Blogs
If there’s more and more data arriving and time isn’t expandingi, then data must be arriving at greater and greater velocity.
In my last post I talked about Variety in the Volume, Variety, Velocity triumvirate. There’s more to be said about that, but first I’d like to take a run at Velocity. We’ve got used to the idea that you load stuff into a database (or other data store) then you take a look at it. That’s just too slow for lots of operational decision making processes. And if you think about it, as the volume of data available increases the bar is constantly rising on real-time analysis. But for many kinds of decisions, you just need the data that comes with the event you want to decide about: is this a fraudulent transaction? Was this call dropped?
We'll start from the very beginning. It's a very good place to start...
Big data is all about Velocity, Variety and Volume, and the greatest of these is Variety. At least it causes the greatest misunderstanding.
I tuned into the recent US federal government’s web-cast. I was curious to see what a government big data initiative would look like, as my government (UK) is unlikely to produce anything equivalent any time soon. They and their opponents are too busy trying to prove that they’re not entirely removed from the concerns of the ordinary citizen.
| Tags: | | | Permalink | | | 0 Comments |
Last week I was in Bucharest and Ljubljana, but before I headed to the airport on Monday I recorded a webinar – doubtless I’ll be blowing my own brass section about how and when you can watch it, when I know that. Usually for webinars, as for other presentations, I have my own slide deck, which is almost always a slight variation of a previous one, but on this occasion I was using a pre-set deck because I was a late substitute for the planned speaker. The deck, as usual, included a bunch of Netezza customer stories, including one I wasn’t familiar so I had some reading to do over the weekend to get acquainted with it.
| Tags: | | | Permalink | | | 0 Comments |
I was speaking at a conference last week (Heliview BI, in Holland) and my theme, as is pretty usual now, was the place of the data warehouse in a big data strategy. I had a packed room, but I suspect, it was the title not my reputation that filled it. It went well, as it usually does. I think that’s because I pitch it from the business benefit angle and spend more time on the use cases, than the technology.
2011 finished with the European leg of the 2011 Global Netezza Roadshow. We shared product updates, customer case studies and just got together with our community in Paris, London, Milan and Frankfurt. A year ago I wrote about a great restaurant in Milan that I visited when I was there for the Netezza roadshow in 2010 and, true to form, I ate well there on this trip too - especially the place that has a chocolate board as well as a cheese board!
This year was my first IOD. I hope it won’t be the last because it was a really good conference. These big shows are always difficult, despite the mobile apps, the maps, the schedules, the signage and many helpful show guides. I still have difficulty getting to the sessions I want to see or being frustrated that I want to see two clashing sessions, never mind the miles you walk at these events; I suppose that’s some contribution to exercise.
It’s a question that came up in Ray Tacoma and Phil Francisco’s Q&A session at IOD and it’s a question I’ve answered at the IBM Netezza booth in the exhibition. Smart Consolidation demands an answer, just as every workload optimized platform in the Smart Consolidation portfolio needs to be applied to the right analytics use cases that an organization is addressing.
I’ve spent a fair bit of time recently learning about InfoSphere Streams and BigInsights, as I’ve been working on the Smart Consolidation story.
For a while now at IBM Netezza we’ve been observing that the grail of a unified Enterprise Data Warehouse (EDW) is often not achieved. It still remains an ideal - all your data, cleansed, de-duplicated, governed, in one single place - but in reality not all organizations that attempt it, have achieved it and plenty have abandoned it as a goal - preferring a core EDW with a proliferation of application-specific data marts surrounding it.
