Data Analyst Role: Requirements, Duties And Skills
Updated 7 December 2023
A data analyst collects, analyses and interprets data from various sources. As companies transition to digital operations, they collect valuable data, which they turn into actionable insight. Understanding what this position includes and its requirements can help you determine if it is the right career choice. In this article, we discuss what a data analyst role is, review its requirements, explore its job duties and outline the skills you require to excel in this career.
Please note that none of the companies, institutions or organisations mentioned in this article are associated with Indeed.
What Is A Data Analyst Role?
A data analyst role is a job that focuses on the collection and analysis of data. Data analysts turn data into meaningful information companies can use to improve and grow. They use statistical and analytical techniques to find trends, interpret the data and study patterns that help influence business decisions and recommend changes in company operations. Their analysis helps the company improve efficiency, understand customer requirements and increase its profit. Apart from conducting in-depth analysis, these analysts create meaningful reports and share them with management and leaders.
Depending upon the industry in which they work, some analysts specialise in financial, operations or marketing data, among others. Using their coding languages and data mining skills, they help companies visualise the data.
Types Of Data Analyst Role
Here are the different types of data analysis roles:
Market research analyst: Market research analysts help businesses understand what products or services customers want and the price they are willing to pay. These analysts use a variety of tests, data collection and statistical and analytical tools to predict the product or service performance, monitor sales trends and measure the marketing campaign's success.
Healthcare analyst: Healthcare analysts identify and evaluate medical data to improve the business aspect of hospital and medical care facilities. They combine and analyse information, contribute to better patient care, streamline healthcare processes and ensure superior patient care.
Business analyst: Business analysts are information technology and data analytics experts who use data to evaluate a company's operations and help determine project requirements. Their duties include identifying a business's technical requirements, evaluating its operations and analysing its costs and efficiency.
Business intelligence analyst: Business intelligence analysts collect, analyse, review and share data to identify areas where a company can make changes to improve its efficiency and productivity. They review and manage analytics and competitor data and identify opportunities for improvement.
Operations research analyst: These analysts collect and interpret data sets to solve problems and develop more efficient methods for companies to operate. They develop company-wide policies and use different tools to organise and interpret data and determine how it relates to workplace productivity.
What Does A Data Analyst Do?
The typical job duties of a data analyst vary depending on the company where they work. For instance, data analysts in sales companies focus on increasing sales revenue, while an analyst in a logistics company may search for ways to reduce transportation time and fuel costs. Here are some job responsibilities of a data analyst:
Developing and implementing data collection systems, databases and other strategies to optimise statistical efficiency and quality
Improving efficiency, understanding customer needs, increasing profit and impacting other valuable aspects of business operations
Streamlining data collection processes for automating different business processes
Maintaining databases by monitoring performance and addressing errors
Designing data systems and databases
Solving data-related problems and coding issues
Interpreting data sets for extracting relevant information benefitting the organisation
Collecting data, processing it using advanced tools and summarising it to tell a story
Managing databases and showing end-users how to utilise them effectively
Facilitating strategic decision-making within the company
Compiling reports based on data analysed and creating data dashboards, visualisations and graphs
Designing, creating and maintaining relevant and useful databases and data systems
Producing and tracking key performance indicators
Cleaning the data and discarding relevant information
Requirements For A Data Analyst
There are certain qualifications many employers look for in data analyst candidates. Here are some requirements for becoming a data analyst:
Most employers expect you to complete a computer science, engineering, applied mathematics or statistics degree. These courses teach you how to apply mathematical skills to real-world situations. This prepares you to help companies make data-backed decisions. In addition, consider completing a relevant course based on the type of data analyst you want to become. For instance, if you want to work as a financial or business analyst, pursue a degree in economics or finance. Many employers prefer candidates with a big data analytics, data science, data analytics or business analytics post-graduate degree.
While completing your graduate or post-graduate degree, search for an entry-level position. Contact mentors or industry experts for advice on which positions you can apply for. Also, consider pursuing an analytics internship to gain a deeper understanding of the responsibilities. For example, before becoming a data analyst, you could work as a statistical assistant, technician or coder. These roles provide on-the-job experience in handling databases and data analytics. Earning one or two years of relevant experience helps you excel as a data analyst.
In addition to completing a bachelor's degree, there are further certifications specific to the job that companies may require. Some examples of certifications are Certified Analytics Professional, Microsoft Certified: Power BI Data Analyst Associate, SAS Statistical Business Analyst, CompTIA Data + and Cloudera Data Analyst Training Course and Certification.
Earning certifications shows your commitment to excel in this job. These certifications ensure you stay up to date with the latest computer systems and technologies to collect and analyse data.
Skills For A Data Analyst
Here are some skills to develop for success as a data analyst:
Data analysts require excellent statistical analysis skills to interpret and derive conclusions from data. Knowledge of using equations, formulas, statistical tools and other mathematical methods helps you analyse information. Use statistical analysis skills to create models or prototypes for new software or products.
Data visualisation conveys the meaning of data using graphs and charts. Knowledge of data visualisation tools helps you analyse data to present key findings. You can present this information to relevant stakeholders in an easy-to-understand and comprehensive manner.
Statistical programming languages
Proficiency in using statistical programming languages such as Python helps you perform in-depth data analysis quickly. The ability to code in different programming languages helps you analyse and visualise data sets more efficiently. These languages offer aggregation, merging, filtering and data-cleaning functionalities. Using these programming languages, you can create interactive plots and facilitate data exploration to analyse data.
Data collection and cleaning
Data collection involves collecting and managing data, while data cleaning involves removing and fixing incorrect data in a dataset. Employers expect you to have in-depth knowledge of these two processes as it ensures data accuracy. Data cleaning ensures no inaccuracy in data analysis, while data collection gives you a comprehensive understanding of the data cleaning process.
Data Analyst Tools
Here are some tools that data analysts use:
Structured query language (SQL): Data analysts require proficiency in SQL because it is the common language of relational databases. Though it is a relatively simple tool, it helps you analyse complex and complicated datasets.
Microsoft Excel: Knowledge of Microsoft Excel and other spreadsheet software helps in data organisation, cleaning and transformation. Employers prefer candidates proficient in manipulating spreadsheets as they provide a range of statistical and analytical functions, enabling you to summarise data, perform calculations and derive insights.
Power Business Intelligence (BI): Power BI helps users to generate interactive visual reports and dashboards, enabling data analysts to create interactive and visually appealing reports. Proficiency in Power BI is essential as it integrates with a variety of data sources, such as spreadsheets, databases, online platforms and cloud services.
Statistical Package for the Social Sciences (SPSS): SPSS helps analysts conduct statistical analysis and provide a range of procedures that they can use to analyse and interpret data. It even provides a tool for data cleaning, handling missing data, creating derived variables and merging datasets.
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