Bamboozled. That’s your customers’ reaction to the Data Scientists in your organisation. Data Scientists need to communicate without jargon so customers understand, believe and care about their recommendations. Here is a Data Science jargon buster to help. Data Science is a technical field that applies scientific rigour to the understanding of business data and the associated processes […]
Data Science involves applying the scientific method to the discovery of opportunities and efficiencies in business data. An essential part of the scientific method is reproducibility. Reproducible Data Science is essential for scientific credibility but also improves your Data Science efficiency in 3 keys ways. If you start to apply the 7 Principles of Guerrilla Analytics your teams will quickly achieve reproducibility and […]
Programming language version 3.2. SQL, NoSQL, NewSQL. It seems that too often, the path to become a Data Scientist involves skills in vogue rather than more permanent competencies. In a fast paced field like Data Science, skills are more tangible. They can be directly tested. They can be dated to the latest technology or the latest language version. […]
A/B tests! Machine learning! Deep learning! It’s easy to be distracted by new libraries and beautiful visualizations. It’s easy to waste time with scattergun approaches to data and algorithms. It’s easy to forget that as a data scientist you should be taking a scientific approach to understanding data. Is scientific rigour appropriate in industry or should it be confined to […]
Vague mixes of skill sets. A focus on activities and technology. Bizarre Venn diagrams. It seems there is huge confusion over what Data Science is. Is it Big Data? Isn’t it statistics? Is it something else entirely? This confusion causes untold problems. It leads to vendor and recruiter hype. It leads to inflated career expectations […]
Confusion, hype, failure to start. Data Science has huge potential to change an organisation. It has real potential to improve the top and bottom lines. But many organisations become mired in the associated cultural, technological and people change. Data Science is delivered as an interesting report rather than a driver of change. Data Science identifies […]
People want some guidance in what can be a very overwhelming and fast moving field. Managers want to know what to buy and where to invest training. Junior data scientists, students, dev ops engineers and system administrators want to know what to learn. I will focus on the important capabilities for a Data Science team and the tools I have found useful for enabling those capabilities.
I gave the following lecture to Engineers Ireland which is the professional body for Engineers. It’s about “Data Science and the benefits for engineering” and is entirely in Irish.
It was an interesting exercise to brush up on my Gaelic and also to see the wealth or resources that now exist for using Irish with modern technical vocabulary. If you are curious or are trying to get your Gaelic up to scratch then please get in touch!
Are you a data scientist working on a project with constantly changing requirements, flawed changing data and other disruptions? Guerrilla Analytics can help.
The key to a high performing Guerrilla Analytics team is its ability to recognise common data preparation patterns and quickly implement them in flexible, defensive data sets.
After this webinar, you’ll be able to get your team off the ground fast and begin demonstrating value to your stakeholders.
You will learn about:
* Guerrilla Analytics: a brief introduction to what it is and why you need it for your agile data science ambitions
* Data Science Patterns: what they are and how they enable agile data science
* Case study: a walk through of some common patterns in use inreal projects
Data Science is ‘defensive’ if it can withstand the disruptions of changing data and requirements while still producing repeatable, explainable insights. Put another way, Defensive Data Science maintains data provenance. Fortunately, the Guerrilla Analytics Principles make it easy to do defensive Data Science . This blog post describes how.