Supervised Learning – Teaching the machine how to do tricks
A task-oriented approach to Machine Learning allows us to divide it into three categories: supervised learning (data are labelled according to some criteria), unsupervised learning (no labels exist for the data), and reinforcement learning (no data is directly available, only...
Transitioning from raw to high quality data by means of Data Pre-Processing
Some of the most important pillars in Data Science and Machine Learning supporting the ability to extract meaningful insights and knowledge from the data are: 1) how representative are those data of the phenomenon being measured and 2) the quality...
A quick dip into Artificial Intelligence and Machine Learning
Current developments in areas such as Computer Vision and Natural Language Processing continue to push us towards technologies that are expected to have a profound and long-lasting impacts in our daily lives (for example, autonomous driving and speech-to-speech translating systems,...
Superset reaches 1.0 and achieves Top-Level status at the Apache Software Foundation
In the world of open-source data visualization tools there are several offerings. One of those that gathered a lot of interest here at Link Redglue is Apache Superset. The project began in an internal Airbnb hackathon in 2015 and joined...
What Power BI Premium per User license has to offer for those who already have Premium
Although we believe that the latest Premium Per User license will be quite important for those who, at this time, have a Pro license or who was considering other offers available in the market, we consider that it will also...
What Premium Per User (PPU) license will change in Power BI adoption
The Power BI user community has long been asking for an intermediate tier between Pro and Premium licenses. To understand the current status, Power BI has (had!) three licenses: Free, for personal use only. Pro, licensed per user with a...
Should i still use a Kimball approach on a modern data warehouse?
Kimball has been a standard in the design and implementation of data warehouses over the years, mainly for gains in data reading performance. Lately, with the progress in analytics, the question has arisen whether the use of the Kimball methodology...
Data Lake or Warehouse? You don’t have to choose!
Today, more and more organizations are adopting the lakehouse pattern, which combines the best elements of data lakes and data warehouses. But first, let us provide you with some context. Let’s first talk about data warehouses We have all worked...
Do I really need Machine Learning?
There has been a recent hype in many business areas where many ‘data evangelists’ have been selling Machine Learning (ML) as a Holy Grail, promising that it will allow companies not only to solve most of their data-related problems but...
Data Vault as the single point of truth
There are several different ways to model your business and by consequence the data that supports it. Depending on your requirements are operational or analytical the model that suits them should be designed accordingly. Typically, for operational requirements you go...
