As data costs balloon every quarter, achieving a high return on data investment is critical. Data volumes grow, costs soar, and many organizations struggle with fragmented systems and operational inefficiencies.
In this on-demand webinar, you’ll hear how Artlist’s journey began with a small data team tackling basic marketing analytics, but as the company grew, so did the complexity of its data environment. Scaling to meet demand introduced intricate pipelines and dependencies, creating bottlenecks that slowed insights and increased reliance on engineers. By adopting Seemore Data, Artlist transformed its workflows—empowering analysts with self-service capabilities, simplifying pipeline management, and uncovering major cost savings. The result? A scalable, efficient data ecosystem that supports rapid growth without compromising on agility or innovation.
Hear from a top-notch panel of experts as they share their insights and actionable strategies:
- Guy Biecher: CTO and Co-Founder of Seemore Data, with 15 years of expertise in Snowflake and data efficiency.
- Hannan Kravitz: Data Engineering Team Lead at Artlist, driving growth and tackling data bottlenecks.
- Ariel Pohoryles: Head of Product Marketing at Rivery, bridging technical challenges with business solutions.
The Data Challenges of A Speedy Scale-up
Rapid growth and increasing data complexity can put immense strain on data teams. For Artlist, this meant navigating tight deadlines, managing complex pipelines, and dealing with mounting Snowflake costs—all while scaling operations to support their expanding user base.
According to Hannan Kravitz, Data Engineering Team Lead at Artlist, the challenges were clear:
- Data Engineering Bottlenecks: “Rapid growth meant more and more pipelines were being added and more models were built, so we needed some sort of basic understanding of what was going on.”
- Complex Pipelines and Calculations: The team struggled to manage growing dependencies between models and lacked visibility into how data was transformed across pipelines.
- Heavy Dependency on Engineering: Non-technical users frequently relied on engineers to understand data constructions, slowing down time-to-insight and delaying critical decisions.
These hurdles not only slowed operations but also led to inefficiencies that increased costs and diverted valuable resources from innovation. Artlist needed a way to simplify workflows, enhance transparency, and gain control over their data environment.
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Webinar Overview: Turning Challenges into Opportunities
In this on-demand webinar, the panel dives deep into the tools, strategies, and real-world experiences that helped Artlist tackle their toughest data challenges as a super scaler. From cutting costs to growing operations, this session provides a roadmap for data teams aiming to optimize their data stack without sacrificing quality or speed.
Key topics include:
- End-to-End Visibility: Explore how clear lineage and real-time insights can streamline workflows and reduce operational bottlenecks.
- Cutting Costs with Data Observability: Learn how actionable insights from Seemore Data helped identify and eliminate inefficiencies in Snowflake pipelines.
- Scaling Without Losing Control: Discover strategies for managing complex pipelines and dependencies as your data grows.
- Empowering Analysts and Engineers Alike: See how Artlist enabled non-technical users to access and understand data independently, freeing up engineering resources.
This webinar dives into the practical steps Artlist took to optimize their data operations. See how they used Seemore Data to map out end-to-end pipeline lineage, identify redundant data processes, and adjust pipeline refresh frequencies to match actual usage. Learn how these strategies empowered their analysts to trace metrics independently and reduced engineering bottlenecks, offering real, actionable insights for streamlining your own data workflows.
Snapshot: The Artlist Case Study
Artlist, a leading creative technology company, turned to Seemore Data for complete data observability, streamlined pipelines, and reduced Snowflake costs. With a 30‑minute onboarding, the team quickly uncovered cost-saving opportunities—cutting expenses while enhancing workflow efficiency.
Within just one month, Artlist optimized three resource‑intensive pipelines, removed unnecessary processes, and empowered both technical and non‑technical users to understand data flows independently. This case study reveals how actionable insights and comprehensive lineage visibility drove a 30% cost reduction and accelerated time‑to‑insight, setting the stage for sustained efficiency as the company continues to scale.
