Scrum 🔗For the last 2 years, I have discovered and followed the Scrum framework in the Data Analytics Tribe. I know there are Pro’s and Con’s opinions in the Data Science area regarding it, but I must confess that for me it was a good opportunity to better auto-organise, know each other and move from a reactive to a proactive setup. How Scrum adventure started? 🔗In the pandemic year, 2020, we had a programme initiated by our Agile Coach Lead to enhance the Scrum internal team and to complete all spots with resources, even part-time as I was.

DATA and enthusiast, why not love to be a data analyst or a data scientist? 🔗For many years, I have been trapped in the big data and data scientist hype. I was working in the field as a specialist or expert, without being named a data scientist. I preferred to rather call myself a data analytics professional, as I felt to overwhelmed by the whole discussion and sometimes unaware by the value I bring at the table.

What is data quality? Is a process in which you are ensuring your raw data is accurate, consistent, timely and complete. Missing values In your data you can discover missing values or incorrect formats, more usual for date formats. Unwanted characters in columns For exemple, you don’t want to see in a column with years values as “<2009”, but “2009”. Examine categorical data For example, when you have Yes-No type of values might have missing values inside.