Data analytics has become a fundamental pillar of data-driven businesses in today’s world.
Data analysts are essential to data analysis as they possess the knowledge and understanding to draw valuable insight from data. They have the expertise in data-related technologies and methods to sort out complex data sets, locate patterns, and make predictions about data trends.
These insights can help organizations take better business decisions, improve customer experience, detect fraud, identify opportunities for differentiation from competitors, and more.
The value of data analytics lies not just in identifying trends but also in surfacing unidentified potential opportunities. In light of its significance today, data analysts are now highly sought after professionals, with many companies investing heavily in data science initiatives to stay ahead of their competition.
What is Data Analytics?
Data analytics is the process of gathering or collecting data, analyzing it, determining data quality and drawing meaningful insight from it.
It enables data analysts to make intelligent and informed decisions based on data-backed evidence. It has become an essential part of data-driven business processes, providing data-based decision support for companies looking to optimize their operations.
In today’s data-driven world, data analysts are in-demand professionals with strong analytical skills who are able to turn data into actionable insights and decisions. Data analytics can be used in any number of fields and industries, from finance to marketing to healthcare and more. By using data analytics, businesses can enhance efficiency and productivity by leveraging data that can give them a competitive edge in the market.
Projected growth of data analytics job market in 2023
The data analyst job market has been trending upwards for the past few years and shows no signs of slowing down in the next few years. According to reports from some of the top organizations in this field, data analysts are projected to be in high demand for the foreseeable future, with data analyst job growth expected to reach new heights by 2023.
According to Business Wire (2020), the Big Data Analytics market is expected to experience rapid growth, with a CAGR of 12.3% from 2019 to 2027. This spur in Big Data Analytics uptake will mean that by 2027, the market size is projected to increase to $105.08 billion.
Reasons Why You Should Consider Starting A Career As A Data Analyst
Data analysts are in high demand and they are only set to increase as data analytics become more important in business. Not only do data analysts command great salaries, but they also enjoy high job satisfaction.
- According to the US Bureau of Labor Statistics, data analyst jobs are expected to grow by 23% between 2021 and 2031.
- The national average salary for data analysts, according to Glassdoor, is $72,311 as of January 2023. In general, the salary for data analytics ranges between $60,000 to over $120,000.
- Moreover, data analysts have reported job satisfaction ratings of 3.9 out of 5 stars on PayScale.
- Data Scientists (a career path in data analytics jobs) has ranked #3 in the list of U.S. News’ Best Technology Jobs of 2022.
With the field expanding rapidly and data analytics becoming crucial within businesses across many industries – from finance to tech – starting a career as a data analyst can be an incredibly rewarding move both financially and professionally.
Before we go on to the most important part of this article, let us first know what skills are required to be an effective data analyst?
To be a successful data analyst, specialized analytical and technical skills are essential.
Data analysts need to possess strong programming and data manipulation skills, analytical thinking and problem-solving capabilities, an ability to work methodically and accurately, as well as data visualization techniques.
In addition, data analytics involves interpreting data using various statistical techniques such as predictive analytics, which requires data analysts to have an understanding of complex mathematics and statistical algorithms. Being able to assimilate and communicate data in a meaningful way can also be beneficial, so data analysts must have good communication and presentation skills.
Thus, both technical data skills such as programming languages, structured query language and statistical analysis must be complemented with soft skills such as communication and problem-solving abilities in order to be successful in the data analytics industry.
Top technical and soft skills required to become a data analyst include Structured Query Language (SQL), statistical programming languages (like R or Python), machine learning (AI), probability and statistics, data management, statistical visualization, Microsoft excel, critical thinking skills, and some transferable skills like excellent communication skills, excellent problem solving skills, creative and analytical skills among others.
Now that you know enough details about data analysts, let’s know how you can become one!
How To Become A Data Analyst In 5 Steps?
We have mentioned 5 steps that can help you become a data analyst.
1. Get Relevant Certification/ Degree
Acquiring data analytics certification is the first step to answering your “How to Become a Data Analyst with No Experience?” query.
Investing in data analytics boot camps as well as taking relevant courses or certifications will undoubtedly offer an opportunity to gain professional credentials and provide the data analyst with a set of invaluable skills they need to succeed in this field.
Consider enrolling in a data analytics course that offer in-depth technical training. Doing so will bolster your professional credentials and enhance your marketability as a data analyst.
2. Learn Programming Languages
Data analysts have to be proficient in data analysis, data analytics, and data science. The second step in becoming a data analyst is to learn the popular programming languages used in data analytics. Knowledge of programming languages allows data analysts to automate repetitive tasks, write algorithms, and make data-driven decisions quickly and accurately.
