A data analyst gathers, cleans, and interprets data sets to answer questions or solve problems. They work in a variety of fields such as business, finance, criminal justice, science, medicine, and government.
What types of customers should a company target in its next advertising campaign? What age group is most susceptible to a specific disease? What behavioural patterns are associated with financial fraud?
These are the kinds of questions you might be asked as a data analyst. Continue reading to learn more about what a data analyst is, what skills you'll need, and how you can get started on the path to becoming one.
What exactly is data analysis?
The process of extracting insights from data in order to make better business decisions is known as data analysis. The analysis of data typically proceeds through five iterative stages:
Identify the data you want to analyze
Collect the data
Clean the data in preparation for analysis
Analyze the data
Interpret the results of the analysis
Depending on the question you're attempting to answer, data analysis can take various forms. More information on the various types of data analysis can be found here. In a nutshell, descriptive analysis tells us what happened, diagnostic analysis tells us why it happened, predictive analytics generates future projections, and prescriptive analysis generates actionable advice on what actions to take.
Duties and obligations of data analysts:
A data analyst is someone whose job it is to collect and analyse data in order to solve a specific problem. The job requires a lot of time spent with data, but it also requires communicating findings.
On a daily basis, many data analysts do the following:
Data collection: Analysts frequently collect data on their own. Conducting surveys, tracking visitor characteristics on a company website, or purchasing datasets from data collection specialists could all fall under this category.
Data that has been cleaned: Raw data may contain duplicates, errors, or outliers. Cleaning the data entails keeping the quality of data in a spreadsheet or programming language so that your interpretations are not incorrect or skewed.
Model data: entails creating and designing database structures. You might decide what types of data to store and collect, how data categories are related to one another, and how the data will appear.
Data interpretation : entails identifying patterns or trends in data that may provide an answer to the question at hand.
Present: Communicating the findings of your research will be an important part of your job. You accomplish this by creating visualisations such as charts and graphs, writing reports, and presenting information to interested parties.
What tools are used by data analysts?
Analysts frequently use a wide range of tools to improve the accuracy and efficiency of their work during the data analysis process. The following are some of the most commonly used tools in the data analytics industry:
Microsoft Excel
Google Sheets
SQL
Tableau
R or Python
SAS
Microsoft Power BI
Jupyter Notebooks
Salary and job prospects for data analysts:
According to Glassdoor, the average base salary for a data analyst in the United States in December 2021 is $69,517. This can vary depending on your seniority, where you live in the United States, and other factors.
Analysts of data are in high demand. The World Economic Forum ranked it second in terms of job growth in the United States [1]. According to the Bureau of Labor Statistics, related occupations are also experiencing extremely rapid growth.
Operations research analyst positions are expected to grow by 25% between 2020 and 2030, market research analysts by 22%, and mathematicians and statisticians by 33%. This is significantly higher than the overall employment growth rate of 7.7 percent.
How to Work as a Data Analyst?
There are several paths to becoming a data analyst. Whether you're fresh out of school or looking to change careers, the first step is often assessing your transferable skills and developing the new skills you'll need in this new role.
Data analyst technical skills
Database tools: Microsoft Excel and SQL should be standard tools in the toolbox of any data analyst. While Excel is widely used across industries, SQL can handle larger data sets and is widely regarded as a must-have tool for data analysis.
Programming languages: Learning a statistical programming language, such as Python or R, will allow you to work with large amounts of data and solve complex equations. Though Python and R are two of the most popular, it's a good idea to look at several job descriptions for a position you're interested in to see which language will be most useful in your industry.
Data visualisation: Being a successful data analyst requires you to present your findings in a clear and compelling manner. Knowing how to best present information through charts and graphs will ensure that your work is understood by colleagues, employers, and stakeholders. Among the many tools used to create visuals are Tableau, Jupyter Notebook, and Excel.
Statistics and math: Understanding the concepts underlying what data tools do will greatly benefit your work. A solid understanding of statistics and math will help you determine which tools are best to use to solve a specific problem, identify errors in your data, and gain a better understanding of the results.
Paths to becoming a data analyst?
The first step to becoming a data analyst is to acquire these abilities. Here are a few methods for getting them that are adaptable enough to fit in with your schedule.
Professional certificate: Programs leading to professional certificates at the entry level typically don't require any prior expertise in the subject. They can give you the opportunity to produce projects for your portfolio and receive real-time feedback on your work while teaching you fundamental skills like SQL or statistics. On Coursera, several professional certificate programmes accomplish precisely that.
Bachelor's degree: For employment requiring data analysis, the Bureau of Labor Statistics advises a bachelor's degree. Focusing on statistics, algebra, or computer science in your courses will help you stand out to employers if you're thinking about getting a degree to become a data analyst. You can squeeze a degree in around your priorities by choosing one of the many online bachelor's degrees that provide flexible scheduling.
Self-study: If you prefer a route without formal instruction, you can pick up the skills required for data analysis on your own. Use this beginner's reading list for data analytics to get going. Here are some suggestions for data analytics projects to consider once you're prepared to begin developing a portfolio.
Data analyst career advancement
Data analysis can lead to other vocations as well. Many people who begin as data analysts later become data scientists. Data scientists study data similarly to analysts by using arithmetic, statistics, and computer science. But a scientist can create models and other tools using cutting-edge methods to predict future trends.
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