In 2020, the global volume of data produced and captured was just over 64 zettabytes. According to statistics, this figure will quadruple to 180 zettabytes by 2025. To put this into perspective, a single zettabyte is equivalent to trillions of gigabytes of data. Is it possible to extract significant insights from all of that data? Yes, with the use of data analysis tools and procedures.
The capacity to make sense of such huge amounts of data is precious for various enterprises. Within those seemingly limitless data troves are diamonds that can help businesses better understand their clients, design more effective campaigns and outperform their competition. It’s up to data analysts to make those data-driven decisions possible.
All of these factors contribute to a high need for data analytics professionals. Plenty of jobs are beneficial, but it also means more competition for each open position. In this article, we’ll teach you how to study data analysis path and take steps to improve your prospects of a successful data analysis job.
How to Study Data Analysis Online
1. Get acquainted with more free courses online
From the algorithms that recommend your next Netflix binge to the accuracy behind supply chain management, data plays an important role in places we don’t even realize. Business leaders, in particular, rely on data to make sound decisions that define their firms’ performance.
To become an expert data analyst, you must first lay a firm foundation, and free courses can help you do just that. Online classes give a clear path and the required information to help you study while building your portfolio.
2. Build a case study by collecting and analyzing free data
Data analytics isn’t a spectator career; it’s a hands-on learning experience. Both Ciabarra and Van de Wiel believe that before you consider finding a job or if you don’t know where to begin, you should attempt collecting, manipulating, and analyzing data in your spare time.
Use internet resources such as Google Dataset Search, Data.gov, Kaggle, and FiveThirtyEight, or follow your interests and insights to collect data yourself.
Searching for information on the internet is an important ability in the data era. According to a poll of 150 IT, technology, and data analytics specialists from US retail, technology, and nonprofit organizations, publicly available web data is critical for businesses and nonprofits to achieve their objectives. According to the poll, 94% of these firms rely on this data daily to run efficiently and successfully.
3. Attend data-related conferences and be proactive
Conferences can be beneficial experiences for those interested in learning data analytics. While no two conferences are alike, the major ones often provide an opportunity to hear keynote speakers, attend workshops and breakout sessions, comprehend cutting-edge data, and network with other analytics professionals.
So far, the notable data-related conferences are DataCamp’s Radar: The Analytics Edition, the Gartner Data and Analytics Summit, and Coalesce. Each event focuses on data anomaly detection, data engineering, machine learning, and AI.
4. Increase your technical data analytics knowledge
The next step is to build on your core skills. A few glances through LinkedIn, Indeed, and Glassdoor job boards reveal that the major talents stated on job listings are data visualization, machine learning, and programming.
SQL knowledge, experience dealing with massive datasets, Python, data visualization tools such as Tableau or Power BI, and deriving insights from complex data are all common skills listed on job boards.
5. Identify your data analytics soft skills
Aside from programming languages such as SQL, R, and Python and applications like Microsoft Excel, Google Sheets, Power BI, and Tableau, you should have a productivity attitude.
Both experts clarify that it is fine if you were not born with a talent for arithmetic and that if you enjoy the task, you will learn as you go. However, certain indicators can predispose you to success in the data analytics field.
What is An Average Data Analyst’s salary?
According to the job listing website Glassdoor, the average salary for a data analyst in the United States is $76,293. The US Bureau of Labor Statistics reports a median annual pay of $83,640. Meanwhile, ZipRecruiter reported $82,640.
While the range varies, each salary amount is much greater than the average yearly salary for all jobs in the United States. However, several factors can determine how much you will earn as a data analyst.
How to become a data analyst with no experience
To become a data analyst with no experience, the first stage is to develop the requisite skills. Following that, you must select the direction you want your career to go. Finally, begin selling yourself as a data analyst, network, and advance through the ranks of data analytics.
Here are the steps you must follow to become a data analyst.
1. Determine your ideal career path
If you like to work from home, becoming a freelance data analyst will be a wonderful fit. Once you have a large clientele, you can act as a consultant for organizations.
Alternatively, you can begin as a junior data analyst and advance to data scientist after honing your programming abilities or obtaining a degree in data sciences.
Another option for junior data analysts is to enhance their abilities and expertise by becoming senior data analysts. If you acquire strong leadership skills, you can eventually advance to the position of manager or Chief Technology Officer.
Some firms demand individuals in managerial positions to obtain a Master’s degree in data analytics. So, if you intend to advance your career in management, consider obtaining a suitable higher degree along the way.
If you want to specialize in your profession, choose a certain department. For example, as an entry-level data analyst, you can go to a marketing analyst by honing your marketing skills.
