Client background & business context

  • Client: German manufacturing company specialized in high-quality technology for sensors and measuring instruments and complete measuring systems with more than 75 years of market experience 
  • Project: Software Development 

Services we provide:

  • Data Lake design and implementation – design a Data Lake that allows our client to ingest the data from all the platforms and databases it has the data currently on. This allows for much easier and faster analysis of the data as well as increased speed in manipulating and transforming the data and presenting them into reports directed to the business team. 
  • Statistical analysis and reporting – we provide our client with analysis of the data he has acquired and first give him insights on the quality of the data and initial value we can find from our datasets. 
  • Smart algorithms and AI – once we are able to create our datasets and identify the most valuable pieces of data, we use them to train machine learning models to allow our client’s devices to become smarter and handle many more scenarios automatically, with fewer human intervention. 


  • Our client’s biggest challenge was to find a way to extract value from the hundreds of gigabytes of data they have accumulated from their devices and sensors: first understand their data and then build smart algorithms to automate the processes that involve human intervention like maintenance and device checkup. 

Our approach

Over the last year, the team was involved in every software development phase, starting with developing the Data Lake infrastructure, ETL jobs, data processing scripts and jobs as well as development of the business-facing reports, data analysis scripts and ending with developing the statistical and machine learning models for improving the way our client’s devices work. 

To create a clear vision about our client’s business, every new member attends several knowledge sharing sessions and new members have a mentor/buddy assigned. The sessions include different types of subjects, starting with general ones (client’s industry, Data Lake Infrastructure, goals), and ending with subjects which are related to the new member’s area of expertise. 

Throughout the year the team has developed a strong connection with the client’s main stakeholders which allowed the team the ability and freedom to express their ideas for further developing the infrastructure and the processes. Most of the suggestions have already been implemented and we were able to reduce the ETL and data processing time of all of our incoming data by more than 5 times. 

We managed to provide a client-centric software solution by:  

  • Having a proactive attitude and taking care of our client’s Data Lake and ETL jobs in order to always provide him with the ability to analyze his data, monitoring jobs and coming up with proposals for newer solutions that could reduce the time it takes for the data to become available in the Data Lake 
  • Understanding the bigger picture and the actual need of the client, not only the technical problem that needs solving. We keep in mind the big picture and the actual business problem the client tries to solve and we come up with the best solution for his problem, sometimes with improvements in areas where he did not explicitly request. 
  • Implementing new techniques and upgrade the Data Lake infrastructure to reduce costs and increase the processing speed of the client’s data 


Cloud computing platforms 

  • Microsoft Azure 

Development tools: 

  • Python 
  • Azure Databricks and Spark 
  • PowerBI 


Due to the implementation of our Data Lake and ETL jobs we have reduced the response time of getting answers to our clients from their data by over 10 times. The Data Lake also allows our customer to connect PowerBI reports to our Data Lake much easier and he can get updated insights much faster than before. 

Building on the analysis of the data, we have trained machine learning models and statistical models that allows our client to tune their devices much easier and also allows the devices to handle more scenarios with less human intervention. 

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