Case study

The super functional maps.

Implementing an engine for transforming and processing geospatial data for user perks.


The company needed to create a more effective information exchange between Data teams and GIS experts. One of the essential components required for that was implementing a tool for exchanging data between various formats including: relational data, GIS data formats and Big data file formats.


Low level performance optimisation was crucial. Initially the GIS area was upskilled. The initial analysis of GIS specialists’ preferred interactions combined with  the benefits of automatic data processing at scale was the basis for our approach to best meet all expectations. We implemented a tool for data transformation between multiple commonly used formats.

Technology & Tools



A worldwide renowned computer and consumer electronics company. One of the largest globally. Headquartered in the USA, it deals with design and manufacturing. Offer includes software and related services and accessories  as well as third-party digital content and applications. Both for consumers and professionals. 


Operating fast in order to provide relevant updates based on various data sources is crucial for a B2C company building a map service. Achieving efficient updates requires a good communication framework between various teams, among others: Engineers, GIS experts, Data Entry experts. It also calls for compatibility of GIS solutions with big data.


Firstly the already implemented solutions at the company were analysed against the review of the working ways of the GIS experts combined with their expectations. They are the enabler of the product, making them the primary interest group. 

Secondly, existing data models and their fit together was analysed. It revealed that a data transfer from completely different types of models (object, relational) was the key challenge. The implementation required flexibility to fully support the corner cases inevitably resulting from the complexity of the domain. The delivered solution was capable of transforming every existing data set from and to a relational model.


The capability to flexibly transform data greatly improved the ability of GIS experts to participate in the work of data engineers. It also dramatically improved the feedback loop of all the changes introduced in any of the existing systems.

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