Alteryx Case Studies Deutsche Börse Group's Transformation with IoT: A Data Science Lab Case Study

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	Deutsche Börse Group's Transformation with IoT: A Data Science Lab Case Study Alteryx

Deutsche Börse Group's Transformation with IoT: A Data Science Lab Case Study

Alteryx

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Machine Learning
Applicable Industries	Cement Construction & Infrastructure
Applicable Functions	Quality Assurance
Use Cases	Time Sensitive Networking Visual Quality Detection
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	Deutsche Börse Group, a global financial services company, saw an opportunity to transform the large volumes of stock data, previously considered as 'exhaust' of their trading business, into a significant revenue contributor. The company decided to invest in data science to sell not only raw data but also more advanced content. Despite having invested in on-premise architecture in the past, Deutsche Börse Group realized the need to build its new data science center in the cloud to leverage the cloud's flexibility and scalability. However, the company faced a challenge. Business users required specific transformations to be made to the data before it could be migrated to the cloud, but they did not want to overload the already busy IT team with requests. Furthermore, Deutsche Börse Group wanted to prevent their highly-trained data scientists from spending most of their time on data cleansing and preparation tasks, even after the data migration. Read More
About Customer	Deutsche Börse Group is an international exchange organization and innovative market infrastructure provider. The company offers its customers a wide range of products, services, and technologies that cover the entire value chain of financial markets. Operating globally, Deutsche Börse Group is a key player in the financial services industry, dealing with huge volumes of stock data. The company sought to transform this data into a significant revenue contributor by investing in data science and migrating to a cloud-based data science center. Read More
Solution	Deutsche Börse Group adopted Designer Cloud to securely transform and move data from its on-premise environment to a cloud platform without burdening the IT team. Designer Cloud enabled business users to see exactly how data would be transformed before moving it to the cloud. It also provided a clear audit trail of where the data originated and how transformations had been applied. The ability to save and reuse transformations allowed business users to accelerate their work with each new batch of data. Moreover, as data scientists leveraged data for machine learning or predictive models, Designer Cloud enabled them to reduce the amount of time spent preparing data. For instance, a project that once required nine months has now been reduced to three weeks with Designer Cloud. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Machine Learning

Applicable Industries

Cement

Construction & Infrastructure

Applicable Functions

Quality Assurance

Use Cases

Time Sensitive Networking

Visual Quality Detection

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

Deutsche Börse Group, a global financial services company, saw an opportunity to transform the large volumes of stock data, previously considered as 'exhaust' of their trading business, into a significant revenue contributor. The company decided to invest in data science to sell not only raw data but also more advanced content. Despite having invested in on-premise architecture in the past, Deutsche Börse Group realized the need to build its new data science center in the cloud to leverage the cloud's flexibility and scalability. However, the company faced a challenge. Business users required specific transformations to be made to the data before it could be migrated to the cloud, but they did not want to overload the already busy IT team with requests. Furthermore, Deutsche Börse Group wanted to prevent their highly-trained data scientists from spending most of their time on data cleansing and preparation tasks, even after the data migration.

About Customer

Deutsche Börse Group is an international exchange organization and innovative market infrastructure provider. The company offers its customers a wide range of products, services, and technologies that cover the entire value chain of financial markets. Operating globally, Deutsche Börse Group is a key player in the financial services industry, dealing with huge volumes of stock data. The company sought to transform this data into a significant revenue contributor by investing in data science and migrating to a cloud-based data science center.

Solution

Deutsche Börse Group adopted Designer Cloud to securely transform and move data from its on-premise environment to a cloud platform without burdening the IT team. Designer Cloud enabled business users to see exactly how data would be transformed before moving it to the cloud. It also provided a clear audit trail of where the data originated and how transformations had been applied. The ability to save and reuse transformations allowed business users to accelerate their work with each new batch of data. Moreover, as data scientists leveraged data for machine learning or predictive models, Designer Cloud enabled them to reduce the amount of time spent preparing data. For instance, a project that once required nine months has now been reduced to three weeks with Designer Cloud.

Impact #1	The adoption of Designer Cloud resulted in secure and seamless data migration from on-premise to cloud platforms. It provided visually-driven data transformation and detailed data lineage, offering transparency around data origins and changes. This led to an increase in data quality as business users with the right context of the data were able to prepare it themselves, leading to more robust insights in the long run. The solution also increased efficiency by involving the IT team in data preparation only when necessary, allowing data scientists to focus on modeling rather than data cleansing.

Impact #1

The adoption of Designer Cloud resulted in secure and seamless data migration from on-premise to cloud platforms. It provided visually-driven data transformation and detailed data lineage, offering transparency around data origins and changes. This led to an increase in data quality as business users with the right context of the data were able to prepare it themselves, leading to more robust insights in the long run. The solution also increased efficiency by involving the IT team in data preparation only when necessary, allowing data scientists to focus on modeling rather than data cleansing.

Benefit #1	92% reduction in analytic build time
Benefit #2	Data preparation time decreased from 9 months to 3 weeks

Benefit #1

92% reduction in analytic build time

Benefit #2

Data preparation time decreased from 9 months to 3 weeks

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Overview

Deutsche Börse Group's Transformation with IoT: A Data Science Lab Case Study

Operational Impact

Quantitative Benefit