There are many ways to get involved with Xoogler.co. The organisers page on Xoogler.co can give you a good idea about possible roles and activities. However, arguably the simplest, most accessible way is to start a subgroup or community together with other Xooglers who all share the same interest.
What follows is based on my story with the group I created, the Solopreneurs & Freelancers group.
Read on to learn about the specific ways a Xoogler group can benefit its members and the broader network as well as the group organiser. …
Krista is one of the most influential voices in the digital analytics industry. She has trained thousands of new analysts via her YouTube training courses. She is also a keynote speaker, practitioner, writer on Analytics and Optimization, and a passionate supporter of #WomenInAnalytics. Krista is currently running her own analytics consultancy, KS Digital. Prior to that, she held key roles in some of the leading companies in the field, including Adobe, Quantcast and Google.
Krista discussed the major trends in the digital analytics industry as she observed them through her own independent research. Her study is based on responses from hundreds of analytics professionals. The insightful talk and discussion that followed shed light on key aspects of a changing industry. …
If you are a data professional considering to upskill, there is no shortage of learning options, but if you are looking for ways to transition your data and analytics to the Cloud, you can choose between only a limited number of public Cloud providers.
This guide focuses on Google Cloud, more specifically the Data Engineering on Google Cloud specialisation (formally known as Data Engineering on Google Cloud Professional Certificate), and provides you with up-to-date information and practical advice.
It is based on my own experience completing the specialisation along with input gathered from other data engineers also working in the field. …
It was no doubt an interesting encounter, with Google Analytics meeting:
Kaggle (the machine learning competition platform)
Rstudio (the cash prize sponsor)
and Big Query (the data host).
The purpose ? to organise a machine learning competition- the first of its kind having Google Analytics data as its raw material.
The event (in its first phase, i.e. before the redesign due the data leakage, more on this later) attracted more than 3,500 teams, making it one of the most popular competitions hosted in the platform’s 8 year history.
This article is a summary of what happened, coupled with a few thoughts around particular aspects that I found of interest -starting with the Kaggle experience itself, followed by the highlights of this particular competition and closing with the takeaways. …
“R or Python? That would be an ecumenical matter!”
It was the amusing title of a past data meetup in the city of Dublin where the topic was debated.
Apparently making the choice between R and Python is not the most straightforward decision. A web search will return numerous articles trying to answer which one is better or which one to learn first. After examining facts and figures about each of the two, however, the typical conclusion of those articles is one of the following …
Terms such as data science, machine learning and artificial intelligence have found a well deserved spot in the “pantheon” of tech buzzwords.
We hear and read about them almost on a daily basis. In fact they are often used interchangeably, even though depending on the source there are clear preferences (you might have noticed a certain fondness that say marketing and media have for the term AI).
The illustration above is an adaptation from PWC, one of the many Venn diagrams available on the internet attempting to explain the relationship between the terms, but it is not very straightforward.
Can we use data and analytical methods to capture the meaning and semantic context of these terms ? Ok, let’s give it a go and try to fight fire with fire. The Wikipedia clickstream dataset will be of great help for this. …