A featured contribution from Leadership Perspectives, a curated forum for enterprise technology leaders, nominated by our subscribers and vetted by the CIOApplications Editorial Board.
Camping World
Turning Data into Power and Possibility
I work closely with the business to ensure that needs are met from day-to-day analysis, reporting, tagging, data science, and data governance and product roadmaps. We build algorithmic models for real time integration for various needs, forecasting, and segmentation. The team plays with Agentic AI to help and AI w/RPA to drive various processes and explore operational efficiencies. Overall, it’s a lot of fun, as we get to see the full consumer lifecycle of our enthusiast consumers who love to travel and see the world!
Like many older companies, there are a lot of legacy infrastructures being integrated with cutting edge capabilities, and my team has to live in both. This presents infrastructure, security, governance, and agility problems. The team overcomes this by effectively building relationships, understanding the needs of the business, the limits of the technologies in play, and finding where we can apply our skills and ingenuity to stretch both further without driving high costs or maintenance workloads on our peers. My team will consistently work to document process, code, and requirements, stay connected with the various teams across the tech stacks, and ensure intimate familiarity with their creations so that when numbers look off, or performance is beyond a threshold, they’re ready to jump in and find a solution.
I’ve made it an important part of how my team operates to ensure that we’re integrated into the digital development, martech and transactional/ERP systems roadmaps.
Applications are no longer tools of just operational functions, they’re the seedbeds of your customer, employee, and process data, and so, if you don’t plan the soil conditions and plant the right seeds, you will have very little data for harvest and consumption, be it for other downstream applications, better Customer 360 support, or utilization of AI on well governed and purpose-built data structures.
Applications are no longer just operational tools—they’re the seedbeds of your customer, employee, and process data. Without planting the right seeds, there’s little data to harvest for AI and analytics success
Successful companies are the ones who embrace the importance of data, governance and their role in understanding their customers and the employees and processes that connect them. And the most powerful AI capabilities companies want to unlock require their data to not only the context of the customers as they sit today, but how they sat at the time of that last communication, transaction, call center interaction, etc. And so, by making these relationships available in flexible and proper ways, given the use cases and audiences intended, they can unlock tremendous value for their marketers, operators, and customers.
Data architecture wise, graph databases and their related ontologies are incredibly powerful for building effective AI and Data Science applications, as context for the customers’ journeys can be created and trained against very quickly when governed properly. But many of the current BI tools don’t work well with these types of databases, preferring more traditional relational architecture, and so you may need to support both data architecture and storage methods, which require different talent sets to maintain, and ensuring the governance keeps the two in sync as far as how the data ought to be related.
Systems architecture wise, it’s ensuring that there’s always a handshake between systems such that the necessary metadata are exchanged to ensure that an LLM being trained on your dataset and ontology knows how this event in this system’s raw data ties to this event in this other system’s raw data for this customer’s particular outcome.
