A data analyst will play an important role in developing business operations, especially as we are approaching the age of information data.
This industry has strong growth potential with great recruitment demand and attractive remuneration. You can find a lot of potential opportunities here.
So, how to become a data analyst? Follow the roadmap that includes five basic steps as follows:
- Attain a degree.
- Get some certifications.
- Develop hard and soft skills.
- Apply for a job.
- Advance your skills and knowledge.
If you want to learn more about the details of each step in the process and additional information about this job, please read on to discover!
A data analyst (also known as a data modeler and systems analyst) collects and analyzes large amounts of information and data to find trends and useful conclusions.
Therefore, a good data analyst needs to understand the needs of the user. From there, they identify potential business opportunities for the company.
An analytical approach uses data to evaluate a company’s processes and products. They then analyze campaigns and track them to find the right strategic direction for the company.
Data analysts have roles in everything from finance to epidemiology to mining. They also have to work with many different departments to make the most rational decisions.
As a result, these experts will always closely monitor the company’s business activities. They are indispensable elements in an organization.
Depending on the industry and specific company, their job description will vary.
However, the basic scope of work for these professionals will be able to cover four basic aspects as follows:
- Understanding information.
- Data analysis.
- Manage and build databases.
- Communicate the research back to others.
This job will generally come with a wide range of responsibilities and roles. Some of the expected and common tasks include:
The first thing that analysts need to do is define the organization’s goals. They will need to collect the correct data regarding resource availability and the business problem to do that.
You should also research the organization’s current industry situation. It will make the next steps easier.
The experts then write complex SQL statements and queries to store, collect, retrieve, and manipulate the information.
They will search from popular sources such as databases like MySQL, MS SQL Server, and Oracle DB.
They can dig up information from various sources so they can sort through new insights from there. As a result, they will have everything to build data models to improve system performance.
Processing and cleaning information will be an important job of an information analyst.
When you first collect data, it will often be quite messy and lack important value. It would not be easy to draw any conclusions from this.
Information modelers use tools and applications for statistics and analysis.
The programming language is also a great aid in making data checking more logical and logical.
Systems analysts use different libraries and packages to detect patterns and trends from complex information. From there, they can come up with never-before-seen business ideas.
A data analyst uses data visualization tools to prepare summary reports. The leadership team can use the information from here to make important decisions.
Finally, research and information systems specialists interact with management teams. Working with departments allows these professionals to ensure a smooth and successful workflow.
After learning about a data analyst’s responsibilities and job description, it’s time to explore the step-by-step process of entering the industry.
If you’re new to data analysis, start by accumulating some of the basics in the field.
Understanding the industry overview will help you determine if you’re ready for the job.
As was the norm, a bachelor’s degree is the entry requirement for most data analyst positions. However, this situation is gradually changing in recent years.
You can still dig into the basics and enhance your resume with a math or computer science degree. These related areas also have a certain influence on the work.
Also, look for alternative programs to learn more practical knowledge. We’ll dig deeper into the next section.
A higher degree will certainly bring many attractive job opportunities and career advancement for yourself.
Employers will certainly appreciate candidates who have mastered the knowledge and understanding of the latest tools.
To gain more knowledge, take courses as well as boot camps. It will give you access to the latest software programs with the most experienced professionals.
Some training centers and universities also partner with organizations to create capstone projects. These certifications are of great value, and the amount of practical experience is invaluable.
Another advantage of certifications is that you can complete them quickly, from just three months to a year.
Some of the certifications that you should focus on are certifications in data visualization, business analytics, and prediction.
A data analyst will need to master some basic tools and skills to apply their job knowledge. Some of the hard skills that any professional should have include:
- Practice with popular visualization tools like PowerBI, Matplotlib, Tableau, Bokeh, and Plotly.
- Proficient in spreadsheet and query languages such as SQL and SML.
- Mastery of frameworks and programming languages such as R, Hadoop, and Python.
- Experience with reliable data analytics platforms such as Adobe Analytics and Google Analytics.
You should start participating in projects that are full of information analysis stages. Try market research, collect and analyze data to turn them into complete reports.
Once you’ve drawn your conclusions, you can organize and present the details into beautiful visuals.
Also, try to familiarize yourself with different data types like images, videos, and structured data. It will help you learn how to do statistical analysis, confirm causality and make recommendations.
During the implementation of the project, you can also hone your soft skills to do the job better.
Communication skills and a clear, logical mind are indispensable. You will need them when working with different departments.