Some of the best programming languages are SQL, Python, Java, R, Scala, C/C++, Julia, and JavaScript. Through this core knowledge and skills in various major programming languages, data analysts can create powerful data visualizations that communicate meaningful insights in an effective way.
Acquiring enough proficiency in programming can really help set data analysts apart from others, since they’ll have the ability to interpret data more efficiently than those without fundamental programming knowledge.
Therefore, learning programming skills should not be overlooked when aspiring data analysts are planning their career journey.
3. Learn How To Use Data Analysis Tools
Becoming a data analyst requires an intricate knowledge of data analytics and data analysis techniques. The third step in this process is learning how to use data analysis tools. These data-focused tools allow data analysts to collect, analyze, and interpret data quickly and effectively, helping them make informed decisions based on the insights they discover. These tools also help data analysts streamline their data management processes and improve operational efficiency.
In today’s data-driven business environment, data analysts have the responsibility of being at the forefront of data analytics. Data analytics tools are becoming more and more important for data analysts to properly analyze data and extract actionable insights to help inform decision making.
Learning how to use analytical tools is therefore no longer just a nice-to-have skill – it is a must for any data analyst looking to remain data-savvy and educate their organization on how best to utilize data.
Familiarize yourself with data visualization software, programming languages, and databases used in data analytic projects. As such, mastering the use of data interpretation tools is key for realizing data-driven success as a data analyst. This knowledge is essential when working on programming projects. Mastery of these tools can help data analysts to produce more accurate results faster, leading to higher productivity and better performance on the job.
4. Understand Database Concepts And Algorithms
Given the rapid evolution of data analytics, data analysts must understand database concepts, algorithms and methods in order to stay ahead. Database concepts such as data integrity, data types, relationships, data normalization and models provide data analysts with the foundation they need to organize and store data effectively.
Additionally, algorithms are responsible for processing and manipulating data efficiently, so it’s important for a data analyst to have a strong understanding of these processes when analyzing data from large datasets or complex data structures.
Understanding database concepts, methods and algorithms enables data analysts to expertly craft solutions that yield accurate data insights and ensure the correctness of their work.
Ultimately, these skills are key components for success as a modern-day data analyst.
5. Learn How To Use Data Visualization Tools
Data analysts are essential for data analytics jobs of turning data into insights that can be understood by stakeholders who may not possess the same technical knowledge.
To ensure data communicated is comprehensive and effective, data analysts must learn how to use data visualization tools as a way of presenting data through visual storytelling techniques. By learning to visualize data, data analysts can help stakeholders understand data quickly, making it easier for important decisions to be made based on the information.
Tailoring visuals to make the data as accessible and digestible as possible can help focus conversations on the right topics and inspire ideas that might not have been previously considered possible. Furthermore, in this data-driven world, developing data visualization skills sets data analysts apart from others in their field and increases their marketability to employers.
Therefore, learning how to use data visualization tools is a valuable skill for any successful data analyst.
Conclusion
It is EASY to become a data analyst with the right data analytics courses.
With these five steps, data analysts have a great starting point to jumpstart their career and become successful data analysts by 2023!
But what is interesting to mention here is that all the above-mentioned 5 steps can be covered in the first step itself if you go for the right data analytics training program!
It would not only help you get complete foundational knowledge and required data analyst skills, which includes strong math skills, analytical skills, strong technical skills, programming skills and other in demand skills, but also help you get practical exposure and insights from industry experts.
Once you complete your course and get your data analyst certificate, it’s time to write your resume, create a data analytics portfolio, start a job search and apply for a data analyst job and become a data analyst.
Ready to start a flourishing new career in the data industry?
Data Analysts FAQs
Is it hard to become a data analyst with no experience in computer science?
No. If you choose an appropriate data analytics course and put in some effort to acquire required skills (technical data skills and transferable skills) and foundational understanding of it, then within a few months you can easily start getting a job as an entry level data analyst or junior data analyst.
What are some of the data analyst job roles or data analyst career paths?
Data analysts can work in various industries and roles. Normally, a data analyst’s career path starts as a junior data analyst or entry level data analyst, and then goes on to become a senior data analyst, analytics manager, data scientist or chief data officer.
What skills are required to become a data analyst?
As mentioned in the article above, in order to become a data analyst and work in the data analytics field, one must have necessary technical skills like math skills, machine learning, data visualization, regression analysis, SQL, predictive analytics skills among other core skills, as well as have transferable skills like communication skills.
