How to Become a Data Analyst from Scratch?

Data analysts are in high demand today. They collect, clean, and analyse data to help businesses make better decisions and achieve their goals. If you want to start or shape your career in data analysis, here is a step-by-step guide on how to become a data analyst.

Who is a Data Analyst?

Data Analysts collect, cleanse, transform, and model data to find meaningful and useful information supporting decision-making processes. Every data drive business needs analysts to make the best of their available data, make the right investment decisions, understand customer behaviour, assess risks, or decide on capital allocations.

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How to Become a Data Analyst?

A good data analyst must have certain technical skills to perform more easily daily, solving the various situations that may arise in information analysis and organizational relationships. So, if you are considering starting a career in data analysis, the tips below can help you –

Fulfil the Educational Criteria 

Training in STEM (Science, Technology, Engineering, and Mathematics) qualifications is the best starting point to acquire the basic skills necessary for this profession. However, to work as a data analyst, you must have an undergraduate or a postgraduate degree in a relevant discipline, such as:

• Computer science
• Economics
• Information management
• Mathematics
• Statistics
• Marketing
• Finance
• Business information systems

Companies prefer hiring candidates with advanced Data Analysis or Data Science degrees. Some popular postgraduate qualifications are offered in subjects such as M.Sc. in Data Science, M.Sc. in Business Analytics, M.Sc. in Data Science and Analytics, and M.Sc. in Big Data. Candidates should also have excellent math, statistics, basic programming knowledge, and an eagerness to crunch the data.

To learn more about data science, read our blog on – What is data science?

Develop a Strong Knowledge of Programming

The coding knowledge and experience required for a data analyst are not as high as that of a data scientist. However, you are expected to have the ability to explore and analyze large data sets. This is accomplished through data visualization tools such as Power BI and Tableau. However, not all companies can afford to buy these tools. So, the ubiquitous option is to use Python and its extensive data visualization libraries. Python is the best choice for anyone new to coding. You’ll get to manage with basic Python skills and master the key libraries required for this role, including Pandas, Matplotlib, Seaborn, Numpy, and Scikit Learn.

Basic knowledge of SQL – SQL is one of the most talked-about data analyst skills. Knowledge of SQL would give you control over accessing data from various sources. Understanding data recovery and integration will help you manage your data well.

Hands-on with Data Visualization Tools

Data analysts use data visualization tools on a very regular basis. Mastering these data visualization tools does not require technical knowledge. Most of these tools work by clicking and dragging. The important aspect is understanding the various functionalities required to analyze and visualize data using these tools. The more versatile your skillset is, the more likely you are to work on challenging, compelling, and business-transforming projects.

MS Excel is the most basic tool, yet it is used in all companies and professions. Many features of Excel, such as pivot table creation, formulas for data manipulation, and graphs for visualization, are used effectively to develop highly remarkable dashboards.

Check Out Our Data Analysis Courses

Become a Storyteller

The dashboard consisting of all the charts and data is not enough if it is simply colourful and pleasant to look at. Each item on the board should convey a message and conclusions with a solution-based story for stakeholders. Thus, a business analyst must be able to convey a history of their findings without confusing the user. The story should be concise, simple, and accurately highlight the problem.

Learn Machine Learning

Machine learning enables organizations to gather greater insights from structured and unstructured data compared to what they could otherwise gather with traditional business intelligence solutions. In fact, it enables leaders to plan and take action. Applying machine learning and analytics more broadly enables you to respond faster to dynamic situations and get more value from those rapidly growing data treasures, making it an inevitable tool for data analysis.

It is clear that analytical skills are the great importance for data analysts. These skills include gathering, classifying, and analyzing all kinds of particular raw data. Therefore, if you want to be a professional data analyst, you must expand your analytical skills and thinking. Analytical skills help you see a challenge or situation from different perspectives.

Acquire Domain Knowledge

Knowing the domain means understanding specifics about the industry and the particular company you work for. For example, if you work for a company with an online store, you may need to understand the nuances of e-commerce. Conversely, you may need to understand the systems and their functioning if you analyse data on mechanical systems.

Domain knowledge varies from industry to industry, so you may need to do your research and learn quickly. Regardless of where you work, if you don’t understand what you’re analyzing, it will be difficult to do it effectively, making domain knowledge a key data analyst skill.

A data analyst must have a good command of logic to understand algorithms and complex structures easily. Therefore, you can quickly interpret native solutions, such as CRM or ERP systems, and run complex reports. In addition, improving logical thinking will help you solve business problems more easily.

Become a Decision Maker and a Problem-Solver

These skills are the foundation of data analysis. The main job of a data analyst is to provide the correct information for decision-making and problem-solving. This is why it seems to be a perfect skill required to be a data analyst.

Communication is the Key!

Excellent oral and written communication skills are extremely important to a data analyst. You should be able to communicate effectively with teammates to prepare, present, and explain data. Communication is key to collaborating with your colleagues.

Explore these online degree programmes–

Take A Data Analysis Course

You may consider taking a data analysis course to gain the most required skills. Here are some of the popular data analysis courses for your perusal –

• Data Analysis and Presentation Skills: the PwC Approach Specialization by Coursera
• Data Analysis with Pandas and Python by Udemy
• Data Analysis with Python by Coursera
• Intro to Data Analysis by Udacity
• Foundations for Big Data Analysis with SQL by Coursera
• Tools for Exploratory Data Analysis in Business by Coursera
• Microsoft Power BI – Up & Running With Power BI Desktop by Udemy
• IBM Data Analyst Professional Certificate by Coursera
• MS-Excel Mastery: Data Analysis & Dashboard Reporting by Udemy

Conclusion

The role of a data analyst is very lucrative and high-paying. However, if you want to become a data analyst without having any prior experience, then you should strengthen your basics of data analysis first, take up some data analysis projects and build your profile. Some project work experience and some added skills would make your data analyst resume stand out and can help you land your dream job.

All the best. 

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