Design of a Cloud Data Analytics Platform

Design of a Cloud Data Analytics Platform

Design of a Cloud Data Analytics Platform

Expert: Michael Scharpf

Industry: Energy

Area: Marketing & Sales

Maximise operational efficiency and reduce costs with our customised cloud data analytics platform that seamlessly unifies complex data infrastructures.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

Our client, a widely branched company with several autonomous organisational units, faced a significant IT and data infrastructure challenge. Each unit operated its own IT and data infrastructure, which made the consolidation and use of all company-wide data an extremely complex matter. Our goal was to develop a unified platform that enabled this data integration without compromising the autonomy of the individual units. In addition, the platform had to cover both development and production operations, which presented another challenge in terms of scalability and flexibility.

[Solution]

With our focus on the use of cloud technologies and our deep understanding of data science and artificial intelligence, we were well equipped to tackle this challenge. We started the process with a comprehensive requirements gathering for the platform in collaboration with all organisational units. This was critical to understanding the specific needs of each unit and developing a solution that was tailored to their individual requirements.

In the next phase, we tested the most important scenarios on possible technologies to ensure that our solution would meet the client's requirements. We chose a modular design based on cloud technologies such as AWS and Azure to make the platform flexible and adaptable.

Data access was enabled both via a central data lake and directly via the source systems of the individual organisational units. This ensured that the autonomy of the units was maintained, while at the same time a central, cloud-based data analysis platform was established.

[Result]

The end result was a highly flexible, efficient and adaptable cloud data analytics platform, designed on the basis of Collibra and one Azure/AWS stack each. This customised solution enabled all of the client's organisational units to work seamlessly and efficiently with enterprise-wide data without adapting their existing IT infrastructure.

The platform was characterised by its high adaptability, which gave the organisational units maximum flexibility in data use. At the same time, the use of cloud technologies ensured that overall costs were kept low. This is a key advantage when it comes to optimising business efficiency.

Another significant advantage was the end-to-end coverage of all common data use cases. Regardless of the type of data evaluation or analysis required by the different units, our solution was able to meet these requirements.

In summary, we have developed a powerful, cost-effective and flexible cloud-based data analytics platform that enables the client to centralise and optimise its data-driven decisions while preserving the autonomy and individual needs of each organisational unit.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Michael Scharpf - Key Account Manager

Your expert

Michael Scharpf | Sr. Principal Key Account Manager | Alexander Thamm GmbH

Omnichannel data integration of customer data

Omnichannel data integration of customer data

Omnichannel data integration of customer data

Expert: Michael Scharpf

Industry: Energy

Area: Marketing & Sales

Turn your customer data into valuable insights and create a seamless customer experience with our innovative omnichannel data integration solution.

OUR AI AND DATA SCIENCE Case studies:
EXPERIENCE FROM OVER 2,000 CUSTOMER PROJECTS

[Challenge]

As a leading provider of data analytics and artificial intelligence solutions, we were faced with the challenge of helping a renowned energy company that wanted to offer personalised content to its customers. The client's requirement was to effectively use cross-channel information to achieve a complete and comprehensive representation of the customer journey in a data model. The goal was to optimise internal processes on the basis of this representation and the analyses based on it. In this context, there was a special focus on the aspect of omnichannel data integration.

[Solution]

Our solution began with a thorough evaluation of the tool used by the client, particularly in terms of the data collected and the ability to export data. Our expertise in data science and artificial intelligence allowed us to gain a comprehensive overview of the client's data landscape and fully utilise the tool's data collection and export capabilities.

In the next phase of our solution strategy, we developed an optimised data model based on the tool the client was using. This model took into account all aspects of omnichannel data integration, which enabled the client to gain a comprehensive understanding of the customer journey and deliver tailored content across different channels. In addition, we took on the definition of exporting data to a data warehouse to further increase the efficiency of data management and analysis.

[Result]

After our optimisation, the tool used was able to collect all relevant data and effectively map it into the data model we developed. This has resulted in the client now having a clear understanding of their customer journeys and being able to deliver personalised content based on cross-channel information.

In addition, the implementation of the data export to the data warehouse was successful. This extension of the existing infrastructure enabled the company to optimise its internal processes and achieve better utilisation of its data resources. This success underlines our expertise in Omnichannel Data Integration and our commitment to providing our clients with customised, effective and efficient solutions.

Curious now? Let us show you what sets us apart from other companies and how we can help you achieve your goals.

