Finding the worlds best beer
OK, so here we are at the end of another awesome release of Yellowfin. The theme of this one is Social Business Intelligence and collaboration. Typically, we would bang on about how great all our new collaborative and sharing features are (you can see all that on the showcase page if you are so inclined). Instead, we are here to celebrate. And what better way to celebrate than to have a few Friday afternoon bevies.
It’s summer in Oz, and we’ve got an office full of beer geeks, so a beer is the order of the day. But how to choose the perfect beer for today’s festivities?
Finding the best beer by geography
We kicked-off the selection process by perusing an awesome web site www.beerme.com , which has a great beer list that you can browse at your leisure. The only problem being that we couldn’t search the list based on factors like type or locality. After all, we are a global software company, which means we should be drinking the best beers from around the world. Right?
So, what to do? Get the data into Yellowifn, that’s what. So that’s exactly what we did. At last, the perfect way to find the perfect beer. We did have to do a little work cleaning the data, but hey, totally worth it.
So what did we come up with? This handy world map, which highlights the the highest average beer score by nation, and allows you to filter it to your taste – literally.
Want to give it a shot for yourself? Just use the filters, and drill down on a country of your choice to find a beer to suit your palette. Have fun, and drink sensibly!
Done. Now we can kick-back and celebrate. But hang on, now we have to have a closer look at the data, right? Is this sites data skewed? Can we trust what we see? Will we be disappointed by our order?
Let’s look at the distribution by type – interestingly they have a strong preference for Pale Ales….
How consistent is the tasters scoring?
We wondered how long this site had been rating beers, and how scores had changed over time. Here, we found something interesting.
The scores have steadily increased from an average of 15 to 17.5.
This could mean one of two things:
(Mental note; try not to taste 8000+ plus beers in less than 15 or so years.
You can toggle the series selection to see the number of beers tasted by month.
OK, so we have an issue with scoring. Let’s move on. What does the distribution look like? Our first reaction: ‘Cool a bell curve!’ But hang on, it’s a tad skewed to towards to top end. And what’s going on with the whole number spikes situation on the right-hand-side of the curve?
For this chart, we could have just looked at the total for all beers, but we wanted to know if the distribution differed by type of beer – we set the default to Belgian / French Ales (a favoured beer we assume). Filter to find out for yourself.
Enough already lets celebrate!
Obviously no one is perfect. But hey, what the heck, enjoy! This is getting all too serious and analytical… and where’s my beer? Cheers!
If you want to know more about Collaborative Business Intelligence or our latest release details follow the links.
It’s summer in Oz, and we’ve got an office full of beer geeks, so a beer is the order of the day. But how to choose the perfect beer for today’s festivities?
Finding the best beer by geography
We kicked-off the selection process by perusing an awesome web site www.beerme.com , which has a great beer list that you can browse at your leisure. The only problem being that we couldn’t search the list based on factors like type or locality. After all, we are a global software company, which means we should be drinking the best beers from around the world. Right?
So, what to do? Get the data into Yellowifn, that’s what. So that’s exactly what we did. At last, the perfect way to find the perfect beer. We did have to do a little work cleaning the data, but hey, totally worth it.
So what did we come up with? This handy world map, which highlights the the highest average beer score by nation, and allows you to filter it to your taste – literally.
Want to give it a shot for yourself? Just use the filters, and drill down on a country of your choice to find a beer to suit your palette. Have fun, and drink sensibly!
Done. Now we can kick-back and celebrate. But hang on, now we have to have a closer look at the data, right? Is this sites data skewed? Can we trust what we see? Will we be disappointed by our order?
Let’s look at the distribution by type – interestingly they have a strong preference for Pale Ales….
How consistent is the tasters scoring?
We wondered how long this site had been rating beers, and how scores had changed over time. Here, we found something interesting.
The scores have steadily increased from an average of 15 to 17.5.
This could mean one of two things:
- beers are getting better, or
- the site is making a ton of money on Google ads, and our taster has moved up a notch in the quality stakes.
(Mental note; try not to taste 8000+ plus beers in less than 15 or so years.
You can toggle the series selection to see the number of beers tasted by month.
OK, so we have an issue with scoring. Let’s move on. What does the distribution look like? Our first reaction: ‘Cool a bell curve!’ But hang on, it’s a tad skewed to towards to top end. And what’s going on with the whole number spikes situation on the right-hand-side of the curve?
For this chart, we could have just looked at the total for all beers, but we wanted to know if the distribution differed by type of beer – we set the default to Belgian / French Ales (a favoured beer we assume). Filter to find out for yourself.
Enough already lets celebrate!
Obviously no one is perfect. But hey, what the heck, enjoy! This is getting all too serious and analytical… and where’s my beer? Cheers!
If you want to know more about Collaborative Business Intelligence or our latest release details follow the links.