Curating a Comprehensive View of Customer Data in Atlan
The Active Metadata Pioneers series features Atlan customers who have 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 Nevenka Perisic, Data Architect at Optimizely, a global leader in digital experience that helps more than 10,000 businesses improve customer lifetime value, increase revenue, and grow their brands through their flagship platform, Optimizely One. Nevenka shares how Optimizely’s Data Services team transitioned away from maintaining siloed data after multiple mergers, into using Atlan as a holistic solution for managing data.
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 work as a Senior Data Architect at Optimizely, joining over a year ago. My objective is to bring data, and understanding of it, closer to customers, helping them see its value to the business.
While studying science at university, various projects exposed me to databases. This experience enabled me to develop essential skills, as one opportunity led to another.
My training proved invaluable, as it helped me stay focused and structured in understanding data and appreciating the real information it provides, distinguishing between raw data and the value that can be derived from it.
Optimizely is a digital experience platform provider that aims to be a one-stop shop for marketers. Our flagship product, Optimizely One, is the industry’s first operating system for marketers and allows teams to connect each step of the marketing lifecycle through a single, unified workflow, so they can better promote their products digitally. Many companies lack the skills, resources, or time to handle this, and that’s where Optimizely comes in. We take on that burden, offering customized solutions for each customer. Many major brands are already Optimizely customers, working closely with us to deliver value.
When I joined Optimizely, the company was undergoing significant changes, including multiple mergers, which created the challenge of bridging silos and identifying where data was stored. I became part of Data Services, a newly established central function responsible for managing analytics and supporting our common data platform in Snowflake. The team was small, but growing as we recruited more members. Now, we are focused on building a modern data stack to connect teams across Optimizely that had traditionally worked in isolation.
Could you describe Optimizely’s journey with Atlan, so far?
I was responsible for implementing the platform, coordinating with Atlan and the data engineering team to bring the Optimizely instance online. I designed the initial implementation plan with Atlan’s help, outlining the stages, user stories, and short- and long-term targets.
To engage the business, we needed something tangible, so we began integrating Atlan with key data sources. We quickly integrated all our major systems, earning recognition from Atlan as one of their fastest customers to complete this process. Native connectors, like Salesforce, allowed us to fully leverage Atlan’s features, and we’re working with Atlan to integrate systems without native connectors to extend access to features like data lineage, consumption, and other metrics.
What are the use cases you’ve built with Atlan? Who’s getting value from it?
We integrated data sources, glossaries, and dictionaries, and worked with power users who quickly saw value since they were already familiar with the software. Now, we’re promoting this value to business users who still rely heavily on spreadsheets, a process we’re actively rolling out. I handled the technical integration, making all data sources available, provided training so users could explore the data and identify useful features, and helped guide Atlan’s development to maximize value from the catalog.
I see Atlan not just as a data catalog, but as a collection of data artifacts. Our vision is to connect data flows, processes, and data quality on top of the lineage provided by Atlan. We aim to offer a holistic solution for users who come to Atlan and say something like, “I need this for a specific project. Can I pull all these data artifacts together with attributes linked to the right terms, glossaries, and data flows?” That’s our goal.
We’re still building it, as it’s a huge task, but we’ve made progress, and users are starting to recognize its value and actively engage with us.
What are you looking forward to achieving with Atlan in the future?
We want to ensure that everything our team needs to understand our customers is made available in Atlan as our data estate matures.
We’re not there yet, so we’re limiting exposure for now because there’s still a lot of work to be done. We’ve made a lot of progress in Atlan, but we need to carefully consider how to expose meaningful data without creating an unusable swamp. Our intention is to provide reliable and credible information within Atlan.
Photo by Davide Baraldi on Unsplash
