The biggest takeaway from Gartner’s Magic Quadrant (the MQ) this year for me is that organizations, analysts, and vendors now realize that analytics is not linear.
While many businesses are looking to artificial intelligence and augmented analytics, these don’t replace other types of analytics. There’s very little point in delivering sophisticated advanced automated analytics if you haven’t got your ‘bread and butter’ reporting and governance working.
There are three modes of BI. Mode One is traditional reporting, dashboards, and centralized governance. Mode Two is self-service and discovery analysis. And Mode Three is advanced automated analytics and AI.
Table of Contents
Leave no mode behind
These have long been thought of as a linear path. You do Mode One, then Mode Two, and finally progress to Mode Three and don’t look back. But the reality is that it’s more like Maslow’s hierarchy. You need the traditional reporting and dashboards in Mode One as they’re a firm foundation for self-discovery in Mode Two. You then need to get this working well before you can have data exploration and autonomous discovery in Mode Three.
Go back to the beginning and build firm foundations
So, what we're seeing now in the marketplace is a shift back to Mode One. Features of this mode include governance and enterprise security that allows people to access the data they need to do their jobs well.
It’s like taking a step back to go forward.
The challenge for organizations is to make sure they have really stable foundations and good exploratory product sets so that they can move into augmented analytics.
Many organizations are now buying multiple products so they have all three modes, but they often don’t talk to each other. Some vendors, like IBM and Oracle, have multiple tools but they’re disconnected. They have the same logo but they don't have the same architecture. So businesses are spending an awful lot on system integration which isn’t a cohesive enterprise strategy. They’re just building more cost and complexity into their organization.
Remove the complexity
At Yellowfin, we've always believed that you cannot build a solution set without making sure that you have great foundations. So we developed an all-in-one product stack based on what an organization needs. We developed the reporting and dashboards, then added self-service and data discovery, and now augmented analytics into our product set. So, our customers can get automated data discovery with Yellowfin Signals and still get the benefit of all the infrastructure that sits below it.
Organizations are now starting to realize that’s what they need. They need to deliver the basics to everyone before they start providing higher-level analytics. As Gartner said in the MQ, being able to deliver all three is the holy grail of analytics moving forward.
The three stages of analytics maturity
Find out where you are in the three stages of analytics maturity. Here are the three stages spelled out so you know where to advance to next.