We have talked about it for years now. Consultancies have been saying for a long time that we need it. Maybe you are even aiming towards it in your strategy? What exactly is Big Data? and how did we get to talk so much about it? Before reading further, try answering the following question - no cheating: How many V's defines Big Data?
In this blog post we are talking about something that in machine learning is called data leakage. Please, do not misunderstand it as the leakage of data to the public. Data leakage in machine learning is when using a feature for predicting the output, that at the time of prediction cannot be available. In many cases, the feature holds information about the value we are trying to predict.
“Reduce energy consumption in your household, and you will live longer". This could be a headline in your favorite tabloid. People have a tendency to see a correlation between two values, and determines immediately that there is causality. But would you really live longer without energy in your household?
Artificial Intelligence. The word itself says something about what it does. It tries to create an intelligence, artificially. But how? What exactly is it? Can it improve your everyday life? Can it improve businesses? What is Machine Learning in this picture?
With the introduction to big data and later industry 4.0, an increased focus has arisen on the usage of data in the industry. Even though industry 4.0 still rises confusion to what exactly it is and what it is not, one thing we can agree on is that it involves data.
In this blog post we will go through the different approaches to big data, define what big data is, and how to use it to create value. There are many opinions on how to handle and use big data, the reality is that many do not have a clear idea of the amount of data that are being generated in their companies.