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

Delivering a comprehensive report comparing 7 data platform solutions and advision on best option to steer future data platform strategy

Problem

• 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

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

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

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

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

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

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

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

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

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

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

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

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

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)