Success Stories

As different as my customers’ industries are, their topics and challenges are just as complex and diverse. I therefore offer tailor-made solutions that are efficient and sustainable.

Some of these success stories are listed below and can provide inspiration for possible joint projects and my way of working. If you have specific questions or project inquiries, I look forward to a personal exchange.

USE CASE WORKSHOP IN THE HEALTH SECTOR

How data can be used beneficially?

Task

The product data within the company has not yet been specifically used and evaluated. The product manager was faced with the task of developing the topic of data analysis for internal business evaluations and to create a database across all products.

Strategy

After an initial contact via LinkedIn, the specific briefing was discussed over the phone. It quickly became clear that identifying data applications and their potential outcomes made a lot of sense for the organization. Working on this in use case workshops became part of the project strategy. After preparing the offer, placing the order and the official kick-off date, we started with two workshops (3 hours each) in which a use case list including a description and prioritization was developed. Almost three weeks after starting the collaboration, we had a clear picture of the potential of the company's data.

Solution

A total of eight use cases were defined, three of which were put on a shortlist for prompt implementation and project planning with the appropriate resources and developers. The customer received two internal reports, on the basis of which existing data structures and the aggregation were prepared to provide KPIs to the company management. A targeted evaluation of conversion rates and forecasts of a digital product in the App Store were also developed. In addition to the prototype Implementation project also designed and documented the application architecture in the AWS cloud as the foundation for all subsequent implementations.

DATA ARCHITECTURE FOR A SOFTWARE PROVIDER

How do you fully exploit the potential of a current data architecture?

Task

Responsibility for a database and analytics applications can be extensive. My customer and their team had established some technologies in the Microsoft Azure environment the year before (including Azure Synapse, Azure Postgresql, Azure Functions, Azure Container Instances) and were familiar with the existing architecture. However, they wanted an external perspective and advice to further develop this architecture.

Strategy

Together with the customer's team, we derived the essential questions in order to design a further developed data architecture. In a second step, we determined the implementation plan for the individual streams.

Solution

A gradual conversion from a non-scalable, purely relational database architecture to an expanded database that also takes non-relational data sources into account could be implemented within a very short time. Another assignment was made in which I provided technical support as a data engineer during the implementation and helped set up the necessary data pipelines in Azure Data Factory. We increased the number of automatically orchestrated data pipelines from 5 to 25 within the project (+600%) where track would transfer around 0,75 Terabyte of data every day

DATA OPS & INFRASTRUCTURE FOR A MEDICAL COMPANY

How to create an individual data platform from scratch?

Task

As a data & analytics project manager, my customer wanted to operate and further develop a defined data infrastructure and create it as an internal platform for creating analyzes to support decision-making. However, its internal capacities for data engineering were severely limited and simply made it impossible to implement it on its own.

Strategy

Through internal coordination, three additional employees were assigned to the project on a part-time basis. At the same time, I was available three days a week to answer special questions about server configuration of virtual machines for Docker and R Studio Server Web. We also worked together to monitor the database connections and clusters. My work with the team was intended to ensure that the company builds up its own know-how.

Solution

Ultimately, after six months, all employees were able to access an internally hosted web application and work on a central R-Studio workbench, which represents the individually desired data platform to analyze different medical studies or analysis insights about offered products. With this workbench, unrestricted access to all company data was possible. I also trained other employees to continue operating the platform. All backed up with a Gitlab CI/CD environment with a datadog monitoring on top of it. During the project, the availability of the platform increased from 60% to 95%.

DATA INTEGRATION IN THE CONSUMER GOODS INDUSTRY

The fairy tale about harmonized data (sources).

Task

As stream lead “Data Integration”, my customer and their team were supposed to revise all data integration routes. However, the tool framework for setting up new pipelines and their automated monitoring was unknown to them until then.

Strategy

We defined the project steps together: the project team should continuously develop the corresponding data integration structure according to an agile mindset and a Scrum backlog. With my external perspective and my wealth of experience from other industries, I was able to provide important inspiration for the definition of architecture.

Solution

The entire team was trained in the tool framework to build the new pipelines and monitoring. I was also able to work on specific user stories and implement the jointly defined requirements as an externally hired data engineer. We recognised, that the amount of logged data quality issues per week was decreasing from 15 incidents to 5 within 6 months.

DATA VISUALISATION WITH ENERGY DATA

Stumbling blocks in data visualization.

Task

Being responsible for reporting as a business analyst means gathering all the information for a central reporting structure (in this case for the sales forecasting business area). My customer wanted to visualize this using the reporting tool Tableau and PowerBI. However, what was missing was the connection of the right data sources, the correct data modeling and ultimately the hands-on work in data visualization.

Strategy

As part of a coaching session, I was able to familiarize the customer with the desired tools and the specific requirements in a practical manner. The coaching took place in several blocks to ensure that any questions in handling were answered.

Solution

After the coaching, the customer was able to prepare all reports independently. After training, I continued to serve as their sparring partner. Due to the large amount of data and new requirements, I also increased my capacities and supported them in producing additional dashboards as an externally hired data engineer.