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When I talk to customers, they always find value in stories about how our other customers are progressing on their data and analytics initiatives and their journeys toward realizing self-service BI.
This post will do a deep dive into a few customer stories and examples of leveraging AtScale + Tableau to break down silos to become more data-driven.
Toyota’s Data-Driven Cloud Migration with AtScale + Tableau
Leading industrial powerhouses like Toyota understand the importance of empowering teams to use data and analytics independently. As Toyota moved to embrace modern cloud data platforms and consolidate, they teamed with AtScale. Toyota decided to migrate from their legacy data warehouse onto Amazon Redshift with the goal of modernizing their analytics and accelerating their time to insight.
A central challenge to Toyota’s modernization project was that it needed to combine 35+ constituent North American companies into a single structure, forcing them to transform their data warehousing and analytics architecture.
Any business of Toyota’s scale has a considerable analytics footprint, with many users who need access to analytics and business insights. Their modernization effort had to address the shortfalls of Toyota’s current solution with zero disruption to its knowledge workers. Fortunately, the company’s initial investment in AtScale positioned them perfectly to manage a seamless transition for their data into the cloud.
AtScale’s Semantic layer provided a foundation for the entire effort because once their data was in the warehouse, they could leverage multidimensional modeling of all of their source data in one place. From there, they could easily connect their Redshift data warehouse on the back end with their existing visualization tools such as Tableau.
For Toyota, AtScale became the single semantic layer between its new data warehouse and Tableau, allowing their business analysts to glean actionable insights from their queries in real-time, without ever having to go back to their data engineers. By underpinning Toyota’s migration from isolated on-premises data marts onto Redshift, AtScale helped accelerate their time to insight by 21x and deliver a 60% improvement on ROI via reduced infrastructure costs and better analytical performance.
Wayfair’s Journey to Self-Service BI with AtScale + Tableau
Wayfair is a fast-growing company, and they needed their data infrastructure to grow alongside the business. As an eCommerce retailer, Wayfair leverages data for their most critical metrics: Customer interest and the performance of their manufacturers. They also need to parse through large amounts of data to predict their products’ price and quantity. To better serve the company’s data needs, the data infrastructure team decided to modernize their analytics and move to a cloud platform.
One oversized challenge Wayfair faced in their modernization is the hundreds of business analysts doing mission-critical work every day with Microsoft SQL SSAS. Maintaining business continuity was essential, and the data infrastructure team needed a partner that could support their current business operations while enabling the transition to modernized BI.
Wayfair chose AtScale because it helped them support its hundreds of business analysts using the BI tools they were comfortable with, such as Tableau, and maintain their OLAP analytics capability without the costly overhead and data movement found in SSAS solutions.
Wayfair’s embrace of analytics modernization with AtScale accelerated their time to insight with a live connection to all of their cloud data. The company now enjoys a single, unified source of truth shared by hundreds of data modelers and business analysts supporting Wayfair’s online retail business.
Analytics Modernization at Tyson Foods with Atscale + Tableau
In the face of an unprecedented global supply chain crisis, business and technology leaders at Tyson Foods recently shared a vision of delivering self-service BI to its 144,000 employees. This would enable smarter decisions across the company and allow Tyson to respond with agility to the daily changes in market conditions and the supply chain.
The challenge the company faced was breaking down the data silos that had accumulated over time, with fragmented data spread across various legacy platforms and data lakes. They initially turned to a Hadoop-based architecture but immediately found it didn’t have the scalability the company needed.
“That was one of a few reasons why we quickly turned to AtScale,” said Chad Wahlquist, Director Data Strategy and Analytics Technology Platforms at Tyson Foods.
Tyson Foods used AtScale’s semantic layer to connect their siloed data, transforming their fragmented data sources into a single, governed source of truth that could be easily visualized using leading BI tools such as Tableau. AtScale helped Tyson deliver self-service BI capability to 144,000 employees without the need to seek out data engineers every time they wanted to ask a question.
AtScale Works With Leading BI Tools Like Tableau to Help Companies Deliver Self-Service BI.
The common thread in all these stories is that companies are making better decisions by embracing a data-driven culture. But leadership can’t do it alone. AtScale is the perfect fit for companies looking to break down their data silos and create a unified source of truth for their data without asking their knowledge workers to learn new BI tools or business processes. These companies succeeded because they had the right tools and focused on enabling self-service, rather than dependence on IT, across their organizations.