What Makes Cloud Transformation So Hard?
Transformation is not a new concept, and has been around a long time before cloud and big data. It has always been a pretty nebulous term, but generally has referred to the fundamental reinvention or redesign of a business or function. From an enterprise-wide perspective this typically has meant redefining everything from target markets, products [...]
Getting it right with data attribution
There have always, it seems, been people for whom attribution and citation really matter. Some of them passionately engage in arguments that last months or years, debating the merits of comma placement in written citations for the work of others. Bizarre, right? But, as we all become increasingly dependent upon data sourced from third parties, [...]
Seeking Simplicity’s Sweet Spot
Albert Einstein, you may have heard, was a clever man. He scribbled equations on blackboards, thought big thoughts, and all of that. But, allegedly, he also said Everything should be made as simple as possible, but not simpler. These words have resonated with me recently, as I’ve heard pitches from one company after another, all [...]
Find the data, aggregate the data, make the data useful
I was in New York in March, taking part in GigaOM’s Structure:Data event. As usual on these trips, I spent the day before the event walking around the city, soaking up some air, getting rained on, using coffee to stay awake, and meeting with a number of local companies. Of the companies I met that [...]
Justifying Big Data Investment
Traditionally companies invest into software that has been proven to meet their needs and has a clear ROI. This model falls apart when disruptive technology such as Big Data comes around. Most CIOs have started to hear about Big Data and based on their…
Visualisation – the key that unlocks data’s value?
As the Big Data hype machine continues its relentless attempt to gobble everything in its path, new business units and entire new domains buying into the promise find themselves faced with unanticipated data volume and complexity. They see the potential for data-based decision making, but still face (short-term?) challenges in actually managing, analysing or interpreting [...]
To Dublin, in search of evidence
I travelled to Ireland last week, to attend the second meeting of the European Data Forum (EDF). The EDF provided travel support for my trip, and I am grateful to them for that. I was searching for evidence of ways in which smart use of data is having a transformative effect upon European businesses. Although some [...]
Doing the DataBeat
For the past two years, Ben Kepes and I have helped the team at VentureBeat assemble the programme for their annual Cloud Computing event, CloudBeat. It looks as though we may end up doing something similar with them this year, as CloudBeat moves from Redwood City to downtown San Francisco, and from November to September. [...]
Thrive For Precision Not Accuracy
Jake Porway who was a data scientist at the New York Times R&D labs has a great perspective on why multi-disciplinary teams are important to avoid bias and bring in different perspective in data analysis. He discusses a story where data gathered by Über in Oakland suggested that prostitution arrests increased in Oakland on Wednesdays [...]
A Data Scientist’s View On Skills, Tools, And Attitude
I recently came across this interview (thanks Dharini for the link!) with Nick Chamandy, a statistician a.k.a a data scientist at Google. I would encourage you to read it; it does have some great points. I found the following snippets interesting: Recruiting data scientists: When posting job opportunities, we are cognizant that people from different [...]
Is Infochimps running from the Data Market business?
Infochimps is one of the early champions of the data market business, and one that I’ve followed for several years. As I mentioned in my last post on the topic, the company has recently begun to pivot towards delivery of their (compelling) Enterprise Cloud big data analysis offering, with the company’s data market origins slipping further [...]
Continuity Rolls Out Public Beta of its Big Data PaaS
When Continuuity launched late last year I was pretty skeptical given the buzzword heavy press release, light on any real specifics. After spending some time talking with the founders however I was more positive, and not only because of the princely $10M funding round the company had just raised. As I said at the time: [...]
Commoditizing Data Science
My ongoing conversations with several people continue to reaffirm my belief that Data Science is still perceived to be a sacred discipline and data scientists are perceived to be highly skilled statisticians who walk around wearing white lab coats. The best data scientists are not the ones who know the most about data but they [...]
Discussing Data Markets in New York City
As part of GigaOM’s Structure:Data Conference (taking place in New York City on 20-21 March), Jo Maitland and I are going to host a Mapping Session on Data Marketplaces. What are they, what are they doing, why do they matter, and how does their future look? The session is intended to be highly interactive, so attendees [...]
SAP Business Suite on HANA, Because Big Data is a Stupid Term
I spent a lot of time last year talking with vendors about big data and it’s ramifications for both the tech industry and the economy at large. Often these conversations centered around one or another vendor’s use of the big data term as the buzzword de jour, regardless of whether anything they do even vaguely [...]
