Pulling data from different sources fast is becoming prudent for critical business decisions, because it accelerates analysis and operational efficiency.
To enable customers to express themselves through fashion, Saks.com LLC is going a notch higher by modernizing its databases and pipelines so that near real-time insights can be gained, according to Veronika Durgin (pictured, right), head of data at Saks.
“Saks is the premier luxury e-commerce platform,” Durgin stated. “Fivetran helps us ingest data from all those data sources into Snowflake in near real time.”
As an example, within a matter of a few weeks, Saks was able to get data from more than a dozen different data sources into Snowflake in near real time.
“Some of those data sources were not available to our users in the past because they required a lot of engineering effort to actually build those data pipelines to manage and maintain them,” Durgin added.
Durgin and George Fraser (pictured, left), chief executive officer of Fivetran Inc., spoke with theCUBE industry analysts Dave Vellante and Lisa Martin at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Saks was able to revolutionize its data system for near real-time insights and how Fivetran and Snowflake Inc. came into play. (* Disclosure below.)
Taking the data integration complexities away through a plug-and-play approach
Since data integration is not a walk in the park, Fraser believes it requires high expertise, and Fivetran fills the void by tackling challenges like volume, latency and incidental complexity.
“There are really three things that make data integration hard,” he explained. “One is volume, and that’s the one that people tend to talk about, just the size of data. It’s also latency; how fresh is the data in the locus of consolidation? The last challenge, which people tend not to talk about — it’s the dark secret of our industry — is just incidental complexity. What we bring to the table is mapping out all of these complexities of data sources so that a user just connects a source and destination.”
Fivetran offers a data pipeline strategy that is simple and easy to integrate, according to Durgin.
“You just connect it to whatever source, and within a matter of minutes, you have a pipeline,” she said. “Once data lands in Snowflake, we have data across different sources in one central place. We can do all kinds of different things; we can integrate data and do validations and reconciliations.”
Given that Snowflake is a data cloud, Durgin believes it simplifies things because you can undertake different functions on workloads, such as analysis and reporting.
“We always had to offload those specific analytical reporting functionality or machine learning somewhere else, and Snowflake is excellent for that,” she added.
By accurately replicating data, Fivetran does not take information away from the source systems, according to Fraser.
“Our job is to get the data from here to there,” he noted. “The data is accurately replicated, which means in practice that it is exactly as messed up as it was in the source. No better or worse, but we really will accomplish that task.”
Since Fivetran acts like the consolidator and pipeline, Fraser believes that the company brings data to one place irrespective of where it lives.
“So a considerable amount of the data that we’re all talking about here flows through Fivetran … we’re a data pipeline,” he pointed out. “We bring it all together, and the place that it is consolidated is Snowflake. From there, you can really do anything with it.”
In the quest to modernize its data systems, Saks was looking for a cloud-native approach and partners that would enhance its growth, according to Durgin.
“So my first experience with both Fivetran and Snowflake was like, this is where I want to be, this is the stack and the tooling and the engineering behind it,” she pointed out.
When Saks evaluates tools for a new platform, it looks at things in three dimensions, Durgin added.
“One will be cloud-first. We want to have cloud-native tools, and they have to be modular. But we also don’t want too many tools. So Fivetran certainly checks that,” she stated. “The other thing is that data engineering effort is spent on actually analyzing data, not building pipelines and supporting infrastructure.”
Lastly, Saks looks for partner companies that help it grow.
Since Snowflake offers a simpler framework than Hadoop, Fraser believes data accessibility is enhanced for better decision-making.
“Great analysts are great navigators of organizations amongst other things, and one of the best things that have happened as part of this evolution from technology like Hadoop to Snowflake is the new stack is a lot simpler,” he pointed out. “There’s a lot less technical knowledge that you need; you still need technical knowledge, but not nearly what you used to, and that has made it accessible to more people.”
Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Snowflake Summit event:
(* Disclosure: TheCUBE is a paid media partner for the Snowflake Summit event. Neither Snowflake, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)