Data Science & Data engineering

While traditional BI is suitable for describing the past, data science is all about predicting the future and prescribing corresponding actions. It is the art of turning your data into advantages. This all is made possible by the domain of data engineering.

Fancy tools and technologies alone won’t give your business a competitive advantage. The essential element to create advantages from your data are people. People that are not only technically skilled to implement these algorithms and systems, but also understand the real challenges and needs of your business. This will be the only way to turn those challenges into opportunities and generate real impact.

Turn your data into an asset

Your data is an opportunity to get a competitive edge, to mitigate risks and to grow your business in a sustainable way by making the right decisions. But too often data remains unavailable, unknown or not combined and opportunities are missed. Are you seeing the untapped potential? Are you looking for the next step to take?

What’s your data challenge?

Don’t forget to also start treating your data as an asset! Check out our view on Data Governance

datashift ceo nico huybrechts
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"Data science is not about fancy algorithms. It is about data-driven problem solving in order to create business value."

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Eline Vanwalleghem
Data Science Lead
Datashift geared us up with the required architecture, knowledge and tools to be able to steer our business with insights. They clearly understood the importance of a hands-on approach at the start, evolving into a strategic and future-proof data roadmap later on.

Bart Van Den Langenbergh,
Head of Marketing & Sales, Streamz

Want to get trained in Data Science and Engineering? Follow The Link!

Get inspired by these Data Science and Engineering use cases

Read our paper on the Modern Data Platform here

Data Science and Engineering articles you might be interested in

Data-Driven Marketing: Embracing Data Science and AI for Success

This blog post explores the potential of data science and AI in enhancing marketing practices to achieve optimal results.

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What an event-driven architecture brings to the table to solve your data ingestion challenges

Before you can generate insights from your data, you need to move those data from an operational to an analytical environment - a process commonly referred to as data ingestion. An event-driven architecture provides an elegant way to achieve a process marked by timeliness, performance, and cost-effectiveness.

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How a data hub helps you step up customer engagement

A modern data platform makes integrating new services and empowering new use cases easier than ever. A data hub that provides your salespeople and service engineers with actionable customer data straight from your data platform is an excellent example of what you can achieve with modest effort.

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Who knows who: from Hollywood to Flanders

In this sequel on graph analysis we try to find connections between different actors and movies they played in. Some of the links are not obvious at first glance, e.g., what is the connection between Zendaya and Audrey Hepburn? Will Smith and Chris Rock? Xander De Rycke and Steven Spielberg? Andy Peelman and Steven Seagal? The method to find out those links is the Dijskstra shortest path algorithm.

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