The job duties of an entry-level data analyst include working to collect, manage, and analyse data. They may also contribute technical skills to assure the integrity and accuracy of the data before processing, designing and presenting it to assist people, businesses, and organisations in making better decisions.
Read: Skill requirements for a data engineer resume
Data analysts professionals are in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education. An entry-level data analyst can work in a variety of industries, such as:
- Data quality analyst
- Business intelligence analyst
- Data assurance analyst
- Marketing analyst
- Sales analyst
- Finance Analyst
- Higher education analyst
- Customer analyst
- Healthcare analyst
- Clinical data analyst
- Processing analyst
- Data privacy and compliance analyst
- Operations Analyst
- Sports analyst
- Risk analyst
As an entry-level data analyst, you would work as part of a team of analysts and statisticians that evaluate data. You will also develop reports for executives, stakeholders, and managers. In summary, an entry-level data analyst is expected to carry out business-critical tasks with the supervision of someone more senior. While the role tends to become more specialised over time, we can broadly generalise what junior data analysts do.
How to Become a Data Analyst
If you commit to learning full-time, you may become a Data Analyst in just four months, as a degree is not always necessary to work as a Data Analyst. You can learn a lot of desirable data analysis skills through short courses at specialist data schools, such as:
However, most hiring managers will require a bachelor’s degree in a relevant discipline, such as:
- business information systems
- computer science
- information management
- mathematics
- statistics.
- data science
There are also opportunities for people with postgraduate qualifications in subjects including MSc Data Science, MSc Business Analytics, MSc Data Science and Analytics and MSc Big Data to be data analyst professionals. So, if you are looking to change careers, you may find a postgraduate qualification helpful.
NB: To land your first Data Analyst role, it is essential to be proficient with SQL.
Next, you will need to polish your portfolio in other to get a job. A strong portfolio will boost your chances of finding a role with a firm you’ll enjoy working with.
Ensure to include projects that demonstrate your programming abilities, such as Python, R, and SQL. You may also list any group projects you have. You will have an edge if you’ve gained experience through an internship or placement during your degree. If you don’t have any previous projects, taking internships or apprenticeships or offering to do volunteer jobs can help build your portfolio.
See: 20 Best Apprenticeship Program
Skills You Will Need To Land Your First Entry Level Data Analyst Job
A profession in data analysis necessitates that you have a set of technical abilities. Below are some of the set skills you should possess in order to be employed; whether you’re learning through a degree programme, a professional credential, or on your own:
- SQL: As a beginner, you will need to have complete knowledge of SQL. Although at the start of your career, you will only need to know how to use it to query data in relational databases.
- Maths: If you struggle with math, then data analysis as a job may be difficult for you. In this profession, you will heavily rely on statistical analysis and data interpretation such as linear algebra, regression, probability theory and numerical analysis among others.
- Phyton: Coding is an unavoidable part of data analytics. The most generally used language for data analysis is the Phyton language. Other programming languages used are R, C++, Java e.t.c
- MS Excel: You will need to master using an excel spreadsheet. You will also need to be an expert in manipulating data using excel data analytics functions.
- Statistics: To make sense of data in a real-world environment, you will frequently rely on statistical principles.
- MS Power BI: Power BI is a go-to tool for data analytics who are in the business intelligence sector.
- Presentation skills: You must master the ability to produce clear graphical representations and data visualisations. Additionally, you must possess the capacity to develop and document procedures and workflows
- Relational Databases tools: As an entry-level data analyst, you may not master or know all of the relational databases tools. However, you should show advanced skills in MS Acces.
- If you are looking into ht market analyst roles, you will need to master the use of Google Analytics, SEO, keyword analysis and web analytics aptitude.
Entry Level Data Analyst Salary
The average salary of an entry-level analyst is $42,091. Furthermore, the average typically falls between $42,091 and $77,018. This depends on several factors, including education, certifications, additional skills, and the number of years you have spent in your profession.
Related Article: Remote Data Analyst Jobs: Can I Work Remotely?
Conclusion: Career Prospects
The data analyst role is one of many roles that offer both remote and hybrid styles of work. There are also opportunities to work on a self-employed basis, as a freelance and as a consultant.
Although finding a remote job at an entry-level position may seem difficult. Nonetheless, it is pretty much achievable.
Data analysis is a rapidly expanding field, and skilled analysts are in high demand across all industries. This is in addition to the fact that data specialists are needed in a wide range of industries and domains, including healthcare, manufacturing, education, media, retail, and even real estate.
With experience, you could quickly advance to a management position. Data analysts with advanced skills can also work in academic research or on government advisory boards.
Visit vizajobs to find some of the latest jobs for entry-level, mid-level and senior-level data analysts. We offer jobs across the UK, US, Canada, Australia and European countries.
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