Technology modernization

Use the right technology to get the most value from your data. A modern technology stack will make your data processes easier, faster, and more impactful. It will also scale and support your business’s long-term growth with no additional overhead. By implementing leading software, you become a pioneer in the solutions you adopt, putting you on the best path toward becoming data-driven.

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Check out the latest news, articles, and events

Blog post

DEEP LEARNING FOR UNSTRUCTURED DATA? YES, YOU CAN !

August 9, 2021

Today, you take a picture of a paper bill and it gets suddenly processed by your banking app without you doing anything but confirming through Face Id recognition. Today, you speak to your microphone’s car while driving and it starts calling someone from your contact list. Today, you are probably old-fashioned if you never used google translate to process some sentence in another language, right?

Expert's opinion

UPGRADE OF A SEMARCHY XDM SOLUTION

August 9, 2021

In 2014, one of our clients (leading provider of packaging worldwide) sought a solution to bring structure to their customer base. They reached out to Keyrus who designed and developed the Customer Data Integration (CDI) tool.

Blog post

BE MORE EFFECTIVE THAN DOLLY PARTON ON OPEN BANKING

August 9, 2021

Appropriate action is a combination of marketing automation and of the personal touch by your frontline staff. Make it data driven.

Blog post

WHY DATA SCIENCE NEEDS BOTH MACHINE LEARNING AND CAUSAL DATA ANALYSIS

August 9, 2021

Data Science is running complex machine learning algorithms on ever growing datasets. The promise towards business stakeholders is to replace gut decisions and experience with objective and improving algorithms. But is machine learning the only game in town data scientists need to help business decision making?

Blog post

RISE OF THE CITIZEN DATA SCIENTIST

August 9, 2021

And why you still can’t replace your employees with software completely...

Blog post

DATA SCIENCE EXPLAINED BY BAKING CAKE

August 6, 2021

A few times I have been asked what it is I do exactly as a data-scientist, and managers and potentials data-scientists especially are interested in the common struggles we as data-scientists have to deal with. Just listing all issues we comes across would not result in an interesting read, so I will present it to you in the form of an analogy you’re all familiar with: baking cake.

Blog post

Data Visualization and Decision Making

August 6, 2021

“In 2019, one of the leading actors in the Oil Industry, was assessing different possibilities for the implementation of a mobile payment solution in their B2B segment. In order to be able to take data driven decisions, they reached out to Keyrus to set-up a data visualization solution.”

Blog post

DATA AND ANALYTICS: THE FOUR TYPES OF DATA ANALYTICS

August 6, 2021

You might have heard the saying Data is the new oil. This mainly refers to their potential value and in both cases this value is not merely in the raw product but rather results from the way it is processed. In this article we present a commonly used classification of data and analytics into descriptive, diagnostic, predictive, and prescriptive analytics. We’ll discuss each of these separately including some of the commonly used methods. Thereafter follows how these four types of data analytics relate to each other. First however we’ll explain what we exactly mean with data and analytics.

Blog post

THE HUMAN BEHIND THE DATA (PART 3 OF 3)

August 3, 2021

You’ve made it to the third and final part in our series ‘The human behind the data’. This will all be about (illusionary) patterns and the importance of some good old probability theory.

Blog post

THE HUMAN BEHIND THE DATA (PART 2 OF 3)

August 3, 2021

In part 1 of this series you read all about the difficulties to stay objective when selecting the data you want to work with. Simpson’s paradox, multicollinearity, Robinson’s paradox, survivorship bias, and cherry picking were all issues showing how important your decisions as a processor of data are. In this second part we’ll show that you yourself can become data which will seriously influence the outcome of your research, and we’ll also show how critical it is to choose the right measurement tool.