THE PARADOX OF SUPPLY AND DEMAND IN TECHNOLOGY AND DATA INDUSTRY
Effective data collection and analysis are crucial for the success and growth of businesses in today's digital era, characterized by a data explosion. As a result, the technology and data analytics sectors have become highly attractive industries in recent years.
However, there exists a paradox in the data analytics industry regarding the supply and demand for skilled labor. While companies face a shortage of qualified personnel, especially experts, many graduates in data-related fields find themselves unemployed or underemployed.
So, how to build and develop well career path in technology and data analysis industry? Let's explore the keys to building a successful career path in this field, as shared by Nguyễn Minh Châu, Customer BI Manager at Home Credit.
Is data analysis too difficult, leading to the current supply and demand paradox?
Data analysis is not really difficult profession. You need to understand data, coding, operational processes, and business operations to analyze data effectively. The most important aspects are process thinking and understanding the business. Understanding the business issues and the requirements is crucial for effective analysis and solution generation. If the problem is misunderstood or misinterpreted, the analysis becomes almost meaningless.
What are the essential requirements to become a good data analyst?
A good data analyst needs to possess three groups of skills: technical skills, functional skills, and soft skills.
- Technical Skills: These include proficiency in Excel or Google Sheets; statistical analysis and visualization tools and software like Power BI, SAS, Tableau; proficiency in at least one programming language such as R or Python; knowledge of SQL and experience working with Data Warehouses, Data Pipelines, Data Lakes; and familiarity with big data tools like Hadoop, Hive, Spark.
- Functional Skills: These include statistical skills for data analysis, analytical skills for research and forecasting, problem-solving skills, data visualization skills, and project management skills.
- Soft Skills: These include teamwork, communication, presentation, negotiation skills based on data, and curiosity to explore unusual phenomena.
How did you start your career in data analysis, given that the field was not well-developed in Vietnam and there weren't many training programs available at the time?
I started my career as a data analysis intern at Home Credit after graduating. At that stage, I had little knowledge of the field. I just knew that the industry involved working with numbers but was unsure of what specific issues or tasks were involved. With guidance and support from my superiors and colleagues in programming and the tools used for accurate and efficient data analysis, I gradually understood the field better and stayed with it until now.
After gaining a solid foundation in programming and data analysis, I began to delve deeper into the profession, business models, and company operations to analyze more effectively and logically. Without a thorough understanding of processes and business models, data would just be numbers, and I wouldn't grasp what they reflect or whether the analysis results are accurate. The closer the analysis is to reality, the more accurate and effective it becomes.
How important is data analysis for businesses, and how to effectively apply expertise in work?
As I mentioned, understanding processes and analyzing based on operational processes is crucial. Any changes in processes and operations will result in changes in data and vice versa. For example, if the Credit Approval department lowers the acceptance rate from 100% to 50%, sales might drop by 30-50%. However, if the analysis shows no change, there might be errors in the analysis or the data might be incorrect. This is one way to check and evaluate your analysis. A good analyst can demonstrate, measure, and reflect all these changes through data.
Do you have any tips for advancing in the Data Analytics field that you can share?
Some people approach their work with a "get it done" mentality, only completing assigned tasks. However, this mindset makes it challenging to advance in one's career. Each task can be completed at different levels; you might finish it at a 5 out of 10, but if you invest more time and effort to reach an 8 or 9, your efforts will be recognized.
Additionally, in the workplace, you'll often encounter two types of work: the work you enjoy and the work the company needs. Most people invest more effort in work they enjoy, but this might not align with the company's priorities or bring much value to the company. It's essential to consider the importance of different tasks and allocate resources appropriately, as this will help you shine and have your efforts recognized.
What makes working in data analysis at Home Credit interesting, and what are your thoughts on the working environment there?
The data analysis mindset at Home is quite strong, with a focus on data and analysis, and decisions are data-driven. This makes it a good environment for those passionate about numbers and data.
Home is also a great place to learn and improve your skills. You can participate in training programs like Business School, Udemy, Skill for Future, and learn directly from colleagues and superiors. The culture of support and sharing is highly valued, and you can easily approach anyone to learn about their expertise and experiences. If you're looking for a company to start a career in data analysis, Home is one of the top choices.
Do you have any advice for those pursuing a career in Data Analytics to help them excel in this field?
With the current demand for data analytics, it's essential to continually learn and improve the skills mentioned above. Additionally, maintain a strong passion for technology and perseverance, you will be successful in the near future.
