I view IBM or especially HP jumping on a bandwagon as a strong negative signal for that technology.
Surviving Data Science at the Speed of Hype
31–40 of 48 posts
Re: Surviving Data Science at the Speed of Hype
#32Earlier quoted context omitted.
How are association rules "big data analytics"? The article is very refreshing and I bookmarked the site. What I am more frustrated with is that a lot of people use this stupid term "big daata" for things which do not fit the description. If it's structured, it's not big data. If it comes at 2MB/s it's not big data. If it fucking fits in your RAM, it most certainly is not big data.
What on earth are you talking about ? (a) Association rules are big data when you are doing them on large data sets with many variables. I work at a company that sells tens of thousands of different products and tens of millions of customers. Definitely takes us a while to compute those rules. (b) The majority of big data is structured. For most big data projects it is typically stored in old school Oracle/Teradata/e…
4 TB is certainly not big data. Many people would agree with this. Additionally your definition of big data is flawed. If I can't open a 2 GB text file with a single application, does that mean it's big data?
Re: Surviving Data Science at the Speed of Hype
#33I once worked at a major big box retailer where somebody came up with a visualization that purported to show, for a given product category, purchases made in other categories. One surprising purchase correlation was customers bought TV stands after buying DVD players. So, this nugget was trumpeted at countless meetings about the value of big data analytics. Multiple marketing campaigns were designed around this disco…
> One surprising purchase correlation was customers bought TV stands after buying DVD players. So, this nugget was trumpeted at countless meetings about the value of big data analytics. Multiple marketing campaigns were designed around this discovery.
> Of course, that made no sense, so I checked a little deeper.
And there was me thinking it made sense, because I'd done the same thing. A TV can stand on many surfaces, but once you've got a DVD player (some thin, wide rectangle) it makes a lot more sense to get a TV cabinet to put the DVD player in.
Perhaps not so much sense now, but 8-9 years ago I went through this logic.
Re: Surviving Data Science at the Speed of Hype
#34I'm a data scientist that works with companies on their analytics problems every day. This article is spot on. By far the biggest factor influencing the success of an analytics project is that the company has a human who has the time and inclination to think and reason about the business. They figure out what questions are important to ask and then go look at the data to see what they find. Collecting the data is the…
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Re: Surviving Data Science at the Speed of Hype
#35Earlier quoted context omitted.
It looks like an interesting book. Anyone have experience with the ebook version? Does it hold up with the illustrations, or should I hold out for a hardcopy?
I have the ebook version, it's fine if you're ok with ebooks for this sort of stuff.
Can you recommend some other books that are good introduction to analytics/data science? I often get asked for recommendations, but can't seem to find something suitable for beginners.
Dickrolls to be avoided if possible, but secretly kinda wishing...
Re: Surviving Data Science at the Speed of Hype
#36Earlier quoted context omitted.
I have the ebook version, it's fine if you're ok with ebooks for this sort of stuff.
Can you recommend some other books that are good introduction to analytics/data science? I often get asked for recommendations, but can't seem to find something suitable for beginners. Dickrolls to be avoided if possible, but secretly kinda wishing...
I unfortunately don't know too many others. I have this book as well: http://www.amazon.com/Machine-Learning-Science-Algorithms-Se... and because I'm so far removed from any academic math study now in my life, by about page 3 I was lost.
My plan is to dive into Linear Algebra and Statistics book and courses first before I head into ML again.
Re: Surviving Data Science at the Speed of Hype
#37all this will change with the internet of things. once every "thing" is networked, then these optimization platforms won't need to wait for some human to input info about altered environments. the platform will "sense" it.
Re: Surviving Data Science at the Speed of Hype
#38Earlier quoted context omitted.
I have the ebook version, it's fine if you're ok with ebooks for this sort of stuff.
Can you recommend some other books that are good introduction to analytics/data science? I often get asked for recommendations, but can't seem to find something suitable for beginners. Dickrolls to be avoided if possible, but secretly kinda wishing...
Doing Data Science is a pretty good intro.
http://www.amazon.com/Doing-Data-Science-Straight-Frontline/...
Re: Surviving Data Science at the Speed of Hype
#39Earlier quoted context omitted.
Exactly - the human with domain knowledge is vital. I get scared when I see people trump up black boxes. Black boxes don't help with "Which questions should we be asking?" and "What are the missing variables?"
Domain knowledge is also really useful for spotting bugs. I recently worked on a project where I had very little domain knowledge. So anyway I wrote my code, ran my tests, crunched the data, double checked that all the results seemed reasonable, produced the pretty pictures and everything looked spot on. However once I started showing the results to a domain expert it took him 30 seconds to point to one of the output…
True. The ability to sanity check is very important.
Re: Surviving Data Science at the Speed of Hype
#40Amen