[My BI Path | Part-2] Unlocking the World of Business Intelligence: A Guide to a Rewarding Career
Business Intelligence (BI) is a rapidly growing field that plays a crucial role in helping organizations make informed decisions. From the boardroom to the conference room, the mantra is data-driven decision-making — the idea of harnessing powerful computing resources, advanced analytics, and burgeoning data stores to augment human brain power and initiate smarter decisions. First thing first, let’s begin with a definition: Business Intelligence (BI) is a set of practices aimed at transforming raw data into actionable insights for businesses. The primary objective of BI is to provide decision-making support to organizations through data analysis and visualization. BI specialists are responsible for collecting, structuring, and analyzing large amounts of data and turning it into actionable insights that drive business growth.
Choosing to be a Business Intelligence (BI) Specialist
My journey as a Business Intelligence (BI) Specialist began with a belief in the transformative power of data. I was fascinated by the idea of turning raw information into actionable insights that drive business growth. And so, I set out on a mission to become a BI expert and play a critical role in shaping business decisions. At first, my resources were limited. I had to rely on my own initiative and determination to learn and grow in this field. I started by educating myself on the basics of data analysis and business acumen, reading articles and books and taking online courses. Over time, I also developed adaptability for prioritizing workload and meeting business deadlines, as well as developing and mentoring a diverse team.
As I gained more experience, I had the opportunity to work with a diverse group of backend engineers. This exposure to different perspectives and approaches to data management broadened my knowledge and skills. I learned how to manage large amounts of data and turn it into actionable insights that drive business growth. Throughout my career, I have developed a reputation for producing accurate data analysis and insightful visualizations that can be easily absorbed by colleagues and clients with varying levels of data experience. Today, I am a well-rounded BI Specialist, capable of bridging the gap between data engineers and management executives. I have the technical expertise to manage large data sets and the business acumen to separate high-value data from low-value data. By combining these skills, I am able to provide valuable insights to organizations and help them make informed decisions.
My passion for BI has only grown stronger over the years. I believe that data has the power to transform the way we do business, and I am dedicated to using my skills and expertise to help organizations reach their full potential. I understand the importance of setting standards, sharing knowledge, and ensuring the team remains engaged and skilled in the latest tools. Despite starting with limited resources, I have been able to hone my skills and grow in this field over the years, and I am eager to share my experiences and insights with you. Whether you’re just starting out in BI or are a seasoned professional, I hope my story will inspire you and provide valuable insights into this exciting field.
My Journey as a Business Intelligence (BI) Specialist
When I started my career in data science, I didn’t have many resources available to me. I found a video on YouTube which sparked my interest and led me to discover the plethora of online courses like Udemy, Coursera, and edX. I took these courses to learn the fundamentals of data science: analytical skills, technical skills, and business acumen. I practiced what I learned by working with sample datasets, but I quickly realized that I wasn’t as confident or competent as others perceived me to be. My first end-to-end project turned into a nightmare and I still remember that feeling of being overwhelmed and drained. I doubted my abilities and wished for a mentor to guide me. I had to learn from my mistakes and try not to repeat them. I believe this is a common experience for beginners, but it’s essential to overcome this phase to grow.
Level-1: I needed someone (a senior) to oversee my work and someone to mentor me. Unfortunately, I didn’t find one because I don’t know “how-to and where-to”. (Thus, I founded Yangon Data Science Community to connect with like-minded professionals, but it is a separate topic). So I have to learn from my mistakes. I made a lot of mistakes and try to fix them and learn from them. But I always try not to repeat the same mistakes. I believe everyone starts there. This is how a starter unfolds his/her journey. We cannot skip this phase. We have to overcome this. Read more if you want to move to another level. Learn more. The challenge with implementing end-to-end analytics (or) engineering solutions is that it depends on in-depth situational knowledge that we simply can’t have when they start an assignment or a project. Context and Domain knowledge do matter. And I realize our work is largely a performance. Like skillful actors, they use a combination of “backstage” preparation and “front stage” performance to make the audience (that is, the client) believe the story they want to tell. I would say a good mentor will help you guide you through this difficult time. Let’s call this stage “Level-1”.
Level-2: At the second stage of my journey, I became more skilled in business and analytical skills, but my technical skills were lacking. I am good at analytics but cannot foresee the other (engineering) side. At this point, My managers relied on me for quality outcomes in my specialty areas, and I was sometimes tasked with mentoring juniors in some projects. Becoming reliable and dependable allowed me to execute projects and take on more responsibilities. If you can be reliable and dependable, you can execute projects by any means — collaborating with other teams, you are a senior. Your line manager might give you some stretching projects that require you to lead the project as a PM. And this will demand you to oversee and manage resources, risks, stakeholders, scopes, and more. Don’t panic about it. This is part of the growth process. This is the way to become a mid-level manager. Let’s call this stage “Level-2”.
Level-3: Next-level demands not just technical and analytical skills. It requires a lot more soft skills — conceptual leadership, and human skills along with many successful experiences in implementing end-to-end projects, pipelines, and ecosystems in collaboration with many stakeholders and teams. At this stage, strong business acumen with the ability to manage stakeholders and communication skills are vital. We also need to become a resourceful person when it comes to data. In addition to these, business leaders and stakeholders rely on our insights to craft strategies and execute them. We need to grow as trusted business intelligence advisors and consult data strategies with different stakeholders and business leaders. Social intelligence is critical. This is a mid-level manager role and let’s call this stage “Level-3”. At this stage, results do matter. Impacts do matter. And business values do matter for advancing to the next level.
Level-4: If we are advancing ourselves from mid-level managers to higher roles, we need to see from a bird’s-eye view. And we eventually need to reduce some of our hands-on work. We have to focus more of our energy, time, and commitment on conceptual skills, collaboration, leading a team, and helping our team members grow. At the same time, we also need to deliver fruitful results. We have to deal with different types of challenges. On the system side, you have to co-design the architecture to be future-proof with all the backend teams. You also have to lead, direct and oversee data engineers to implement data ecosystems and data pipelines. More still, you could be able to run a team of analysts to pull insights from the data ecosystem you have designed and help them shine in front of business leaders and decision-makers. You need to manage and coach teams on both ends (engineering and analytics) and guide your team through every changing business environment. Moreover, you could be able to set frameworks on data governance, craft strategies, design roadmaps, and implement standard operating procedures. You should promote data literacy in your organization and set a data culture. Then you are Head of Data / Data Analytics / BI. Let’s denote this stage as “Level-4”.
30-Second Takeaway
- Business Intelligence (BI) is the set of practices aimed at transforming raw data into actionable insights for businesses
- The primary objective of BI is to provide decision-making support through data analysis and visualization. BI specialists are also responsible for collecting, structuring, and analyzing large amounts of data
- Start with self-education and determination. Become a well-rounded BI Specialist with technical and business expertise, capable of providing valuable insights to organizations.
- Continuous learning and mentorship are important for career growth as a BI specialist.
I am writing this article provides information and resources for those looking to pursue a career in business intelligence, even with limited resources. My intention is to empower and inspire those who have limited resources available to them, by sharing my journey as a Business Intelligence (BI) specialist and offering valuable insights and advice on how to kickstart a career in this field. Stay tuned for more of my personal thoughts, insights, perception, and tips on how to navigate the exciting world of data science and business intelligence.
[My BI Path | Part-1] Unlocking the World of Business Intelligence: A Guide to a Rewarding Career
[My BI Path | Part-3] Unlocking the World of Business Intelligence: A Guide to a Rewarding Career
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