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Leading furniture retailer

This retailer is one of the world’s leading residential furniture producers, marketing furniture for every room of the home. The corporation’s branded distribution network includes approximately 350 stand-alone furniture gallery stores and more than 550 independent studio locations, in addition to in-store gallery programs.



A leading retailer needed to democratize and centralize their data to remedy manual dashboard creation, siloed data and disjointed tools that lacked governance.


Ollion deployed the Snowflake Data Cloud, along with data transformation pipelines, to enable master data management, machine learning capabilities, continuous integration/continuous delivery and DataOps to internal teams at the retailer. With a modern data solution, data teams can quickly, efficiently, and effectively serve downstream use cases for meaningful business impacts.


We empowered this leading furniture retailer's data teams with a unified platform for data exploration and analysis.

The challenge

The retailer struggled to integrate their data due to silos spread across different source systems and a newly acquired company. Data teams had to dedicate most of their time toward creating dashboards for business users that would only access single data sources. In addition, each data mart was provisioned for a specific business intelligence (BI) tool, such as Domo and Pentaho. These inefficient processes were compounded by unclear data governance and undefined teams that made it difficult for analysts to collaborate on and share data.

Data teams lacked the centralized platform and tools required to fulfill use cases for demand forecasting, eCommerce integration and master data management (MDM). Without sufficient internal DataOps expertise, the retailer required help to design, deploy and implement the pipelines and platform necessary for data ingestion, curation and consumption at scale.

The solution

After assessing the retailer’s existing infrastructure against their goals, Ollion data management consultants focused on creating a solution that not only provided high-quality data sets for immediate use cases — demand forecasting, machine learning (ML) eCommerce integration and MDM — but also established a reusable, scalable data platform for future strategic initiatives. To achieve this, Ollion leveraged a variety of modern tools based on cost, ease of use and ability to satisfy workflow requirements.

The retailer needed a single tool for ingesting data to a Snowflake “raw” layer for staging. The Ollion development team suggested HVR, a Fivetran company, to incrementally stream data from the enterprise resource planning (ERP) solution, customer relationship management (CRM) solution and pre-defined Secure File Transfer Protocol (SFTP) flat files based on change logs. With HVR managing the majority of the ingestion work, users are able to train on one tool and monitor the active data flows using a single application.

After staging the data in Snowflake, our engineering team designed a “business” layer to gather all relevant information for a given domain on a per-source basis. For example, to collect customer attributes, we created multiple “CUSTOMER_SOURCE_N” tables to stage information before mastering the domain at an enterprise level using Ataccama. Using the mastered data, we integrated each data thread into a single source of truth designed as a star-schema data warehouse, which provides governed, secure and consistent data sets to downstream users. To deploy transformation SQL scripts, job orchestration within Snowflake and CI/CD data operations, Ollion leveraged dbt, integrated with GitHub.

Finally, we strategically exposed the data sets to end users in a variety of ways, including Snowflake external shares, a Domo connector for BI, macro unloads to S3 buckets (and later SFTP folders) and Java-based APIs for application development.

The outcome

With a fully developed data pipeline and unified data platform, the retailer is able to take advantage of their data. Not only are data teams empowered to fulfill use cases, but they are doing it on a regular basis. Our client has developed a cadence for engineering and scaling based on new use cases, formalized data governance, and CI/CD best practices for the data ecosystem and DataOps. Now, teams participate in bi-monthly agile sprints for developing data features in the Snowflake data lake house that serve downstream business users and their needs.

The data lake house, enabled by the Snowflake deployment, gives the organization a raw and curated view of important business domains, including sales, supply chain and customer information. With the ability to ingest, transform and consume enterprise-level data in a centralized and digestible location, users can access, explore, share and collaborate across teams to make smarter business decisions.

One of those use cases was to provide extracts for training and productionalizing o9 ML models for demand forecasting to better track inventory and drive manufacturing. The second use case was the deployment of an API for application integration for the eCommerce website. The API integration enables customers to view the status of their orders for improved customer service and experience. A third use case fostered an MDM feedback loop or domains that were mastered with Ataccama. This created one “golden” record per customer or other domain that was brought back into the data warehouse.

In total, the engagement between Ollion and the retailer empowered their data team to be functional. Moving forward, they will continue to build on their capacity to generate and deliver insights within their unified platform. Ultimately, through collaboration, data exploration, sharing and analysis, current and future engineering can grow and scale with the interests of business users and the retailer’s overall goals.

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