Data In Full Bloom (Pun Intended)

It is widely believed that 90% of all data we encounter today was generated in the last two years.

This expansive data landscape encompasses a wide array of sources, ranging from traditional ones like news outlets and research institutions to newer sources such as social media interactions and the content itself. This vast collection of data helps create a rich picture of the world we live in today and demonstrates our efforts to encapsulate and understand it. There has been no other time in history when such a vast amount of information has even existed, let alone been this easily accessible by humans.

I recently came face to face with this reality during my research for a consulting project last month when I used Bloomberg and Refinitiv databases. Coming from a non-finance background, I had no prior exposure to these tools and was unaware of the wealth of data they contained. As I delved into these databases, I was struck by their expansive coverage and the precision of their filtering capabilities. Additionally, the sophisticated research and analysis tools available left me amazed at the wealth of information accessible with just a few clicks. However, friends well-versed in data analytics have informed me that even this minimal effort will soon be replaced by generative AI.

The pace of progress in the field of information technology is truly astonishing. When I compare

these tools to the manual databases I used to create and manage for the Federal Board of Revenue in Pakistan, I feel like I've been living in the dark while others bask in the glow of a fancy ring light and front-facing Zoom-enabled camera. Now, having gained competence in using these databases, I realize that their applications are boundless and can significantly influence how business is conducted in both the private and public sectors in the future.

I've also observed how different databases categorize information, and learning to use them for cross-verification was not as straightforward as we initially thought. We encountered unexpected disparities when engaging in comparative analysis, but through collaboration with the team and tapping into the expertise of other members of the Columbia community, we managed to overcome these challenges.

This research experience has also heightened my appreciation for the importance of good user interface (UI) and user experience (UX) design in front-end systems. I found the Bloomberg Terminal to be much more user-friendly than Refinitiv. However, the latter offered more advanced data tools, even for a beginner like me, allowing for more precise results. I never anticipated that I'd acquire these skills and have such an asset in my toolkit.

These enhancements to my skill set, practical experience, and knowledge in a field like ESG reporting is already proving beneficial as I set up coffee chats and reach out to people for networking. I can also see how they will be applicable in future roles after completing my studies at SIPA, which is reassuring as a second-year graduate student navigating a challenging job market. I'm eager to see what the final product we deliver to the client will look like and how they will use it in this ever-expanding world of data.