Immuta Evaluation
German Automotive Company
Developed and conducted benchmark to analyse fit for purpose level of SaaS solution on data access and governance
Challenge
- Client interested in deploying IMMUTA SaaS solution to handle data access and governance
- Needed advice and technical due diligence before committing significant resources to integrate the new platform
Solution
- Conducted a benchmarking of the SaaS solution using requirements defined by client and presented results in a workshop
- Benchmarking conducted considering different end user perspectives, including topical deep dives and live demos
- Developed possible deployment scenarios
Business impact
- Received expert assurance that IMMUTA solution was fit for purpose and worth the investment
- Able to anticipate potential future weaknesses of solution and develop workarounds in advance
Data Platform Selection Advisory
German Automotive Company
Delivering a comprehensive report comparing 7 data platform solutions and advision on best option to steer future data platform strategy
Challenge
- Wanted to implement new data & analytics solution for core use cases
- Needed to review available data platforms before deciding on a strategy, preferably selecting a low-code option
Solution
- Combined research efforts with our expertise to advise on the best data platform which would fit the client’s needs
- Compared and ranked across 7 dimensions (e.g., ease of use, data governance, etc.)
- Delivered comprehensive final report with best option recommendation
Business impact
- Client able to steer data platform strategy thanks to full report comparing 7 solutions across 7 dimensions
- Ensured that no data platform provider would be overlooked prior to decision making
Residual Value Forecasting
German Automotive Company
Developing and deploying a predictive model for residual value forecasting of vehicle portfolio, resulting in more accurate forecasts and higher margins
Challenge
- Large portfolio of vehicles across the globe
- Need to accurately determine accurate monthly payments and residual value on leasing contracts
- Central computation of residual value difficult as criteria vary from one country to another
Solution
- Worked together with internal team to integrate multiple data sources from the past 12 years together
- Deployed linear regression model refined by incorporating our forecasting expertise
- Applied state of the art model improvements to gain in transparency and control over the learning and predictions
Business impact
- More accurate prediction in residual value compared to existing model
- Increased transparency and explainability of results
- Enables future improvements as model was designed with scalability in mind, ensuring that results stay accurate as new data becomes available
Design and Implementation of D&A Solution on Azure
German Automotive Company
Created infrastructure to enable quick Dataiku setup on Azure, with custom plugins and altering system resulting in higher scalability and fewer downtimes
Challenge
- Maintenance of existing Dataiku platform was too time consuming and the platform was failing too frequently
- Many steps needed to be done manually, both from user and administrator side
Solution
- Created an infrastructure as code scripts to enable a quick Dataiku setup on Azure
- Developed custom Dataiku plugins to enable more self-service for governance
- Integrated with additional (Azure Data Lake and Kubernetes)
- Created monitoring system to gain real time insights on system performance
Business impact
- Enabled much higher self-service capability on platform, simplifying usage and administration
- Scalability both in terms of storage and compute
- Fewer and shorter downtimes on platform
- Monitoring system integrated with Teams enables quick reaction to emergencies
MLOps & Data Governance
German Automotive Company
Defining model guidelines and developing data governance for data lake resulting in successful deployment of models compliant with strict regulations
Challenge
- Client in middle of a digital transformation and experimenting with big number of ML use-cases on proprietary data platform
- Need to operationalise some ML models while avoiding lock-in of vendor platform
Solution
- Implemented guidelines for model training, deployment and maintenance in hybrid environment
- Developed data governance for data lake
- Built model-serving layer bridging the gap between Dataiku and Kubernete
Business impact
- Successful transition from experimentation phase to deployment of multiple ML models while maintaining strict standards of Finance Department
- Client was able to integrate model with multiple client-facing applications
Open Source D&A Platform
German Automotive Company
Supporting the creation of an entirely open source Data & Analytics platform, enabling a self-service and hassle-free approach to development
Challenge
- Product silos prevent efficient collaboration across different teams
- Processes often done manually and require multiple approvals, slowing down development
- Client tech department lacks public exposure, preventing them from hiring top talents
Solution
- Currently supporting the development of an entirely open source Data & Analytics platform
