Holiday Season Prelude
🎄 Whereever you are, Merry Christmas and Happy Holidays! 🎄 If you are online, taking a phone break from the rest of your holiday celebrations, hopefully you will enjoy hearing me talking about enterprise data and value for a few minutes. 😃
Hi, to all the tech geniuses and business tycoons in my network, Merry Christmas! On this special day, most of us are in our homes, taking a break from the intense work of managing enterprise data and building AI.
For me, I’m looking back, one of the things I started doing this year was to sit down with data leaders across different industries and roles, having private 1-on-1 conversations to learn about what they are working on, what they care about, and what keeps them up at night. In total, I had 43 conversations, exchanged thoughts with some of the most brilliant and ambitious executives I’ve ever met, some of them have become friends with me and turned into long-lasting relationships. I want to share the wisdom they passed on to me, what I’ve learned on the challenges data leaders have worked on and will continue to work on in 2025. More importantly, we will discuss some innovative ways to solve them. Among all the thought exchanges, some of the things that really caught my attention were:
When it comes to running data projects and teams, how do you keep your cost of communication low? One thing I learned this year is how much effort data leaders are investing to strive to achieve a common understanding on data & AI within their inner circle. And most of them are looking into reducing this effort, and more importantly, communicate more effectively.
So that was the first thing that caught my attention, another thing is how to quantify data’s impact? Many speak about incubating the culture of treating data as an asset, as a product, a source of revenue. I think we are at a point in time when this should not be just talking points anymore, to truly become an asset, a source of revenue, data leaders need to quantify the value data generates, so how do you put data onto your organization’s balance sheet?
After years of booming & hype, the industry of data and AI has become quite a saturated space, there are too many data tools for people to use to build their architecture. From data ingestion, storage, data transformation & cleaning, to visualization and analytics to feature engineering and MLOps. We had so many tools that people started building specific tech for integration and orchestration, and now we have too many orchestration platforms. So in the age of a million data tools, how do you know which ones are the right tools for your architecture? Are there tools that are truly better than all its peers at all time? Or do you need to understand your own needs on data better and pick the best fitting tools for your situation?
In the new year, I want to continue to challenge myself, I will something I’ve never done before, which is putting myself in front of a camera. I will be posting short videos covering specific topics I’ve mentioned earlier, I’m aiming to do 5-10 of these videos after Christmas, the specific timeline would be really depending on my rookie editing skills, so please give me some extra patience XD.
I’m also collaborating with Gokula, to bring a webinar together on 17th of Jan. If you are interested to hear our thoughts on how to utilize enterprise data more effectively, please sign up for our webinar, I will post the link below in the comment.
