Written by Roman Stanek |
When was the last time you thought about pagers? How many of you are asking what a pager even is? Their heyday was relatively short-lived, and it’s easy to see why. With pagers, you’d hear a beep and all you could do was check the screen and see if a complete phone number popped up, find a phone, and hope the person who paged you answered when you were finally able to get back to them. No wonder people weren’t getting much use out of pagers—they didn’t do a whole lot. Compare those capabilities to those of flip phones followed by the Blackberry and now today’s smartphones, which are so useful and ingrained in our daily lives that we sleep with one next to our beds. They’re there to wake us up in the morning, tell us when our flights are, help us purchase items, or track our physical activity.
Why are we talking even talking about about pagers? Because it’s a particularly apt example of the role that infrastructure plays in technology. It’s easy to focus only on technological advancements—video calls, apps like Uber or Amazon—that we’ve seen first-hand, but that would ignore the important role that infrastructure played as pagers were replaced by flip phones, Blackberries, and iPhones, and as hundreds of users were replaced by millions of users.
In the early 90s when pagers were on the rise, one cell tower was enough to support an entire city, because so few people were using the network. When you have 20 million people using smartphones on a daily—no, hourly—basis, the infrastructure needs to drastically change or the load on the network would strain it beyond its limits. Today’s smartphones are only able to work as well as they do because companies and communities have continuously been improving their networks to keep up with the technology demands.
I also chose this analogy because it’s almost identical to what’s happening with BI and the move to embedded BI. Traditional BI is the pager in this analogy; it doesn’t do a whole lot, and perhaps just one or two C-level employees log in maybe once a day to take a quick look at a static report. Because its use isn’t widespread, it’s not an integral part of the way the company does business and the load remains low. As a result, the old, outdated infrastructure that helps this solution run can live on.
In contrast, the goal of embedded BI is to support every decision that every employee is making throughout the company, all with insights and suggested actions presented within their daily workflow. With embedded analytics solutions like GoodData Spectrum, I can go into my CRM application each morning, see a list of customers to call that day and which offer I need to extend to each of them, and—taking it one step further— take action within that CRM application. It’s so seamless and personalized that I can’t even see any of the analytics running in the background.
This is an enormous upgrade in terms of capabilities, and it expands the uses for BI far beyond the C-suite. Just as networks needed to be improved for smartphones to run effectively, the infrastructure needed to support embedded BI like Spectrum is in need of a facelift to handle the more robust features and increased load associated with more pervasive use.
If we think back to our pager and smartphone analogy, Spectrum is the smartphone that has revolutionized BI—and GoodData is the infrastructure that provides the support and makes analytics, or in the analogy, smartphone use, pervasive. With an end-to-end platform like GoodData, all of the infrastructure requirements necessary to help a robust BI solution run are taken care of, from improving capacity to accommodate higher load to service-level agreements to data governance. And as more users interact with the platform and more advanced capabilities become available, continuous upgrades help support these changes and keep things running smoothly. For those looking to embedded analytics to help them make business-critical decisions, the robust infrastructure like what we provide at GoodData is absolutely essential.
Written by Roman Stanek |