Headed out this evening up to Saint John, New Brunswick for the T4G Big Data Congress. I’ll be up there speaking on a panel with associates from a number of Hadoop vendors including Cloudera and Hortonworks on our respective big data platforms.
It will be interesting to see how the audience is currently interpreting big data and the challenges that they face, and I will share my perspectives from the event in the coming days.
I’m personally looking forward to hearing from Tom Davenport, who will be speaking with us as well. Competing on Analytics came out as I was kicking off my 1st tour of duty for IBM in the warehousing space, productizing the old ‘balanced configuration unit (BCU)’ into our first data warehouse ‘appliance’, the Balanced Warehouse. Yeah seems like a decade ago. It will be very interesting to hear his current view on big data in his session and the associated application of analytics.
I’ve never actually been up to Saint John, but have already been warned by the local office that the temperatures will be a bit on the cold side. From 0 to -15 to be exact. Ouch. Reminds me of the MONY tower back in the day in Syracuse – Would always be interesting to make a run to Marshal Street at that negative temperature mark flashing in the sky.
Last week we formally announced and GA’d a slew of new core big data offerings in our big data platform (There was a reason that I have been quiet/offline) and I thought it would be a great time to share them with you all. We started the discussion of our new technologies at the Information on Demand conference at the end of October – but they are now all fully baked in the marketplace.
The 3 new offerings are:
I’ll plan on digging deeper into each one of these offerings over the next few posts – but in summary, we are building out a platform portfolio that is unmatched in the world of big data. We are making it easier for organizations of all sizes to leverage and exploit ‘big data’ to make better decisions.
On the hadoop front, BigInsights not only updates and includes the latest support/versions for the Apache hadoop initiatives but also starts implementing technologies from across the big data platform. In addition to making hadoop more enterprise (rather than a standalone, open source project) BigInsights 2.0 offers a slew of advanced visualizations and tools for users across the organization.
With InfoSphere Streams 3.0, making decisions in real time has just become easier. While Streams has always incorporated a rich programming language (spl) not every user has had the time and effort to master it on the fly. With version 3.0, InfoSphere Streams now incorporates a visual GUI ‘drag-and-drop’ interface to program your own streams… and yes, that interface also generates the proper code as well so that you can alter and enhance granularly as well.
Last but not least, the Vivisimo acquisition in late Spring has already been integrated into the portfolio with the new InfoSphere Data Explorer 8.2 (formally known as Vivisimo Velocity). This offers fast ROI and minimizes risk by helping customers understand their big data assets and unlocking the value – including federated search – leaving data where it is BEFORE you determine if you are going to use it/analyze it….
Yeah – I’m a product guy, and well – new things are cool – so I get a little nerded out when we release offerings like this. In my next blog installments, I’ll drill into each one of these offerings and show you why we added the features and capabilities that we die (Yes, we did listen) – and most importantly how it helps you with your big data initiatives.
It has been a busy summer so far, just getting back home from San Diego the other day for last week’s TDWI world conference. As usual it was a great event, but one thing that was quite apparent at the event was the advent of ‘Big Data’. I don’t mean just the addition of Hadoop based companies to the mix (ie Hortonworks and the like) but most every vendor had some sort of Big Data story to tell. Even SAS had their booth just plastered with Big Data messages, and does not offer any specific ‘Big Data’ product.
For full disclosure, I’m partial to this growth of Big Data promotion in the marketplace, as I recently migrated my professional focus at IBM to this specific area. There is a level of excitement that surrounds Big Data that I have not seen since the early days of Linux adoption. Folks are clamoring to get in on this technology and surrounding buzz. From developers through consultants, many of my warehouse discussions had some sort of ‘Big Data’ piece to it.
So what is ‘Big Data’? That is a question that I hear left and right – not just at the conference, but in general day to day business. In my limited layman type approach to the definition, I refer to ‘Big Data’ as the challenge organizations and professionals have to start using ALL of the data available to them to make better decisions. Are you using all of it – even the stuff you normally throw away.
Does Hadoop help this? – sure – it is a key enabler in the movement.
Does streaming technology ?– absolutely – decisions in motion – awesome.
Data Warehousing? – uh of course – what do you do with all of this Hadoop based data once you sort through it and deem it ‘relevant’?
Look the list goes on and on here, but the fact is that in my opinion ‘Big Data’ is a part of a larger information ecosystem. It is the challenge to leverage all of your data available to you – not just the items that are placed in front of you, but also the ‘digital/data exhaust’ (great term that was created that I openly support) that to this point in time you have not had time to analyze.
I would suggest that part of the issue of understanding is that every company that has a dog in this fight has crafted the message to suit their own needs. Many vendors only have a subset of the products that make up an exhaustive Big Data platform and skew the definition to support this.
At the end of the day – regardless of definition, the question that you have to ask yourself is ‘Would you be better off leveraging ALL of the information that is available to you, to make better decisions?’ If you desire to be an analytical competitor, your answer is definitely yes. This is why Big Data is big …and why the hype is warranted.