Data has become an integral part of our lives. The amount of data generated globally is estimated to be two and a half quintillion bytes daily. It won’t be an exaggeration to say that data dominate our digital world today.
The International Data Corporation (IDC) reports that the global big data analysis has been expanding at a rapid pace, leaping from $189 billion in 2019 to $274 billion in 2022.
With this rapidly expanding demand for analytics, data analysts are needed more than ever. This is the perfect time to sign up for a data analytics course and begin your data science and data analytics journey. The pandemic has opened up various online data analytics certification courses as well. A rewarding data analytics career requires proper training and persistent efforts.
Digital transformation is the new buzzword, budding with many opportunities. There are so many exciting career development options in various sectors such as telecommunication, education, manufacturing, banking, fitness, healthcare, and many more.
To become a successful data analyst there are specific skills required to thrive in this field and increase the odds of getting a job. Tech-centric qualifications, a background in Mathematics and Statistics aid in learning about data analytics. Firstly, let’s understand what a data analyst does,
Data Analytics
A data analyst uses technical skills to analyze data so stakeholders can understand data and use it to make strategic business decisions. They deal with ‘raw’ data and develop meaningful insights in the process. They also ensure that data is of high quality to derive valuable information out of it.
Data Analytics requires a specific set of toolboxes to process data using a variety of technical and analytical skills. Your data analytics course should incorporate the following set of tools to help you master the subject,
- Data Visualization
Data visualization is a technique used to present data findings graphically or using other illustrations. Visualization is much more simple to comprehend even for a layman. Data analysts help business stakeholders to identify patterns and understand complex ideas. One can gain deeper insights into the company’s situation, help in decision making, and discuss future roadmaps.
Data visualization has become an important skill. A recent study conducted revealed that graduates preferred learning data visualization to analyze data and derive insights.
- SQL
Structured Query Language (SQL) is a database language that you need to be familiar with as a data analyst. SQL is a standard means for querying and handling data. Even though SQL was discovered in 1970, the language is relevant even today and SQL has a foothold in many companies.
SQL enables data analysts to store data, relate multiple databases, or change database structures. If you want to deal with big data, learning about SQL is a primary skill. Advanced versions of SQL such as MySQL offer opportunities to delve deeper into relational database management systems.
- Microsoft Excel
You start visualizing a huge sheet with multiple cells when you think of Microsoft Excel, but there is a lot more analysis power associated with this tool. Microsoft spreadsheet is used by 750 million people worldwide. Excel methods like Macros and VBA lookups are still widely used for quick analysis. Accounting, payroll, and project management can be easily undertaken using Excel. Analysts can save a lot of time and avoid repetition by using Excel. To manage bigger datasets you need to be well-versed with other programming languages.
- R or Python Programming languages
R or Python programming languages are better suited to manage huge data effectively. As compared to Excel, these programming languages are much more advanced and 10 times faster.
R’s syntax and structure allow users to accomplish analytical work, it also encompasses built-in, user-friendly data organization commands. It appeals to many businesses as it handles complex and large volumes of data.
Learning python should be a top priority and quintessential for your data analyst course. It offers remarkable libraries, many of which pertain to artificial intelligence (AI). Python’s applicability to AI is what sets it apart.
Employers don’t bother much about which programming language a data analyst uses as long as the analysis is accurate and meaningful.
- Machine Learning
Not every analyst works with machine learning, however, understanding it can give you a competitive edge over others. Artificial intelligence and predictive analytics are the hottest topics today and understanding machine learning is a key component in data science.
You will need your statistical programming skills to advance in this area, however, there are tools like Orange that can help you build models to start with.
- Linear algebra and Calculus
Advanced mathematical knowledge is a prerequisite to becoming a data analyst. Many people prefer to pursue their post-graduation in mathematics to gain a conceptual understanding of the real-world analytical practice.
Linear algebra and Calculus are essential to understand the basics of data science deeply. Linear algebra is used for machine and deep learning. Calculus is used to build functions that teach algorithms. Learning advanced mathematics will enable you to understand how algorithms work.
Along with subject-specific skills, you will also need to work on your soft skills to excel as a data analyst. The data analyst certification course offered by SkilloVilla ensures that you learn soft skills and subject-specific skills both. The following soft skills should be included in your analytics course,
Critical thinking
A data analyst uses data to find answers to specific problems, this means they need to figure out the question that needs to be asked in the first place. They also need to find connections in the data, which are not normally observed. This requires critical thinking skills.
You can develop these skills by asking basic questions about the issue at hand and simplifying the explanation for business stakeholders. It is important to think like an analyst to derive meaningful outcomes.
Communication skills
Along with critical thinking skills, a data analyst will also require good communication skills. It doesn’t matter if you’re the most talented data analyst if you can’t communicate the patterns you see to your audience well.
As a data analyst, you should be able to explain highly technical points with your peers, with a high-level explanation. Your audience should be clear with what business-centric decision they need to make for the company’s growth. Hence, you need to be able to communicate well and effectively.
Presentation skills
Presentation skills do not come naturally to everyone, but one can learn them over time. There are many tips available to brush up on your presentation skills, the more you practice, the better you get at it. Data visualization and presentation go hand in hand. You should be able to present your analysis effectively so that others can make sense out of it.
To conclude, everyone’s educational journey will be different. It solely depends on what choices you made. Looking for a data analytics course that focuses on the above-mentioned skills with real-world applications will help you understand the subject in depth. It will also give you the correct conceptual foundation and practice to solve real-world problems.
Looking for a data analytics course online?
Skillovilla is an online platform offering a holistic data analyst certification course. You can begin your data science journey at a click of a button. Skillavilla enables you to become a successful analyst who can transform yourself through learning. It is particularly designed for young graduates who wish to secure their dream job. The data analyst certificate programs at Skillovilla will give you the competitive edge while applying for jobs and make your journey seamless and joyous. You will also receive an online data analytics certificate to strengthen your resume. Book a free consultation today!