- Exploring existing open sources solutions, making them enterprise ready, adding functionalities based on client needs, and integrating them into existing services
Business impact
- Increased exposure to the open source world and to other companies interested in the topic
- Self-service approach for users to develop solutions with minimal friction
- Enabled internal teams to discover state-of-the art data solutions that Unit8 used
Architecture and Implementation of D&A Platform
German Automotive Company
Helped in designing and testing future D&A platform in collaboration with internal team resulting in clear architecture and migration scenario
Challenge
- Goal to prepare conceptual blueprint for new D&A platform avoiding known pitfalls from previous one
- Faced paradigm shift because data lake originally planned was replaced by data mesh
- Need to develop many architectural concepts from scratch due to data mesh concept being scarcely used in productive use cases
Solution
- Together with internal team, prepared documentation of technical concepts and requirements, and created several PoC in various areas
- Defined platform operation and testing concept
- Carified architecture to make it compliant to internal policies
- Helped prepare for migration
Business impact
- Clear platform architecture enabling stable deployment components compliant with design and requirements
- Pre-defined migration scenario easy to execute in production environment
- Internal team can now operate more autonomously
Azure Event Stream Architecture
Swiss Mountain Rescue Company
Providing best practices to the client’s technical provider through a workshop and delivering an optimal architecture design to implement new solution
Challenge
- Wanted to introduce more scalable Azure-based streaming platform to collect location data from rescue helicopters more frequently
- New device to be installed would send location data 15x more frequently which would overload current infrastructure
Solution
- On-site meeting with technical provider chosen by client to conduct a workshop and provide best practices on streaming architecture
- Delivered optimal streaming architecture design after careful comparison between different alternatives
Business impact
- Consulting project without implementation from Unit8
- Helped client’s technical providerto define best approach for new architecture
- Could enable new use cases thanks to higher frequency location data availability
Airlines Data Platform Onboarding
Airplane producer
Onboarding airlines across 3 continents on a central data analytics platform with activities such as training and enablement of new users
Challenge
- Need for airlines’ data scientists and executives to explore data independently and be able to implement new use cases on their own
Solution
- Prepared educational material, such as presentations and project examples
- Gave lectures and conducted workshops to train new users to use the Foundry platform
Impact
- Enabled new users to acquire new skills allowing them to implement future use cases and to analyse data independently
Aircrafts Predictive Maintenance
Airplane producer
Implementing a data platform to centralise maintenance data from hundreds of airlines and enable predictive maintenance models
Challenge
- Integrate data from 100s of airlines on a single platform
- Reduce or eliminate operational interruptions and minimise the number of aircrafts immobilised due to unforeseen maintenance needs
Solution
- Integrated sensor data and telemetry into central data lake
- Developed predictive maintenance model outputting the probability of maintenance need in the next 5 flights for each aircraft
Impact
- Notable improvement in speed of problem detection, triaging and resolution
- Enabled feedback loop to aircraft design teams to prevent similar issues from reoccurring
Forecasting platform
Major German Automotive
Problem
- Our client, a global automotive company, lacked a central data platform for forecast generation and analysis. As a result, its teams could not collaborate or analyze data efficiently.
Solution
- a modern data platform with long-term scalability was scoped, designed and implemented together with the initial first Proof of Concepts
Impact
The new platform enables the customer to:
- Develop and operate forecasting models quickly and consistently
- Collaborate on and reuse models, preventing redundant code development
Data lake buildup
Major German Automotive
Problem
- Siloed data spread across multiple systems
- Inability to properly analyse manufacturing/test/sales data on a common platform
Solution
- New data infrastructure architecture and buildup
Impact
- Enterprise data lake. Governed, and secured
- Foundation for the analytical use cases
Residual value prediction
German automotive
Problem
- Car manufacturer holds large global leasing portfolio that has to be periodically evaluated
- Current valuation predictions are inaccurate
Solution
- Based on a large volume of past transactions (12 years) and cars parameters (model, mileage, options), etc. predict accurately the residual value of the car
Impact
- Accuracy of the valuation improved by $100M’s (from large overall base value)