ENTRIES TAGGED "big data architecture"
Yet again, I reveal the base instincts driving my interest in big data. It’s not the science – it’s the cash. And yes, on some level, I find the idea of all that cash sexy. Yes, I know it’s a failing, but I can’t help it. Maybe in my next life I’ll develop a better appreciation of the finer things, and I will begin to understand the real purpose of the universe…
Until then, however, I’m happy to write about the odd and interesting intersection of big data and big business. As noted in my newest paper, big data is driving a renaissance in IT infrastructure spending. IDC, for example, estimates that worldwide spending for infrastructure hardware alone (servers, storage, PCs, tablets, and peripherals) will rise from $461 billion in 2013 to $468 billion in 2014. Gartner predicts that total IT spending will grow 3.1% in 2014, reaching $3.8 trillion, and forecasts “consistent four to five percent annual growth through 2017.” For a lot of people, including me, the mere thought of all that additional cash makes IT infrastructure seem sexy again.
Of course, there’s more to the story than networks, servers, and storage devices. But when people ask me, “Is this big data thing real? I mean, is it real???” the easy answer is yes, it must be real because lots of companies are spending real money on it. I don’t know if that’s enough to make IT infrastructure sexy, but it sure makes it a lot more fascinating and – dare I say it, intriguing – than it seemed last year.
In life, sex is the key to survival. In business, cash is king. Is there a connection? Read my paper, and please let me know.
Get your free digital copy of Will Big Data Make IT Infrastructure Sexy Again? — compliments of Syncsort.
Diversity and manageability are big data watchwords for the next 12 months.
Here are some of the key big data themes I expect to dominate 2013, and of course will be covering in Strata.
Emergence of a big data architecture
The coming year will mark the graduation for many big data pilot projects, as they are put into production. With that comes an understanding of the practical architectures that work. These architectures will identify:
- best of breed tools for different purposes, for instance, Storm for streaming data acquisition
- appropriate roles for relational databases, Hadoop, NoSQL stores and in-memory databases
- how to combine existing data warehouses and analytical databases with Hadoop
Of course, these architectures will be in constant evolution as big data tooling matures and experience is gained.
In parallel, I expect to see increasing understanding of where big data responsibility sits within a company’s org chart. Big data is fundamentally a business problem, and some of the biggest challenges in taking advantage of it lie in the changes required to cross organizational silos and reform decision making.
One to watch: it’s hard to move data, so look for a starring architectural role for HDFS for the foreseeable future. Read more…