What skills does a data analyst need

Whether you’re looking at Data Analyst jobs and want to improve your skillset, or you’re simply intrigued as to the attributes people need to become a successful Data Analyst, here’s all you need to know.

What is a Data Analyst and what do they do?

Data plays a vital role within organisations – across both private and public sectors. Data alone doesn’t drive business success – it needs to be appropriately sourced, translated and applied to make an impact, which is where the Data Analyst comes in.

A Data Analyst gathers and analyses the data they have, and using their creative and analytical thinking, translates it into meaningful conclusions and solutions to business problems, to drive growth and success. You can read more about a Data Analyst’s job description and their day-to-day responsibilities.

Data Analyst salary

According to Indeed’s most recent data, the average salary of a Data Analyst is £37,475 per year in United Kingdom. The exact expected salary will depend on a number of variables, including location and years of experience.

Skills needed to succeed as a data analyst

There are multiple different skills required to be a successful data analyst, which can vary depending on which type of data analysis the individual specialises in. However, all jobs in the field of data analysis will a combination of analytical, communication and technical skills to provide the most valuable insights.

Here is a list of the key skills a Data Analyst should have:

Data cleaning: The ability to ‘clean’ data to ensure accuracy and reliability in analysis. This involves fixing or removing incorrect, corrupted, incorrectly formatted, duplicate or incomplete data within a dataset for most accurate analysis.

Programming skills: Knowledge of programming languages such as Python, R or SQL for data manipulation, analysis and extraction.

Statistical analysis: Understanding of statistical concepts and methods to analyse data distributions, correlations and trends.

Data visualisation: The ability to create meaningful and effective visualisations of the data they are working on, using tools to communicate insights to non-technical stakeholders.

Attention to detail: A meticulous approach to data analysis, ensuring accuracy and precision in findings to inform next steps.
Continuous learning and adaptability: The willingness and ability to stay updated on the latest tools, techniques and ever-changing trends in the field of data analysis.
Machine learning knowledge: Understanding of basic machine learning concepts and algorithms can be beneficial for more advanced analysis.
Critical thinking: The ability to approach problems logically and think critically to derive meaningful insights from data.
Communication: In terms of soft skills, communication is key. A successful Data Analyst will possess the ability to effectively communicate complex findings to non-technical stakeholders in a clear and digestible manner. Being approachable to answer technical questions is also a plus.
Teamwork: The ability to work well in a team, especially with data scientists, engineers and business stakeholders, is invaluable when it comes to getting the job done efficiently.
Ethical considerations: Finally, understanding and adhering to ethical guidelines and considerations when working with sensitive or private data.

How an MSc Data Analytics can help you develop the skills you need

To succeed in this competitive industry, strengthening your skills on all of the above points is vital. In order to do this, you should consider a data analyst course. Our MSc Data Analytics course is part-time, and fully online (with optional face-to-face meet ups) meaning you can learn at your own pace and work around your other commitments.

This MSc will equip you with all the skills you need to become a successful Data Analyst. From training on popular software and tools such as Knime, Tableau, Hadoop and Spark, to analysing real data to provide answers for practical problems, our programme is designed to prepare you for the real-world challenges of working with data, setting you up for success.