How To Become A Data Analyst in US? Complete Guide

Data Analysis is the talk of the town and is undoubtedly the most sought-after career in 2021. Since so many people have started discussing the advantages of becoming a Data Analyst, youngsters have become eager to learn more about this field. If you are a beginner in python and data science, upGrad’s data science programs can definitely help you dive deeper into the world of data and analytics.

Like any other profession, there is a set of skills that one must acquire to start their career, so let’s look at everything you should know before you embark on the journey of becoming a Data Analyst. We are here to cover all your questions and give you a holistic look at this job profile. Make an informed decision by skimming through this article, packed with information about data analysis. 

The Role Of A Data Analyst

Companies hire Data Analysts to collect, process, and analyze large sets of data. These professionals are the gatekeeper of an organization, which helps stakeholders to understand data for making business decisions. One can identify several facts and trends with the help of data analysis. They increase the yield of a company by solving problems and answering questions through assessment of the data. So, after forming a conclusion from data, they prepare a report on their analysis and present it to the management.

Job Description 

A data analyst is responsible for maintaining and designing databases and systems for various departments, creating dashboards, programming, using tools like Tableau and business intelligence software. Most data analysts collaborate with management, IT teams, or data scientists to gather or clean data for business insights or uncovering trends. 

Responsibilities of a Data Analyst

A data analyst is responsible for maintaining databases and data systems, which also includes fixing any errors in codes and other problems. They reorganize data from primary and secondary sources to make it more readable. Data analysts use statistical tools to understand data and pay attention to trends or patterns that could be valuable for the company. Apart from that, they also collaborate with people, develop new policies for data governance, and suggest system modifications. 

Steps To Become A Data Analysis 

If you are wondering about how to become a data analyst? Go through the steps given below to get a clearer picture to determine if it is the right career path for you. 

• The first thing you need for considering data analysis as your career is a degree in mathematics, statistics, computer science, or other equivalent fields. However, you can even enter the field with a bachelor’s/master’s degree in other disciplines such as Psychology, Economics, etc. 
• Learn the skills required for a data analysis job. You will know more about these skills ahead. 
• It is vital to have proof of your skills. So, consider learning from a source that provides certification or doing a few projects that you can use in your portfolio.
• As a newbie in the field, you need to get the first job to create your breakthrough. Start hunting for entry-level data analyst jobs as soon as you complete the learning part. 
• Finally, go for a master’s degree in data analytics to take your career to a new level. A master’s degree promises better job opportunities and higher pay. 

Qualifications And Skills Required For Data Analysts

1. Programming Languages

Programming languages are used in data analyses for data visualization, statistical analysis, data gathering, and data cleaning. The two most common programming languages known by Data analysts are SAS and R. There are multiple boot camps, Youtube videos, and courses that can make you proficient in these languages. 

2. Data Visualization

A crucial part of data analysis is data visualization, where you must know about the usage of proper charts and scale for your audience. This skill develops with time, and you can only consider yourself successful when everyone – including non-technical staff – understands your data findings. 

3. Data Cleaning, Mining, and Munging

Sometimes, a data analyst needs to clean the data and process it all using a programming language. Such scenarios occur when a professional has to gather unstructured data not neatly stored inside a database. 

4. Database Querying Languages

Data analysts must possess a sound knowledge of querying knowledge that is required in the field. Thus, data analysts use some of the most common languages are SQL and other variations such as PL/SQL, PostgreSQL, and T-SQL. 

5. SQL Databases

A data analyst extracts information from different tables with data storage that helps in analysis. SQL is one such database that is relational and includes structured data. 

6. Data Warehousing

Data warehouses are used along with querying languages for finding and managing data. Data analysts create these data warehouses using multiple sources, and they usually work in the back-end department. 

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7. Machine Learning

Even though machine learning is not an expected skill for most data analyst jobs, it is an excellent skill to have in your arsenal. If a data analyst is skilled at machine learning, they become a highly valuable professional. 

8. Communication Skills

How will the company benefit from your skills if you are excellent at programming, creating reports, and analyzing data, but you cannot convey your findings? Therefore, effective and smooth communication is an essential skill for data analysts because you must explain your data. 

9. Critical And Creative Thinking

A data analyst should present data and facts and pose new questions to strengthen a company’s understanding. Therefore, analytical and creative thinking becomes essential to analyze data and think of creative outlooks. 

Data Analysis Tools

• Tableau: This tool comes in handy for aggregating and analyzing data. It assists data analysts by creating different dashboards for everyone, along with your creation of visualizations.
• Github: If you are not part of a certified program and need a valid method to prove your abilities. Creating a few projects on Github will help you set your portfolio because it is a platform that helps in building and sharing projects.
• AWS S3: Cloud computing services are rising, and one of them is AWS (Amazon web service). Data analysts use this to store and retrieve large amounts of data. 
• Google Analytics: GA or Google Analytics is customer-oriented, where data analysts can easily understand customer data. These datasets help in improving the call to action (CTA) on landing pages. 
• Jupyter Network System: Jupyter notebook is used to test and run codes by data analysts. People from a non-technical background prefer the simpler version of Jupyter due to the markdown feature. 

Job Outlook

Change is the only constant, and all data analysts should be prepared for a change because their roles are getting more advanced every day. An experienced data analyst transforms from a data analyst to a data scientist. 

Market research analyst and management analyst are two professions that will grow 18% and 11%, respectively. The role of a data analyst is becoming vital across all industrial sectors, making them an indispensable part of organizations. As companies and individuals keep churning out data, the demand for data analysts will continue to grow in the upcoming years. By 2026, the global data analytics market is expected to grow at a CAGR of 28.9%, generating a revenue of USD 132,903.8 million. 

Conclusion

Data analyst is one of the highest-paying jobs today, with a demand for these professionals worldwide. This is the perfect time to become a data analyst because companies rigorously hire these individuals to boost their profit. Once you have all the right skills and qualifications needed, you will never have to worry about questions like “how to get a data analyst job?” or “how can I start working as a data analyst?” because offers will come knocking at your doorstep! After your bachelor’s and entry into the job market, you should enroll yourself in an MSc Data Science course. This will give you an edge over your contemporaries and bring in new opportunities. An MSc in Data Science from Liverpool John Moore University or a Professional Certificate Program in Data Science for Business Decision Making are two excellent choices for aspirants who want to upskill while continuing their professional commitments.