Business Intelligence for the industrial sector.

The project



The SFK company’s main objective was to order and reorganize the information held by different sectors. One of the main demands regarding the organization had to do with the areas of production, administration and sales. We worked for twelve months on the development of data models in several stage

It is a Swedish multinational company founded in 1907 dedicated to the design and manufacture of bearings, seals, lubrication systems, maintenance products and systems, mechatronic products, among other services. SKF is one of the largest Swedish companies and is one of the largest bearing manufacturers in the world, with 108 manufacturing centers and a commercial presence in 130 countries.

The process

One of our most relevant success stories is our client SKF. Since it was an important challenge that required integrations, data analysis and custom dashboard designs. One of the first steps was working on determining the inputs, working on the integration of the sales models and identifying the specific data models for the dashboards.
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Once we progressed with the project, we worked on the creation of Scripts, which allowed us to interpret the existing entities of presentations, products, brands, laboratories, clients, representatives, settlements and all kinds of internal information that the company had. From there, we design the DataHub data models and write the model population scripts (Python/SQL).
The result for our clients was highly satisfactory. We achieved the integration of the designed dashboards, guaranteeing the correct logic and indicators. In the same way we managed to do an analysis of the users involved, directed models and differential dashboards.


Reduction of costs, since the company has new, more accessible and faster information
Allows for multiple data analysis in a single report or dashboard
Includes Power View and Power Map tools
They have a qualitative leap to analyze the information in real time, and present the data on another level
Integrations with systems that used to be watertight compartments
Improves decision-making by automating processes


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