Tips for Training Co-Workers in Excel

A friend of mine said yesterday that knowing Excel was everything you need to know these days. It was a joke of course but it had an ounce of truth in it. It made me think again about the role of this application in the office life and even more on the way we acquire the skills. In my opinion the workplace is where we get the most of it and it is in the best interest of organizations to provide better environment for that. External Excel trainers are good only to an extent as they are usually far from the business context, not that flexible, do not have enough time outside the classes and are expensive. A better alternative is the in-house training by an employee with proven expertise. Another is hiring a trainer that comes from or still is in a business similar to yours to do a customized class. I would like to share with you some tips from my experience for a successful in-house Excel class. It is assumed that the class will be held by a non-professional lecturer. 

So You Think You Are THAT Good with Excel?

So you think you are an Excel guru with a ninja black belt skills? I hope you are! The good news is you could challenge the world and test your worth! There are few Excel contests that would give you the opportunity to do just that.

Things to Consider When Selecting a Data Mining Software

Data mining software package is not something we usually choose. It either already in place in the company or taught in the university or the decision is made on corporate level. However with the growing number of companies tapping into the power of analytics the question probably is asked a lot. I have recently been asked for an advice for a good data mining software and I came up with some points I would like to share with you.

Excel Tip: Dynamic Named Ranges

Named ranges are a great tool in Excel. It helps writing and reading formulas faster, make less range-related errors and if you are not using it in complex calculations, you should. Directions on defining and using them you could find here. The functionality is simple but you should pay attention to the names you assigned to the ranges - you want name to be meaningful and unique. Otherwise you would waste time checking what was behind that name and reduce its benefits.

The Do’s and Don’ts of Data Mining

Checklists and Business Intelligence-like "Ten Things You Need to Know" over a huge and general topics have dubious value or impact. This is probably because we tend to read them fast and between other stuff as well as it seems that we all know better everything included there. However, sometimes it is really worth to pause and reflect on some of the included topics. KDnuggets recently published an article about the do’s and don’ts of data mining that is a fine example of this. As you might expect, a practitioner would find lot of "I know that" there and often it is hard won knowledge. Still, it is worth to stop and think for while over the topics as in the daily hurry and pressing deadlines we tend to go in a frame and veer off the best course of action.

Pedestrians Are the New Threat to the Nature

The war waged by governments, mindless green-heads, NGOs and a selection of free-roaming lunatics on the global warming had a range of effects on society. One is the  new breed of eco-minded people could finally find financing to go the rainforest where they are bitten and die, get lost and die or take some pictures for their Facebook timeline and return safely home to die by an unknown parasite. Other consequence is that some rich people could get even richer by selling cheap movies or inventing a new trading papers. But my point is not about that. It is about the pedestrians and their found hate towards cars.

Defining Big Data

Would you be surprised if I told you there is not one broadly accepted definition for "big data"? Would you be surprised if I told you 99.99% of people using the term have never even tried to find a definition for it? I bet you won't. I know some people who use "big data" for spreadsheets with more than thousand rows, some other use it every time they talk about something related to data and have no idea what they are talking about - this seems to be a common case actually. Relying on gut feeling could be misleading. Two computer science students attempted to catalog  all the definitions out there. You can see the article at  arXiv:1309.5821 . 

"Trouble with the Curve" and Some Lessons for Analytics

Yesterday I saw Trouble with the Curve starring Clint Eastwood and Amy Adams. It is a movie with a predictable plot and typical characters but still nice to watch. What is interesting is that unintentionally it makes a good point about applicability of data analytics and statistics in decision making process as well as reveals some hidden dangers of relying too much on it.

The P-Value Was Never Meant To Be Used The Way It's Used Today

I have just came across Scientific method: Statistical errors  published Nature's website. I found it a very good article about the misuse and misinterpretation of p-values and about scientific evidence in general. It says, among other things, that “the P value was never meant to be used the way it's used today.”. I was not aware of the history of introduction of this measure and it was interesting thing to read. I was not surprised by some of the points about the quality of scientific research as it has been covered a lot by Taleb, Goldacre and Ioanidis to mention a few but it was nice to see the connection between these two. The author suggest an approach to curb the p-hacking effects in science but considering the nature of science studies these day I do not believe it is applicable for the majority of research. There is other good thing to learn in the article, so please read it yourself.

Ban GDP as A Driver in Regressions!

If there is one thing in analytics that grinds my gears it is the overuse of GDP as a driver in regression. If it were up me, I would ask the government and academy of science to issue a book with all approved regression drivers and distribute it as a standard repository for all knowledge and wisdom there is related to regression. Then one copy of this book and one copy only would include GDP. This copy will be in Klingon and as a precautionary measure will be booby trapped with a potent explosive and buried 100m in the ground. On the Moon. On the dark side of it.