Community posts are submitted by members of the Big Data Community and span a range of themes. No longer ring-fenced by the IT department, big data has well and truly become part of marketing’s remit. A deluge of data flowing from the ever-increasing number of offline and online media, coupled with rapid changes in consumer behaviour – the way people shop, work and relax – is making marketers’ job more difficult. But despite the complexity of big data, it offers huge opportunities for brands to drive value from their customer information.
This is a guest post written by Scott Raspa. He works at IKANOW, a big data software company, where he is involved in the company’s sales and marketing efforts supporting public and private sector clients. He can be found on Twitter @sraspa. Big Data is the biggest trend in IT right now, however the term is loosely thrown around and becoming increasingly ambiguous. Everyone seems to be doing some sort of “Big Data” nowadays, which can cause great confusion among organizations with actual Big Data needs. We at IKANOW focus on unstructured data analytics, and may be a little bias, but believe it is an essential part of any Big Data offering.
This is a guest post written by Jagadish Thaker in 2013. Hadoop is changing the perception of handling Big Data especially the unstructured data. Let’s know how Apache Hadoop software library, which is a framework, plays a vital role in handling Big Data. Apache Hadoop enables surplus data to be streamlined for any distributed processing system across clusters of computers using simple programming models. It truly is made to scale up from single servers to a large number of machines, each and every offering local computation, and storage space. Instead of depending on hardware to provide high-availability, the library itself is built to detect and handle breakdowns at the application layer, so providing an extremely available service along with a cluster […] Continue Reading
It won’t be long before the amount of data produced by machines surpasses the amount of data produced by all humankind combined. That’s a lot of data! Most of this will be streaming in from the IoT, or Internet of Things, which has either gone mainstream or is on the very verge of doing so. Yet only about 8 percent of enterprises have monetized their IoT data streams, and even there, they are only monetizing about 25 percent of what is available. That is expected to change, and soon. Within a couple of years, half of all enterprises will have monetized their IoT data. Here’s how that will change data analytics as it’s always been known. The IoT Will Change […] Continue Reading
Machine learning is absolutely cutting edge. It’s bright, shiny, and new, and only the coolest of cats are even doing it yet beyond a few simple test environments. But just like that lawn mower you bought back in ’04 or the PC you scored on Black Friday in ’13, ML (machine learning) won’t be new and shiny for long. In fact, the models and algorithms you developed just last year are already probably starting to deteriorate. Maintenance isn’t as fun or interesting as building sexy new ones, but over time the performance declines unless algorithms are monitored and tweaked on a regular basis. Here’s what you need to know to properly feed and care for your ML apps. The Concept […] Continue Reading
This blog post is part of the Big Data Week Speaker interviews series. Scott shares his thoughts about the the impact of big data in the travel field, also offering a sneak peek into his talk at the “Big Data in Use” Conference. Why is it important for businesses in your industry to be more data driven nowadays?
This blog post is part of the Big Data Week Speaker interviews series. Wael shares his thoughts about the impact of big data in the business landscape, also offering a sneak peek into his talk at the “Big Data in Use” Conference. Why is it important for businesses to be more data-driven nowadays? Everything still begins with the synthesis and analysis of data. So let’s start by asking, “What kind of business challenges are data challenges?” The short and unsurprising answer is that they’re all data challenges. There may also be matters of operational change, business process, compliance, and so on – it still begins by knowing where you are, knowing the state of the world around you and sourcing the ever-richer set of data […] Continue Reading
The cloud has transformed big data analytics with its agility, elasticity, transparency and simplicity. Keyur shares tips to leverage the power of the cloud for Big Data Analytics based on his real-life experiences at Betfair.
Working on the first Data-Lake-as-a-Service in the world gave us the perspective of how Data Lakes enable companies to understand correlations between existing and new external data in ways traditional BI tools cannot. The rise of Docker & containerized microservices has paved the way for significantly faster deployment, less overhead, easier migration & faster performance for big data apps.