You at least know that in order to become a data analyst, you need to extract insights from massive data sets and possess critical data analysis abilities.

Companies across all industries have significantly invested in big data and expanded their analytics departments, particularly in the telecommunications, insurance, advertising, financial services, healthcare, and technology sectors. This has created a field of data analytics that is ripe with opportunity.

 

That expansion is expected to last for a very long time since sectors that have lagged behind in adopting big data analytics, like education, government, and manufacturing, have committed to stepping up their big data analytics efforts in the future.

 

1. Learn the Basics of data analytics

 

Learning the fundamentals of data analysis and its tools, such as advanced Microsoft Excel, SQL, Python, and R programming languages, Spark and Hadoop for number-crunching, and Tableau, Matplotlib, or ggplot2 for creating stunning visualizations that bring data to life, should be your first step when considering how to become a data analyst.

 

These core data skills can be learned through a data analytics course, which will give you a firm foundation across all of these platforms and the opportunity to obtain practical experience with the following:

 

• Data handling 

• Statistical programming 

• Programming languages 

• Data Cleaning 

• Data Visualization

 

1. Take on tasks to hone your data analytics skills

 

You must gain a firm understanding of the fundamental tools used by data analysts if you wish to work in the field. When you've finished, you can start using what you've learned. In order to be successful, data analysts must stay current on the newest and best tools available, such as:

 

• Data analysts rely on spreadsheets and querying languages like XML and SQL.

• Python, R, and Hadoop are a few programming languages and frameworks that Data Analysts frequently employ.

• Data analysts often use visualization tools like Tableau, PowerBI, Plotly, Bokeh, and Matplotlib.

 

They must also know one or more of the top platforms for data analysis, such as Google Analytics and Adobe Analytics. Along the way, you'll also be honing the soft skills that set the top data analysts apart from the rest of the pack:

 

• A keen sense of detail

• A capacity for both creative and analytical thought

• Superior communication abilities

• A mathematical mind

 

1. Create visualizations and get presentation practice

 

You should use tools like Tableau, PowerBI, Bokeh, Plotly, or Infogram to become a data analyst. Learn to create your own custom visualizations from the start with the goal of letting the data speak for itself.

 

Even during this step, Microsoft Excel is used. Although the fundamental idea behind spreadsheets is simple—creating calculations or graphs by correlating the data in their cells—Excel continues to be incredibly helpful after more than 30 years and is practically essential in data science.

 

However, making visualizations is only the first step. Data analysts use these visualizations to present their conclusions, which calls for excellent presentation skills.

 

1. Create a portfolio for your work as a data analyst

 

Choosing how you will exhibit your data skills and knowledge is one of the most crucial tasks to consider while determining how to become a data analyst. A professional portfolio is essential, and to get going, you should post the code you've created (even if it was for class assignments) on GitHub to demonstrate your skills and start building your portfolio.

 

3 Pointers for Creating a Data Analyst Portfolio:

 

• Showcase your code on GitHub or a similar portfolio website.

• Join networks for data analysts like Kaggle to expand your knowledge and discover inspiration.

• A personal project should be researched, developed, and finished while being meticulously documented and visually produced.

 

1. Apply to Useful Data Analyst Positions:

 

You can find Data Analyst jobs in a wide range of industries with data capabilities. The roles listed below might be entry-level or more senior data roles and heavily rely on data analytics.

 

Many other versions are available; new uses for data analytics are always being created, and even the positions listed here will change as data analysis becomes more commonplace.

 

According to consultancy company Mckinsey & CoThe demand for Data Analyst jobs may exceed the expected supply of data experts by 50-60% due to the highly dynamic nature of the industry.

 

How can I become a data analyst, without prior experience?

 

The first step in learning how to become a Data Analyst without any prior expertise is to pick up the necessary data skills that can be gained from a data science certification course. While some of these abilities are simpler to learn on your own, others are more difficult.

 

Nevertheless, the data analytics industry is so vast and varied that it can be challenging even to know where to begin when learning data analysis. The ideal way to start a profession is with a structured learning environment that systematically goes over all the fundamentals. This way, you'll know immediately what you still need to study.

 

• Start by studying yourself:

 

You may obtain a variety of information for free on the internet. If you are disciplined and motivated, you might think about learning data analytics on your own. You should learn and practice the following skills: Python, R, data visualization, Statistics, and SQL. Start with a Python tutorial if you want to!

 

• Try out projects using data analytics:

 

It's time to put your knowledge into practice with practical projects. You can consider enrolling in one of the top online data analytics courses or earning a data analyst certification after gaining some technical proficiency. Verify that your chosen course or certification will enable you to create data projects and deliver your findings.

 

• Establish a Portfolio:

 

You can compile your completed work into a portfolio once you've gained experience. Before employing you for a position as a data analyst, businesses will look at your portfolio to discover your skills.

 

• Apply for internships and Jobs

 

Prepare your portfolio and resume for entry-level data analyst opportunities by organizing them. You might contact the network you've established through your assignments, classes, and self-paced study. Job sites like Indeed are a terrific way to discover potential employment prospects.

 

You decide how long it takes to become a data analyst. Depending on your degree of dedication, the number of hours you put in each week, your chosen educational path, and your networking skills, it could take a few months to a few years.

 

Conclusion:

 

Not everyone will have the same response to the question of how to become a data analyst. You might pursue a degree for more structure or choose networking and independent study to cut costs and time commitment.

 

Online classes are also an option, and they are more structured than complete self-study. Regardless, I hope that this article has assisted you in choosing the most suitable route to a career as a data analyst. Look at Learnbay's data science course with placement if you want to enhance your data analytics skills and credentials and get a job at MNCs.

Publication: 24/01/2023 06:05