Download PDF
Deutsche Börse Group's Transformation with IoT: A Data Science Lab Case Study
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
The 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 The 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.
The 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.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
System 800xA at Indian Cement Plants
Chettinad Cement recognized that further efficiencies could be achieved in its cement manufacturing process. It looked to investing in comprehensive operational and control technologies to manage and derive productivity and energy efficiency gains from the assets on Line 2, their second plant in India.
Case Study
IoT System for Tunnel Construction
The Zenitaka Corporation ('Zenitaka') has two major business areas: its architectural business focuses on structures such as government buildings, office buildings, and commercial facilities, while its civil engineering business is targeted at structures such as tunnels, bridges and dams. Within these areas, there presented two issues that have always persisted in regard to the construction of mountain tunnels. These issues are 'improving safety" and "reducing energy consumption". Mountain tunnels construction requires a massive amount of electricity. This is because there are many kinds of electrical equipment being used day and night, including construction machinery, construction lighting, and ventilating fan. Despite this, the amount of power consumption is generally not tightly managed. In many cases, the exact amount of power consumption is only ascertained when the bill from the power company becomes available. Sometimes, corporations install demand-monitoring equipment to help curb the maximum power demanded. However, even in these cases, the devices only allow the total volume of power consumption to be ascertained, or they may issue warnings to prevent the contracted volume of power from being exceeded. In order to tackle the issue of reducing power consumption, it was first necessary to obtain an accurate breakdown of how much power was being used in each particular area. In other words, we needed to be able to visualize the amount of power being consumed. Safety, was also not being managed very rigorously. Even now, tunnel construction sites often use a 'name label' system for managing entry into the work site. Specifically, red labels with white reverse sides that bear the workers' names on both sides are displayed at the tunnel work site entrance. The workers themselves then flip the name label to the appropriate side when entering or exiting from the work site to indicate whether or not they are working inside the tunnel at any given time. If a worker forgets to flip his or her name label when entering or exiting from the tunnel, management cannot be performed effectively. In order to tackle the challenges mentioned above, Zenitaka decided to build a system that could improve the safety of tunnel construction as well as reduce the amount of power consumed. In other words, this new system would facilitate a clear picture of which workers were working in each location at the mountain tunnel construction site, as well as which processes were being carried out at those respective locations at any given time. The system would maintain the safety of all workers while also carefully controlling the electrical equipment to reduce unnecessary power consumption. Having decided on the concept, our next concern was whether there existed any kind of robust hardware that would not break down at the construction work site, that could move freely in response to changes in the working environment, and that could accurately detect workers and vehicles using radio frequency identification (RFID). Given that this system would involve many components that were new to Zenitaka, we decided to enlist the cooperation of E.I.Sol Co., Ltd. ('E.I.Sol') as our joint development partner, as they had provided us with a highly practical proposal.
Case Study
Splunk Partnership Ties Together Big Data & IoT Services
Splunk was faced with the need to meet emerging customer demands for interfacing IoT projects to its suite of services. The company required an IoT partner that would be able to easily and quickly integrate with its Splunk Enterprise platform, rather than allocating development resources and time to building out an IoT interface and application platform.
Case Study
Bridge monitoring in Hamburg Port
Kattwyk Bridge is used for both rail and road transport, and it has played an important role in the Port of Hamburg since 1973. However, the increasing pressure from traffic requires a monitoring solution. The goal of the project is to assess in real-time the bridge's status and dynamic responses to traffic and lift processes.
Case Study
Bellas Landscaping
Leading landscaping firm serving central Illinois streamlines operations with Samsara’s real-time fleet tracking solution: • 30+ vehicle fleet includes International Terrastar dump trucks and flatbeds, medium- and light-duty pickups from Ford and Chevrolet. Winter fleet includes of snow plows and salters.