James Serra
Data Platform Architecture Lead
Data lakehouse, data mesh, and data fabric (the alphabet soup of data architectures)
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session, James covers all of them in detail and compares the pros and cons of each from his perspective as a seasoned Data Platform Architecture Lead at EY.
Each may sound great in theory, but he'll dig into the concerns you need to be aware of before taking the plunge. James will also include use cases so you can see what approach will work best for your big data needs.
What is Data Agility Day?
Simply put, Data Agility Day is a day to examine ways to improve value extraction from data.
Many companies still struggle with delivering data projects on time, at scale, and with useful results.
Our mission is the persistent evolution of agile data methods, strategies, and team enablement.
Sessions will cover how individuals and teams at data-savvy organizations are achieving the agility that enables decisions to be made faster and create competitive advantages.
What is data agility?
Data agility is the ability to shorten the distance between data and the decision-making that drives action and empowers businesses to be insight-driven.
As the needs for insights grow, data teams are looking to increase their data management workflows and effectiveness - in essence, run data agile organizations.
On October 21st, we'll bring together data experts (engineers, developers, scientists, architects, and analysts) from leading companies to lead in-depth conversations, case studies, and strategies on exactly how to achieve true data agility.
Who attends Data Agility Day?
Data engineers, data developers, data architects, and data scientists as well as BI teams, marketing analytics professionals, innovation-focused executives, and other data science practitioners and leadership.
Join us for sessions surrounding:
- Data transformation
- Data orchestration
- Data visualization
- Data observability
- Data governance
- Data management
- Data ingestion