making visually appealing charts, graphs, maps, and other visual representations of data is a key data analyst skill that is utilized to explain the findings in an easy-to-understand manner. Additionally, it also avoids elements that can either be misleading or difficult to interpret, such as pie charts.

Machine learning skill focuses on creating algorithms designed to find patterns in big data sets and improving their accuracy over time. The more data a machine learning algorithm processes, the “smarter” it becomes, allowing for more accurate predictions.

Analysts use econometrics to estimate future trends based on historical data by applying mathematical and statistical data models to the study of economics.

Dashboards and reports in the form of a sophisticated dashboard with hundreds of interactive data points or a straightforward chart and table with date filters respectively will remove technical obstacles from others’ access to crucial data.

Analysts must be able to explain complicated topics in a way that is understandable to everyone. Even the greatest analytical abilities are useless if you can’t communicate what they mean and convince your colleagues to act on your findings.

As a data analyst, you will encounter problems, bugs, and roadblocks every day. Being able to think critically and solve the problems your way out is another key skill that is important for a data analyst.