Scaling up analytics embracing cloud data management
This international automotive company needed to combine 35+ constituent North American companies into a single structure, forcing them to transform their data warehousing and analytics architecture across the business. As a result of the consolidation, the business tasked its IT department with creating a semantic layer that supported high performance analytics that could be leveraged by all business analyst teams.
Prior to the project’s implementation, analysts would often need to wait weeks for manual data engineering to take place. This type of delay hindered their ability to provide actionable insights on key business questions. The automotive company’s backend infrastructure was partly to blame for the slow query response time, as data was siloed across thousands of individual data marts.
Given the scale of this company and the number of users accessing analytics and business insights, they needed a solution to modernize their data architecture with zero disruption to their business users.
Fortunately, the company had already invested in AtScale, which enabled them to make a seamless transition to the cloud with no end-user interruptions.
Enabling The Move to The Cloud
With AtScale’s semantic layer underpinning their efforts, this automotive company’s IT department migrated data from a variety of legacy tools to an Amazon Redshift data warehouse. Once their data was in the warehouse, they could leverage AtScale to enable multidimensional modeling of their data, allowing them to connect their Redshift data warehouse on the back end with data visualization tools like Tableau and Power BI on the front end.
With AtScale, Toyota was able to scale its analytics program to support thousands of users using a range of BI tools. This eliminated the friction associated with moving thousands of SQL queries into a single data warehouse, enabling better user access to data. This also made improved governance possible, keeping data more secure as well as ensuring that various definitions were uniform and accurate across the company. Moreover, their use of AtScale ensured that Tableau and Power BI did not overconsume available cloud resources due to simultaneous requests for full-table scans.
Better data access with millions of dollars saved
With AtScale acting as a single semantic layer between the company’s data warehouse and its BI tools, business analysts are able to glean insight from their queries within seconds, with no need to wait for data engineering teams to get involved with every interaction. Additionally, AtScale has allowed the automotive company’s users of Tableau and Power BI to utilize their preferred tool.
AtScale has enabled the company to consolidate disparate functions and democratize access to data. They are now more competitive than ever, with both technical and business users able to to make decisions based on dynamic analytics.
By empowering Toyota to move from an on-premises data warehouse onto Redshift, AtScale helped them accelerate time to insight by 21x. This delivered a 60% improvement on ROI through reducing infrastructure costs and accelerating analytical performance––all while doubling the number of users who have access to data.
For companies like Toyota that have large volumes of data, AtScale forms a strategic component of their overall analytics technology stack. AtScale helps drive data infrastructure cost savings and deliver critical business data to users faster than ever.