Real-time Analytics
Aviv needed to replace fragmented legacy data stacks across seven brands and three countries so it could get groupwide visibility faster and provide governed data that AI agents could use for instant, contextual business insights.
Reported impact
Aviv unified 25 years of legacy data in six months, gives leaders companywide visibility across seven brands and three countries, reduced maintenance staffing from 15 FTEs to two people, and cut common analytics requests from 4–6 hours or a full day to roughly 15–20 seconds and near-instant delivery.
Aviv rebuilt its data estate on Snowflake AI Data Cloud to consolidate 25 years of disconnected infrastructure spanning seven brands and three countries. Data from legacy Microsoft SQL Server environments, Google BigQuery, Salesforce, clickstream sources, and other brand-specific stacks is unified into a governed single source of truth that is clean and granular enough to support AI and machine learning at scale. On top of that foundation, Aviv built AI agents on Snowflake CoCo so business users can explore performance, customer, and classifieds data in natural language through Snowflake CoWork embedded in Slack. The managed Snowflake platform removes much of the pipeline and maintenance burden while serving near-instant answers instead of days-long reporting cycles, so leaders can retrieve contextualized insights, understand why results changed, and redirect engineering effort from infrastructure firefighting to innovation.
Legacy Microsoft SQL Server estates, Google BigQuery, Salesforce, and other brand data are consolidated into Snowflake AI Data Cloud, where governed datasets become the foundation for AI and machine learning. Snowflake CoCo agents query that data, and Snowflake CoWork delivers contextual answers to business users through a Slack interface instead of analyst-built reports.
For each of these examples, Aviv has built an AI agent on Snowflake CoCo that allows users to explore data in natural language through Snowflake CoWork embedded in a Slack interface.
However, with seven different brands operating in different countries, Aviv’s data was spread across numerous stacks built on a range of technologies, from 2002 Microsoft SQL servers to Google BigQuery.
Now, activities that would normally take a data analyst 4–6 hours take only 15–20 seconds.
Where its previous infrastructure required 15 FTEs just to build pipelines, maintain systems and fight fires, Snowflake is now managed by just two people who also have the time to perform various other roles.
With the assistance of Snowflake’s Data Superheroes, a cohort of expert users and community leaders on hand to provide key advice, it took only six months to unify 25 years of disconnected infrastructure.
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