Michael Scharpf - Key Account Manager

Your expert

Michael Scharpf | Sr. Principal Key Account Manager | Alexander Thamm GmbH

Forecasting the demand for balancing energy for energy trading

Forecasting the demand for balancing energy for energy trading

Forecasting the demand for balancing energy for energy trading

Using historical data and forecasts from the energy sector, the balance of physical control energy calls is to be 
in the German grid control network (NRV) are forecast.

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Identification of the sign of the balance with a quality of 83% for positive balances

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Significant improvement of the absolute deviation in comparison for simple updating

Walkforward model that is constantly improving with new data

Challenge

An energy service provider would like to Machine Learning model for Forecast of the positive or negative balance of control energy in the Grid Regional Network (NRV). The aim is to be able to operate on the volatile to be able to trade more efficiently in the electricity market.

Solution

Numerous data sources are cleaned up and integrated into a unified Time series format merged. A visual and data-based Exploration of correlations and possible influencing factors will be is carried out. Subsequently, several regression and Classification models for the prediction of the balance or its Sign and application of a two-stage ensemble model created. 

Result

Es there is a prototype of a forecasting model that is geared towards this, with currently available data, the balance of control energy in 15 minutes to predict. This allows the electricity producer to position itself in the market. better position. 

Are you interested in your own use cases?

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, including of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.

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Development of a predictive maintenance strategy for the data and IT infrastructure

Development of a predictive maintenance strategy for the data and IT infrastructure

Development of a predictive maintenance strategy for the data and IT infrastructure

Development of a data-driven and condition-based maintenance process, which is worth over €5 million.   Annual savings potential identified

More efficient maintenance shows savings potential of €5 million annual

The prototypical application creates transparency about historical Maintenance

Data strategy and platform architecture for AI

Challenge

A DAX-listed energy supplier would like to have a data-suitable IT and business architecture. Furthermore, maintenance costs are to be of its systems and exemplified by the component LuVo (air preheater) the feasibility can be demonstrated

Solution

In the [at] Architecture and Roadmap Workshop, the technology and data basis is determined. This is followed by the exploration of the existing data sources and reviewing identified Requirements. A holistic process and data view of the IT and PDV systems developed. A data generating  Maintenance process is designed and the business case developed. 

Result

The architecture and data strategy depends on the concrete needs of the use-Case requirements derived. A prototypical Predictive Maintenance App for planning and an interactive process click-Dummy are created. A requirements analysis including a business case for data collection is also available. 

Are you interested in your own use cases?

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, including of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.

Our Case Studies

- Get even more detailed insights into our customer projects -

Smart cooking with Thermomix

Smart cooking with the Thermomix

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Case Study AI at Munich Re

Data Operations at Munich Re

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Creating added value from data & AI together

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Discover professional articles on Data & AI as well as the latest industry news.

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Migration from On-Premise to Azure Cloud

Migration from On-Premise to Azure Cloud

Migration from On-Premise to Azure Cloud

Development of a REST API service in Azure for group-specific new customer assessment 
Based on internal and credit agency data 

Modern, more fail-safe infrastructure

The internal analytics team is empowered to provide the credit rating service to develop independently

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The developed Rest API can be used as a template for further use cases. be used.

Challenge

An energy supply company is migrating a large part of its infrastructure to the cloud. The previously used on-Premise Credit rating (R, C#) to be replaced by a new service (Azure, Python) be replaced. Increased safety regulations must be applied to reason of highly sensitive data are respected. 

Solution

There will be coordination with the legal department regarding specific GDPR guidelines as well as the integration of additional Security measures for the storage of sensitive, personal data in the cloud. Subsequently, a REST API with integrated data preparation, model training and realtime-Scoring, and Logging of all enquiries deiwckled. The Data pipeline will be integrated into the Azure infrastructure.

Result

The API creditworthiness service goes live. The internal Credit checks can be carried out as a service throughout the Group and across all brands. be used.

Are you interested in your own use cases?

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, including of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.

Our Case Studies

- Get even more detailed insights into our customer projects -

Smart cooking with Thermomix

Smart cooking with the Thermomix

Download
Case Study AI at Munich Re

Data Operations at Munich Re

Download

Data & AI Knowledge

Creating added value from data & AI together

Blog

Discover professional articles on Data & AI as well as the latest industry news.

Webinars

Dive into our Best Practices and Industry Exchanges. Discover new dates and recordings of past webinars.

Whitepaper

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