The Guerrilla Analytics Principles

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There is now a page on guerrilla-analytics.net giving an overview of the 7 Guerrilla Analytics Principles.

I designed the principles to help avoid the chaos introduced by the dynamics, complexity and constraints of data projects. You will find the principles helpful if you work in Data Science, Data Mining, Statistical Analysis, Machine Learning or any field that uses these techniques.

The Guerrilla Analytics Principles have been applied successfully to many high profile and high pressure projects in domains including Financial Services, Identity and Access Management, Audit, Fraud, Customer Analytics and Forensics.

You can read more about the Guerrilla Analytics Principles in my book Guerrilla Analytics: A Practical Approach to Working with Data. Here you will find almost 100 practice tips from across the Data Science life cycle showing you how to implement these principles in real-world situations.

Do you have your own data science experiences and principles? Let me know by getting in touch!

Guerrilla Analytics: Tactics for Coping with Data Science Reality

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Here are the slides from a talk I gave today to the Information Technology Department at the National University of Ireland, Galway. Thanks to Michael Madden for the opportunity to speak.

The talk was about how Guerrilla Analytics principles and practice tips help you do Data Science in circumstances that are very dynamic, constrained and yet required traceability of what you do.

There were plenty of questions afterwards which is always encouraging. I’ll try to address these questions in subsequent blog posts so please do follow me @enda_ridge for all the latest posts.

Here are some of the questions from today.

  • what are the key skills to focus on if you want to work in data analytics / data science?
  • is programming ability a pre-requisite for doing data science? This question came up before at Newcastle University.
  • do the guerrilla analytics principles map to research projects?
  • do the guerrilla analytics principles map to ‘big data’ projects?

Since NUI Galway is a bi-lingual university, you can find my broken Gaelic version below!

As Gaeilge

Seo h-iad na sleamhnáin ó léacht a bhí agam inniú sa Roinn Teicneolaíocht Fáisnéise in Ollscoil na h-Éireann, Gaillimh. Buíochas le Michael Madden as an deis labhairt.

Bhain an léacht le cén chaoi is féidir leis na  prionsabail agus noda Guerrilla Analytics cabhair leat agus tú ag déanamh Data Science i ndálaí atá dinimic, srianta ach fós tá sé riachtanach go bhfuil inrianaitheacht ann.

Bhí mórán ceisteanna tar éis an léacht agus is maith an rud é. Freagróidh mé iad i mblag eile agus bígí cinnte mé a leanacht ag @enda_ridge don scéal is déanaí.

Seo h-iad roinnt de na ceisteanna.

  • céard iad na scilleanna is tábhachtaí agus tú ag iarraidh obair mar data scientist?
  • an gá duit bheith in ann ríomhchlárú le h-aghaidh obair mar data scientist?
  • an bhfuil baint ann idir na prionsabail agus tionscadail taighde?
  • an bhfuil baint ann idir na prionsabail agus ‘Big Data’?