There's an incredible amount of hype about AI today. Consumer use cases like self-driving cars and robotics have captured people’s imaginations and shown them that they can make a huge leap with innovation rather than an incremental change. That shift in thinking is exciting, but there’s also a lot of FOMO around AI that means businesses are just trying to tick a box rather than thinking more deeply about how they can use automation to improve their business.
There's been a huge amount of investment in the BI space recently. A recent article by Dave Kellogg talked about the hype in valuation and capital efficiency of many BI companies. It’s an important topic that people purchasing analytics platforms should think about because it says a lot about what priorities a business has.
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.
In the previous blog, we initially discussed how Yellowfin Signals discovered a surprising website traffic spike hidden in our Google Analytics data. So how did we set up Signals? And did we learn anything along the way? Read on below for our learnings and suggested best practice (this is going to be a deep dive, so grab a coffee and enjoy!)
