While the field of data science is not tied directly to Big Data, advances in one tends to produce advances in the other. Big Data increases our ability to harvest and process data, while data science allows us to dig into it for insights.
There are hundreds of hotel booking sites online. They all have their own method of matching customers with options. There are basic options, like how many bedrooms for less than $200, and users will still end up searching through several pages before finding the right offer. Generic offers and bad
At a blistering pace and for a variety of reasons, companies are migrating their on-premise database infrastructures to cloud-based solutions—to save costs on hardware, tame the impact of disaster recovery or even to improve security. As the missing pieces of the Cloud continue to be identified and put into place,
Psychological research requires a lot of testing, and a lot of surveys. When relying on surveys, there is a necessary assumption that the subject can be trusted, and that they are answering factually rather than guessing or feeling. Much of the reporting around depression is based entirely on these surveys.
NASA is often on the front end of tech trends. They are constantly coming out with new tools, releasing incredible footage and data, and even support open source communities. Given how much information they can and often need to receive from their space equipment, it is no surprise that they
The rise of Big Data, and the industry’s IoT craze, are driving huge demand for streaming data analytics. There’s an impediment though: streaming data is hard to work with. 2016 will heighten the demand, and also the tension around the difficulty. It may also force a solution. In the big-data
Brands utilising big data are cultivating an ‘insight economy’ where every business move is mapped out with pinpoint accuracy thanks to the internet of things (objects that send and receive data) building a connected world. Businesses are leaping at the chance to embrace ‘cognitive computing’, a process where coding, tools
MDM still has the potential to meet many critical needs in this data-rich environment, but only if it can keep up with changing times. Let’s start with the obvious: We’re already drowning in data, and it just keeps coming. We need to gather, store, collate and analyze it, because we
The IoT already produces massive amounts of data. It’s time to start dealing with it. Is Fog and Edge Computing inevitable? What happens when the cloud isn’t enough? This is a modern problem if there ever was one. Experts are saying 2016 will mark the rise of a new system:
You probably had some big ideas in mind when you first started thinking about adopting big data solutions for your business. There’s usually a tinge of excitement when it comes to big data, and business owners are eager to tap into all its potential. Hiring a qualified data science team
If you listen in on what people are talking about at Big Data conferences, chances are you’ll hear a lot of buzz around Hadoop and Spark. People often think of Hadoop and Apache Spark as key tools for tackling a wide range of big data challenges, but they assume that