AtScale Case Studies AtScale Helps Toyota Modernize Analytics

Edit This Case Study Record

	AtScale Helps Toyota Modernize Analytics AtScale

AtScale Helps Toyota Modernize Analytics

AtScale

Technology Category	Analytics & Modeling - Real Time Analytics Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries	Automotive
Applicable Functions	Business Operation Discrete Manufacturing
Use Cases	Factory Operations Visibility & Intelligence Predictive Maintenance
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	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. Read More
About Customer	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. Read More
Solution	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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Infrastructure as a Service (IaaS) - Cloud Computing

Applicable Industries

Automotive

Applicable Functions

Business Operation

Discrete Manufacturing

Use Cases

Factory Operations Visibility & Intelligence

Predictive Maintenance

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

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.

About Customer

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.

Solution

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.

Impact #1	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.
Impact #2	AtScale has allowed the automotive company’s users of Tableau and PowerBI to utilize their preferred tool.
Impact #3	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.

Impact #1

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.

Impact #2

AtScale has allowed the automotive company’s users of Tableau and PowerBI to utilize their preferred tool.

Impact #3

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.

Benefit #1	AtScale helped Toyota accelerate time to insight by 21x.
Benefit #2	Delivered a 60% improvement on ROI through reducing infrastructure costs and accelerating analytical performance.
Benefit #3	Doubled the number of users who have access to data.

Benefit #1

AtScale helped Toyota accelerate time to insight by 21x.

Benefit #2

Delivered a 60% improvement on ROI through reducing infrastructure costs and accelerating analytical performance.

Benefit #3

Doubled the number of users who have access to data.

Download PDF Version

Overview

AtScale Helps Toyota Modernize Analytics

Operational Impact

Quantitative Benefit