AtScale > 实例探究 > AtScale Helps Toyota Modernize Analytics

AtScale Helps Toyota Modernize Analytics

公司规模

Large Corporate

地区

America

国家

United States

产品

AtScale
Amazon Redshift
Tableau
Power BI

技术栈

Cloud Data Management
Data Warehousing
Business Intelligence Tools

实施规模

Enterprise-wide Deployment

影响指标

Cost Savings
Productivity Improvements

技术

分析与建模 - 实时分析
基础设施即服务 (IaaS) - 云计算

适用行业

汽车

适用功能

商业运营
离散制造

用例

工厂可见化与智能化
预测性维护

服务

云规划/设计/实施服务
数据科学服务

关于客户

Toyota is an international automotive company that was looking to consolidate 35+ constituent North American companies into a single structure. This required a transformation of their data warehousing and analytics architecture across the business. The company's IT department was tasked 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, hindering their ability to provide actionable insights on key business questions. The company's backend infrastructure was partly to blame for the slow query response time, as data was siloed across thousands of individual data marts.

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挑战

Toyota, an international automotive company, was faced with the challenge of consolidating 35+ constituent North American companies into a single structure. This required a transformation of their data warehousing and analytics architecture across the business. The IT department was tasked 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 delay hindered their ability to provide actionable insights on key business questions. The company's backend infrastructure was partly to blame for the slow query response time, as data was siloed across thousands of individual data marts.

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解决方案

With AtScale’s semantic layer underpinning their efforts, Toyota'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 PowerBI on the front end. With AtScale, Toyota was able to scale its analytics program to support thousands of user 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.

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运营影响

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.
AtScale has allowed the automotive company’s users of Tableau and PowerBI 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.

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数量效益

AtScale helped Toyota accelerate time to insight by 21x.
Delivered a 60% improvement on ROI through reducing infrastructure costs and accelerating analytical performance.
Doubled the number of users who have access to data.

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