Accelerating Data Governance and Offering Self-service with Atlan
The Active Metadata Pioneers series features Atlan customers who have recently completed a thorough evaluation of the Active Metadata Management market. Paying forward what you’ve learned to the next data leader is the true spirit of the Atlan community! So they’re here to share their hard-earned perspective on an evolving market, what makes up their modern data stack, innovative use cases for metadata, and more.
In this installment of the series, we meet Gabrielle Tyll, Senior Vice President, Director of Business Initiatives at SouthState Bank, a tenured employee of the bank who shares their two-year journey toward building a modern data stack and function, their goals for Data Governance, and why they chose Atlan as a means of driving data ownership and self-service.
This interview has been edited for brevity and clarity.
Could you tell us a bit about yourself, your background, and what drew you to Data & Analytics?
I started my career with SouthState a little over 16 years ago and I have held a variety of roles across different areas of the Bank, including the Consumer Bank, Operations, Risk Management and Program Management. Several years ago, I was provided the opportunity to develop and implement a data governance program for the Bank. As someone who is a problem solver and loves a good challenge, I excitedly got to work. Fast forward to the present day, the Bank has an enterprise data program we refer to as our Data Intelligence Program, powered by a hybrid team and a modern data technology stack.
Would you mind describing SouthState Bank, and how your data team supports the organization?
SouthState has about $44 billion in assets, 250+ locations, and provides consumer, commercial, mortgage and wealth management solutions to more than one million customers throughout Florida, Alabama, Georgia, the Carolinas, and Virginia. SouthState also serves clients coast to coast through its correspondent banking division.
As you can imagine, with the volume of customers and breadth of financial services provided by the Bank, comes a variety of data needs across the Bank. The goal of the Data Intelligence Program is to create a centralized place that simplifies and streamlines our team members’ interaction with data. We found data was not always easily accessible and posed challenges when someone needed to aggregate various data sources to produce an outcome. We knew getting our critical data sources centralized and aggregated within the Data Intelligence environment would allow team members to focus more on providing remarkable experiences for our customers and other team members, and less time on joins and merges.
Over the past two years, we’ve continued to onboard lines of business into the Data Intelligence environment, and our hope is that one day we will have reached self-service capabilities, where team members can easily search and retrieve the data they need independent of our team.
Could you describe your data stack, and how it came together?
At the onset of the Data Intelligence Program, we knew we had to invest in a data technology stack that was not only sustainable at our current size, but scalable for future growth. Speed to market was another driving force, and we intentionally selected a stack that would eliminate inefficiencies for our data engineers.
Based on our needs, we evaluated and ultimately adopted a cloud-based data stack which hit the mark on our needs and beyond. Modern stacks typically operate on a consumption-based pricing model, so storage and other prohibitive costs associated with it were no longer an issue. We could pay for what we used, and our technology would grow with us. Another benefit of our stack is that it is front-end agnostic, so we can adapt to the needs of our business and support whatever BI tool they choose to use.
What prompted your search for an Active Metadata Management platform? What were you trying to solve?
We knew in order to succeed in operationalizing data governance, we needed to have a platform that not only provided our team with centralized insights into our data environment, but also a user-friendly tool that supports the activities of our data owners and data stewards. Thinking forward on our journey to self-service, we also wanted to find a platform that would enable a unified understanding of data and easily connect team members across the Bank with the trusted data they need.
Why was Atlan a good fit? Did anything stand out during your evaluation process?
Starting an evaluation of any platform, vendor or tool can be overwhelming, as there are so many options out there. For our team, partnership was top of mind. We needed to find a partner willing to embark on this journey with us, not just sell us a tool. The Atlan team we worked with during our evaluation really went above and beyond to ensure we had all the information needed to make an informed decision. They were very responsive to our questions, and they were able to effectively demonstrate their platform.
From a technical perspective, there were a lot of features already in place or soon to come that made Atlan stand out from others being evaluated. They integrated with our entire stack through native connectors, which makes initial configuration and ongoing administration much simpler. Bi-directional tagging was also a unique feature we did not see in other offerings. The impact analysis feature was also a major benefit, particularly for our data engineers.
Atlan’s interface was very easy to navigate and has proved to be very intuitive even from an administration perspective. The user-friendly interface coupled with the experience of Atlan Anywhere will certainly help our team drive user adoption over time.
What do you intend on creating with Atlan? Do you have an idea of what use cases you’ll build, and the value you’ll drive?
Since partnering with Atlan, there have already been quite a few use cases arise that we look forward to kicking off. Getting our data engineers using Atlan is one of our initial areas of focus, as they are living in this space on a daily basis, and the benefits of Atlan could certainly help them be more effective in their roles. We also intend to leverage Atlan to help establish and manage the needed governance aspects for our Data Communities from glossaries and classifications to CDE identification and lineage.
Shortly after partnering with Atlan, our team discovered a line of business was actively searching for a data catalog for one of our SaaS applications, and because of Atlan’s modern approach, we were able to easily establish a connector and prevent the onboarding of a tool that would ultimately lead to a data silo. This specific use case is one of many examples of the value our team hopes to drive with Atlan – breaking down data silos and creating a community for our team members to engage with one another about data and promoting confidence and trust in the data they use.
Did we miss anything?
For anyone tasked with data governance, having a tool that is easy to use and can get people onboard, if not excited, about their role in support of data governance is definitely a win. And so far for us, Atlan is proving to be a tool that will do just that and more!
Photo by Robert Bye on Unsplash
