Some first-wave big data projects 'written down' says Deloitte Consultancy outfit Deloitte reckons early big data projects have had to be written down because they failed, thanks in part to a “buy it and the benefits will come” mentality. The source of failure was sometimes difficulty making open source software work and/or integrate with other systems, Deloitte Australia's technology …
The reasons Big Data projects fail is a complex one.
1) Management believed the hype and their expectations were not met.
2) Those who can work well in the 'Big Data' space are very senior people who have work experience in distributed systems and projects. Techniques that worked well in traditional software development don't always translate to things working well in distributed systems.
3) To be good, you need to spend a bit of time looking at a blank wall.
That means you need to spend time thinking through your problem set before writing a lick of code.
4) Teams need to experiment more and more time doing R&D.
5) Big firms like IBM, Accenture, Deloitte don't understand that you can't take a 10 week wonder and then put them through the basic Hadoop week long training and expect them to perform.
6) The 'hack' (cough) mentality of FB doesn't work well in the real world.
7) Solutions architects need to spend more time thinking about a problem...
8) Developers have to be flexible.
Note while I've said this twice (#3 and #7) its that important.
Posted anon because I do 'Big Data' problems for a living ... ;-)
I still think that "Big Data" is a thing for large scientific projects with appropriate funding and the appropriate time & brainpower levels.
Nothing for consultancy firms, pointy-haired ones sniffing out the "next big one" and fly-by-nights looking for a big/quick buck.
In my experience a lot of "Big Data" can be structured or is already so data warehouse techniques work well and are cheaper than using the latest fashion item.
Any other unstructured data which isn't easily structured is generally worthless anyway and that's why "Big Data" projects don't deliver.
Sorry,
As someone who's been working in the 'big data' space for 4+ years. (Hence the anon posting because its really a small crowd...) I can tell you that its hit mainstream.
However the lack of talent means a higher risk of failure. Too many 'firms' have people with over inflated titles and lack the expertise to do the job.
To your point, the big consultancy firms don't know how to do agile and small teams efficiently. They are the hire the '10 week wonders' (Accenture) and then put them out at clients for $$$$.
The reason I didn't stop at #1 is that while its the main reason for failure... even if you manage the expectations... its getting all of the moving pieces to work together. Not an easy task.
Gartner has been putting out "x% of Business Intelligence projects fail" press releases since at least 2003 and I'm sure I could find a few before that. Periodically other analysts and consultants jump on the same band wagon, for obvious reasons. It was inevitable that the same apocalyptic claims would appear for Big Data.
What they don't reveal, for equally obvious reasons, is the percentage of those projects that fail, despite the assistance of consultants and system integrators.
Sorry to be a bit picky; but it would help if you were to show where you fixed the original, using strike through and bold to highlight the changes. I wish this rag would allow underline as it (underline) and strike through are generally accepted methods of indicating changes.
What they don't reveal, for equally obvious reasons, is the percentage of those projects that fail, despite because of the assistance of consultants and system integrators.
See, now much better.
PS, probably the icon most would like to apply here-------------------------------------->
</pendant>
Its not the tech.
They fail because the businesses didn't know what they wanted them to do. Most businesses have money making bits that work cos people want to buy what they do. Better data mining is, at best, marginal in terms of customer relations and practically useless at developing new markets (hint - its the big demographic that you're not currently selling to).
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