Why Speed Matters When It Comes to Querying Your Data
When evaluating new tools, speed can sometimes be at odds with how many bells and whistles it comes with or how much information it can handle. You can get a CRM platform with a ton of features, but it’ll take a while for your team to understand how to use them. You can get the most highly tailored automated email generator but exponentially increase the time it takes to generate an email.
When it comes to analytics and querying your data, speed matters.
From everyday search engine queries to enterprise-level data queries, getting results as quickly as possible is just as important, if not more so, than the volume of data that can be stored or the complexity limits of a query.
As we’ll talk about in this post, this conclusion is based on how people actually search for things—as a multi-step, imprecise process that follows the speed of thought, not a single detailed question.
To start thinking about how people ask questions of their data, it helps to look at a place where 3.5 billion queries are submitted each day: Google.
Even five years ago, when you did a Google search, you were on average searching through an index of 52,000,000 pages.
But according to a 2015 Chitika study, the first result alone got an average of 32.5% of the total traffic. And forget about looking at the second or third page of results — only 8% of traffic makes it there.
People are really only clicking on the first few results, which seems to point to the conclusion that they must be finding the links they want within those results. Out of those 52,000,000 pages, are people using picture-perfect search terms that get them the exact result they need within just the first four?
Probably not. Let’s take a look at another statistic: the number of words used in Google queries.
94% of searches use five words or fewer. And over a third of searches are just a single word!
If people were finding the results they wanted straightaway, you’d expect them to need more words to get there. Short search queries tend to give broader results, with what you want buried further down the list or a few pages in. But we know that people aren’t clicking on those later results. This suggests that people aren’t actually finding what they want in one search, but are searching using an iterative style, formulating many short search queries until what they want shows up in the first few results.
For example, let’s say you want to learn about different types of cloud computing environments. You’ll probably search something like “cloud types.” Whoops. All the results on the first page are about realclouds. But you’re not going to waste time looking through results until you find something that has to do with cloud computing (not until page 4, by the way). Instead, you’ll change your search to something like, “cloud computing types.” From the titles of those results, you’ll see that there’s discussion of public, private, and hybrid clouds, so to get more detailed, you’ll search “hybrid clouds.” But you’re more interested in advantages and disadvantages than definitions, so you search “hybrid cloud benefits,” which gets you to a link you’ll actually click on.
