hadoop big data with a minimal downtime

7 tips on how to fix a large amount of data in Hadoop

by Marek Sušický, Head of Big Data

I have been working on an international big data project. The cluster is huge, with TBs of memory and hundreds of CPUs – another great experience in the real world of big data and parallel computing for our team. In this short article, I’d like to share a story about some lessons learned with a…

predict client credit default with ai

Managing credit risk with advanced data analytics

by Barbora Fuksa, Business Development Manager

The traditional approach to quantifying credit risk in retail banking often relies on the most obvious variables such as annual/monthly income, employment length, employment title, etc. While these are still valid indicators for calculating...

data science project with unstructured data

The Real Challenge in Social Network Data Science

by Petr Paščenko, Head of Data Science

As even the slowest thinkers of our current era have already recognized, social networks and related phenomena, defined in the broadest possible terms, are a great source of insight into human behaviour and preferences as well as a vital resource for data analysis and predictive modelling. The key phenomenon in predictive modelling based on social…

data scientist in a project

3 Data Science Process Challenges

by Sergii Stamenov, Data Science Consultant

Graduating students hope that they will create a new recommendation system or search ranking algorithm. In reality, they have to deal with missing data, scalability and integration issues. On top of that, they have to learn the company’s processes or build new ones. It is no surprise that school is different from the working environment,…

data science project

How to Succeed in Data Science Projects

by Lukáš Dvořák, Business Development Manager

The effectiveness of data science projects is one of the hottest topics in business intelligence nowadays. On the one hand, we are discussing the huge potential of artificial intelligence in executing sophisticated tasks for businesses. On the other hand, we see the harsh reality of today. Large companies like banking institutions are struggling hard to…