Last week, we looked at how we got from relational databases to big data and real-time analytics. This week, we’re taking a deep-dive into how a real-time business intelligence system works. If you’ve used a real-time dashboard before, or are planning on building one in future, this post can serve as a primer to help you understand what happens behind the scenes, and how the real-time data reaches your dashboard.
‘Real-time’ has become a buzzword in recent times. Every other product we come across touts its real-time capabilities. When evaluating a new tool for your marketing, sales, or operational needs, you may have considered real-time as a necessary requirement. When reading articles on popular tech blogs, you’ve probably come across the term every other day. Yet, for many, the phrase ‘real-time’ is like a popular stranger that everyone talks about, but a stranger nonetheless. They wish they knew what all the buzz is about, but don’t know where to start. If that’s you, this series will serve as a great starting point in your understanding of what real-time data is all about.
Foursquare is a great way to let friends know what we're up to, or check reviews of a local restaurant. With the popularity of Foursquare, and the numerous 'check-ins' by users, it has a pretty good idea of what people are doing at different times of the day. Recently, Foursquare decided to use the data users give them to visualize how we move about in some major cities. They took check-in data over the period of a year, and plotted it over a map, updating it by hour of day. The result is quite fascinating, especially if you live in one of these cities.
We've spent the past few weeks discussing predictive analytics in much detail. We started with an overview of predictive analytics, then took a tour of various companies doing outstanding work in predictive analytics today, and finally reviewed the awesome dashboards of Recorded Future and Sift Science. In this final post, we look at some common, yet relatively unnoticed applications of predictive analytics in our daily life.
I’ve spoken in some detail about what Sift Science does in my previous post. As a quick reminder, Sift Science helps e-commerce businesses fight fraud using the power of machine learning and predictive analytics. They collect diverse data, glean signals from it, and assign a ‘Sift score’ to every user which predicts how likely it is that a particular user is a fraudster.
We're back with our round-up of the biggest news on big data, business intelligence, and data visualization. Going forward, we'll be doing this on a bi-weekly schedule, which we think would be the ideal frequency. 1. Explaining machine learning to non-computer-science people Quora is a great place to find nuggets of interesting conversations between prominent… Read More »
Over the past few weeks we’ve been discussing predictive analytics at length. We started with an overview, and then went on a tour of 9 unique businesses that are leading innovation in predictive analytics. So far, we’ve just set the stage for this and the next post, where we take a focused look at the visualization methods and concepts used in predictive analytics products today.