Similarly, if you are more interested in technical solutions, you can advance to the position of marketing or operations analyst with sufficient experience. You need to tailor your job path to your financial goals and personal interests.
2. Take a course or earn a certificate
Once you have settled on a career path, enroll in a data analytics course or certification. Look for a broad one so you can apply for different job titles within the niche.
A suitable education in data analytics provides the following benefits:
- Mentorship: The top data analytics courses provide one-on-one instruction from a mentor. Aside from motivating young or career-changing professionals, it also allows newcomers to receive feedback on their work.
- Skill Building: A well-curated data analytics course will also help you improve your existing skills and build new ones, allowing you to flourish in the area.
- Hands-on Curriculum: Reading every book on data analytics will not prepare you for the real world. On the other hand, a well-structured course will teach you about data analytics ideas through handpicked materials and hands-on tasks. You can then use these tasks to expand your portfolio.
3. Build a Portfolio
A portfolio will help you get a job since it demonstrates credibility and showcases past projects you have worked on. Your portfolio should normally highlight the following:
- Your technical skills
- Your creativity in research
- Data analysts ability
- Ability to draw insights
- Teamwork and communication skills
4. Revamp the Necessary Skills Needed for Your Target Data Analyst Job
By this time, you should have a solid understanding of the subject and some basic skills. Now, you must connect your next actions with your desired job. Identify your existing soft talents and decide which ones require further practice.
For example, you may have exceptional research skills but cannot give presentations. Keep in mind that senior analysts must deliver their findings to executives and stakeholders in an organization.
So, if you wish to continue on your predetermined professional path, you should work on gaining these abilities or improving the ones you believe are essential for the next job title in your career.
The List of Data Analyst Courses
1. Complete Data Analytics Program by Geeks for Geeks
The first data analysis courses are comprehensive and will help you go from beginner to advanced analyst. This course will provide you with the necessary tools and abilities to become a knowledgeable and industry-ready Data Analyst expert, including Jupyter Notebook, Numpy, Pandas, Excel, SQL, Tableau, and others.
You may improve your skills by taking our Data Analytics Courses. You can learn how to analyze, visualize, and report data using Python, SQL, Excel, and Tableau. Discover hands-on, real-world projects and much more.
Syllabus:
- Excel
- Advance Excel
- SQL Techniques
- Advance SQL
- Introduction to Python for Data Analysis
- Exploring Data with Pandas and Matplotlib
- Real-time Python Projects
- DeIve into PowerBI
- Power BI for Real-Time Analytics and Advanced Features
2. Google Data Analytics Professional Certificate
This is a beginner-level data analysis course that will teach you in-demand skills and get you job-ready in less than 6 months. You’ll learn fundamental analytical skills and tools, as well as how to clean and arrange data for analysis. You’ll learn how to visualize and convey data insights using dashboards, presentations, and standard visualization tools.
Syllabus:
- Basic of Data
- How to Make Data-Driven Decisions
- Prepare Data for Exploration
- Process Data from Dirty to Clean
- Analyze Data to Answer Questions
- Share Data Through the Art of Visualization
- Data Analysis with R Programming
- Google Data Analytics Capstone: Complete a Case Study
3. Microsoft Certified: Power BI Data Analyst
This Microsoft training teaches the essentials of Power BI. To take this exam, you must have the basic abilities required. You should be comfortable using Power Query and writing expressions after taking Data Analysis Expressions (DAX) classes. You understand how to analyze data quality. Furthermore, you understand data security, particularly row-level security and data sensitivity.
Syllabus:
- Get started with Microsoft data analytics.
- Prepare data for analysis with Power BI
- Model data with Power BI
- Build Power BI visuals and reports
- Manage workspaces and datasets in Power BI
4. Business Analytics by Harvard University
Harvard University’s data analysis courses can help you build a data mentality as well as analytical abilities for interpreting and communicating data while applying concepts to real-world business situations. This course begins with basic descriptive statistics and moves on to regression analysis.
You’ll study course principles while performing A/B testing on a website, sampling warehouse inventory, projecting home video purchases based on box office performance, and anticipating hotel front desk staffing needs. Throughout the course, you will be given clear instructions on how to apply analytical approaches in Excel.
Topics:
- Business Intelligence
- Business Analysis
- Career Development
- Excel
- Professional Development
- Self-Improvement
Conclusion
The rise of big data has transformed the way organizations operate. With an increasing number of firms realizing the enormous benefits of hiring data analytics professionals, the prospects for workers in this industry are looking brighter than ever. If you follow these steps, you’ll have a better understanding of where you stand in the data tsunami.
