Right now, nothing is buzzier than big data. And with good reason, big data and analytics sales are on a precipitous rise. In fact, they are set to increase 50 percent by 2019. But as we’ve written, bringing big data to scale can be tricky, oftentimes elusive, even if you’re company that’s already collecting and storing troves of data on a daily basis. Suffice it to say that capturing more value from your big data and analytics can be difficult, especially if you’re a small company and not a tech behemoth with a battery of data scientists. Sound familiar?
It sounds pretty familiar to us here at iPass, because we’ve been there. In our case, it all started with a big idea. Global Wi-Fi can be unpredictable. Unlike your home Wi-Fi network, where you can usually expect a consistent user experience, commercial hotspots are different. So we thought, what would happen if we monitored every hotspot in the world, and that way, we could serve up the highest-quality hotspot for your device to connect to.
At iPass, we came to this problem with years of connectivity experience, which had shaped the creation of our intelligent, self-learning Wi-Fi service platform, iPass SmartConnect™. But bringing big data to scale was a crucial step toward making our technically challenging and innovative plans. And to that end, Apache Spark was crucial, as relates our Director of Big Data and Analytics, Tomasz Magdanski, in his latest blog post, on how big data helped us tame the Wild, Wild West of Wi-Fi.