We have entered the era of big data, but many questions remain unanswered. For instance, who owns all of this information, anyway? If you take a photo and post it on Facebook or Twitter, does it still belong to you? If you create a presentation with Google Docs, does Google
In his recent Financial Times article, Tim Harford explained the big data that interests many companies is what we might call found data – the digital exhaust from our web searches, our status updates on social networks, our credit card purchases and our mobile devices pinging the nearest cellular or WiFi network.
If you have been following this thread for a while, you may notice a theme that I keep bringing up: data virtualization. I'm trying to rectify a potential gap in the integration plan involving understanding the performance requirements for data access (especially when the application and database services are expected
Business intelligence is now accessible to companies of all sizes and sectors. I run a small business and we have incredible reporting and analytical capabilities that allow us to model every aspect of our operation. We can create dashboards of website traffic, article distribution, revenue performance, social media analytics and
"Most” organizations are embracing big data. For instance, a 2013 Gartner survey found that 64 percent of enterprises were deploying or planning big data projects, up from 58% the year before. Those numbers simply don't fit with what I’m seeing, and I suspect that I'm hardly alone. (By way of
As an unabashed lover of data, I am thrilled to be living and working in our increasingly data-constructed world. One new type of data analysis eliciting strong emotional reactions these days is the sentiment analysis of the directly digitized feedback from customers provided via their online reviews, emails, voicemails, text messages and social networking
To a great extent, the data manipulation layer of our multi-tiered master data services mimics the capabilities of the application services discussed in the previous posting. However, the value of segregating the actual data manipulation from the application-facing API is that the latter can be developed within the consuming application’s
Data profiling is a core technique of data quality management and often the starting point for so many projects these days. Because it’s such a relatively simple technique to apply, it’s easy to overlook some of the more advanced techniques that can take your data profiling to the next level.
With respect to data, there seem to be a few types of companies: Those that do fairly little with the value of their data. I've consulted for quite a few. Those that maximize the value of their data, often controversially. Facebook and Google are squarely in this group. Those that maximize the
In his book Where Good Ideas Come From: The Natural History of Innovation, Steven Johnson explained that “error is not simply a phase you have to suffer through on the way to genius. Error often creates a path that leads you out of your comfortable assumptions. Being right keeps you in
