When I went to work years ago, the practice of advanced analytics had an aura of black magic. The insights from corporate data were delivered by a few highly trained scientists who worked their wonders behind a curtain. They owned all data-driven insights.
When business analysts and other users wanted to gain fresh access, they walked down the hall and made a request to the wizards in the white coats, and then they waited days or weeks for the answers to come back. The process was not democratized in any manner and didn’t match the speed of the business.
This was pretty much the way it was in the analytics world in the ’80s and ’90s, and then about 10 years ago things started to change in fundamental ways. As the tools for analytics matured and proliferated, they became easier to learn and more accessible to a wider range of users. In many cases, users no longer needed to be masters of algorithms and complex scripting to leverage analytics tools. Instead, they just need to have a clear view of what they wanted to know and an understanding of how to get the analytics tools to deliver the answers.
It was at that point, data analytics entered a new era—the era in which the analytics silos of the past gave way to a new world of analytics orchestrated by many. Basically, the silo gave way to a symphony. And this is very much the atmosphere we have today. The business of extracting insights from data is no longer carried out by a chosen few who work their magic in the shadows of the business. Today, business managers, business analysts, data analysts and various other corporate players have a hands-on role in the process of gaining insights from massive amounts of data. And so, too, do the DevOps teams that now routinely embed analytics functions into their enterprise applications.
Even better, the analytics symphony doesn’t stop there. Today, it also includes people on the front lines of the business, like call center staff members who field customer concerns and facilitate the ordering process. Thanks to analytics tools, they now might be able to see a ranking of a particular customer’s importance to the business based on sales volumes or other metrics while they are in the midst of a call.
In a term popularized by Gartner, today’s enterprises have growing numbers of “citizen data scientists.” This term refers to people who work outside the fields of statistics and analytics yet routinely touch and deploy analytics tools that yield insights that keep the business competitive. This is a trend that has a lot of momentum. Consider this prediction from a Gartner analyst: By 2017 the number of citizen data scientists will grow five times faster than the number of expert data scientists.[i]
Observations like that underscore the notion that we are entering a new era for data analytics. We are now at the point where many people within an enterprise can put analytics to work to make better-informed decisions, detect performance trends, recognize new opportunities and meet other business objectives.
Here’s the bottom line: To capitalize fully on big data in a large enterprise, it takes many players, each of whom has a unique contribution to make. You’ve just got to put the right analytics instruments in their hands.
For a closer look at some of the common use cases for today’s analytics tools, visit dell.com/statistica.