I love data. I live it, I breathe it and I get excited about it. Recently, I started thinking about what creates a data culture when I read the Big Data and AI Executive Survey 2019. It said that 72% of respondents were yet to forge a data culture. While every business uses data in some form, they don’t all use it to truly understand the dynamics of their business and make strategic decisions.
The launch of Signals has been a complete game-changer for us this year. Yellowfin is doing something completely unique in the marketplace and we’re winning some great deals because of it. Signals is an automated data discovery product that delivers alerts to users about critical changes in their business. It’s not about dashboards - this is a completely different way of consuming analytics.
As an innovative company, Yellowfin is focused on delivering new products to market, not just incrementally improving what we have. If you're a software company looking to build your own innovation strategy, there are some things that you need to do, and a few you shouldn’t, to make sure you're successful. The first thing you shouldn’t do is look at your competitors. Many software companies have one great idea and then they stop.
I often get asked why Yellowfin is always the first to market with new products - it’s because of our innovation culture. Our innovation is something that we’ve even been recognized for by BARC and Gartner. Here are three things that we do to create a culture of innovation that enables us to live and breathe new ideas.
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!)
Lots of organizations use Google Analytics and Google Insights to monitor the effectiveness of their digital marketing. While it looks appealing, some of the information it delivers is almost meaningless. It’s so complicated that it doesn’t help you understand what’s happening in your business.
The introduction of AI, automation and data storytelling to the world of analytics has not only had an immediate impact on the end users of analytics but also the people that work in the field. While many analysts may fear they will be replaced by automation and AI, CEO of Yellowfin, Glen Rabie, believes that the role of the data analyst will increase in significance to the business and breadth of skills required.