In addition, practice logical, analytical thinking and always analyze specific data.
Once you have the necessary skills and knowledge, it’s time to prepare a complete portfolio and enter the job market.
You will need to pay attention to your resume because employers will evaluate your qualifications here.
By presenting your projects, you will demonstrate practical knowledge and skills.
Besides that, optimize your online presence on social media as a data analyst.
The easiest step is to edit and update your LinkedIn profile to highlight the tools and skills you’ve mastered.
Once you’ve applied for a job, start thinking about the interview process. For this job, companies will have a few common questions.
Once you’ve become a systems modeler, start thinking about your future career progression. This way, you can determine what qualifications you need to achieve.
If you want to achieve higher positions, benefits, and salaries, you’ll need to earn advanced certifications. Some suitable options are Cloudera Certified Associate Data Analyst or Certified Analytics Professional.
For those who want to become data scientists in the future, take a master’s course in data science. Related fields will also help.
While an advanced degree is not a requirement, it will still give you an edge over the competition.
Data analysis jobs become attractive in the recruitment market with the above technical and tool requirements.
It also promises to bring a source of financial affluence for professionals.
According to our research, the average salary of a data analyst is $83,750 per year.
The statistic also shows that entry-level analysts with less than a year of experience can earn $64,000 per year.
As experience increases from three to five years, the benchmark will rise to $72,000. Senior analysts can get a salary of up to $81,000 per year.
Yet, years of experience aren’t everything. Other additional factors that you should pay attention to are education, certifications, and practical experience.
After people have worked in this industry for more than ten years, they will move on to other jobs. Some notable choices are data scientists, information engineers, and data architects.
New York, the District of Columbia, California, Virginia, and New Jersey are the highest paying states for data analysts.
According to the Bureau of Labor Statistics (BLS), the increase in demand for jobs will increase by about 25% from 2020 to 2030. Compared with the average gains for occupations, this is much higher.
The metropolitan areas with the highest employment rates for system modelers are Los Angeles, New York City, Chicago, Washington D.C., and Dallas-Fort Worth.
Information analysts are likely to enjoy excellent job benefits. The reason is that organizations are experiencing a severe shortage of this position.
If you have any questions about data modeler work, let’s explore the answers!
Yes, systems analysts can work from home. Along with the development of technology, the job demand in the data industry is growing strongly.
Advanced technology also supports connectivity and remote working for data modelers. According to Upwork, 73% of all employees in the industry will switch to working from home by 2028.
The day-to-day work of a data analyst is also well-suited to the remote working nature. So your opportunities are unlimited!
To learn data analysis, you can contact university courses or boot camps. Those courses can take anywhere from three months to four years to complete.
Undergraduate studies will give you an overview of basic data analysis theory. However, participating in boot camps helps students experience real projects.
In fact, no, data modelers won’t code or know much about programming languages. Their daily quest does not require this skill.
Jobs like analyzing Google Analytics data trends will not require too much of this problem.
Instead, they’ll need essential skills like data visualization software like Data Studio, Tableau, Power BI, ClickView, and statistical probabilities.
If individuals have basic SAS, Python, or R skills, information processing becomes easier.
No, you don’t need a degree to become a data modeler. However, this job will require some necessary hard and soft skills to be able to complete.
Traditionally, most people strive to complete a bachelor’s degree. That notion is still useful today.
In 2017, IBM reported that 39% of research and data analysis jobs required a master’s or even doctoral degree.
Information analytics will require you to have a strong background in math. The good news is that it mainly focuses on data science, statistics, and numbers.
Some other notable elements are linear algebra and calculus. However, much of the analytical process usually follows only logical steps.
Thanks to that, you can completely participate in this field without having too much knowledge in all areas of math.
System modelers often only use excel as a support tool for their work. Presenting data sets in excel can help experts have a clearer view and make decisions faster.
Any data you can think of can be imported into excel. From financial data to things related to human resources, everything is relevant.
The content is not the issue, but the size of the dataset does. Excel only works best with small and medium data sets.
If a data set is too large and cumbersome, look to more powerful applications like SQL or Python.
We hope that this article of ours can help you know the roadmap to become a data analyst.
You will need work experience and data analysis to impress the recruiter. The good news is that you can leverage the data around you to sharpen your skills.
Plus, take part in certificate courses, degree programs, and hands-on projects. It will help you to do real data sets.
Do not forget to share this article if you find it useful and interesting. Good luck with your career path!